Executive summary 

A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see Cybersecurity industry tracking), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [1].

LAUNDRY BEAR’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data. Previous campaigns indicated LAUNDRY BEAR relied on unsophisticated initial access techniques—including password spraying, phishing, and pass-the-cookie—allowing the group to successfully run high-volume operations. The latest campaign targeting ZCS uses a novel exploit that was a zero-day vulnerability when first exploited and continues to be successfully exploited. The vulnerability, Common Vulnerabilities and Exposures (CVE) CVE-2025-66376, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.

Unlike traditional phishing campaigns that persuade a user into taking an action, such as clicking a link or opening a file, LAUNDRY BEAR’s latest campaign leverages a view-based exploit that only requires a user to view a malicious email within a vulnerable version of the webmail service. Once viewed, the exploit attempts to exfiltrate the victim’s last 90 days of email communications, the organization email directory (i.e., Global Address List [GAL]), and other sensitive information to servers controlled by LAUNDRY BEAR. The exploit also attempts to establish persistent access to victim accounts through a variety of means as detailed in the Persistence and credential access section.

This Cybersecurity Advisory (CSA) warns of this ongoing malicious threat activity and urges organizations to update their vulnerable software and implement additional mitigations to thwart these Russian state-supported actors’ continued success. The CSA is being released by the following authoring and co-sealing agencies:

• United States National Security Agency (NSA)
• United States Federal Bureau of Investigation (FBI)
• Netherlands Defence Intelligence and Security Service (MIVD)
• Netherlands General Intelligence and Security Service (AIVD)
• United States Cybersecurity and Infrastructure Security Agency (CISA)
• United States Defense Counterintelligence and Security Agency (DCSA)
• United States Department of Defense Cyber Crime Center (DC3)
• United States Department of the Treasury
• United States Naval Criminal Investigative Service (NCIS)
• Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
• Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
• New Zealand National Cyber Security Centre (NCSC-NZ)
• United Kingdom National Cyber Security Centre (NCSC-UK)
• Czech Republic National Cyber and Information Security Agency (NÚKIB)¹
• Danish Defence Intelligence Service (DDIS)²
• Estonian Foreign Intelligence Service (EFIS)³
• Finnish Defence Intelligence (FDI)⁴
• Finnish Security and Intelligence Service (SUPO)⁵
• French General Directorate for Internal Security (DGSI)⁶
• French National Cybersecurity Agency (ANSSI)⁷
• Italian External Intelligence and Security Agency (AISE)⁸
• Italian Internal Intelligence and Security Agency (AISI)⁹
• Security and Intelligence Service of the Republic of Moldova (SIS RM)¹⁰
• Polish Foreign Intelligence Agency (AW)¹¹
• The Military Counterintelligence Service of Poland (SKW)¹²
• Spain National Intelligence Centre (CNI)¹³
• Sweden National Cyber Security Centre (NCSC-SE)¹⁴

The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the Mitigations section of this advisory to reduce the risk associated with this activity. This CSA also includes specific remediations for organizations to implement if they discover the presence of the listed Indicators of compromise (IOCs).  

As more organizations update their ZCS software based on this CSA, LAUNDRY BEAR may discontinue the current campaign exploiting this vulnerability; however, based on the success of this and previous campaigns, it is very likely that the group will continue to target ZCS and other email systems used by organizations in Western countries. The actors will almost certainly continue to rely on email to engage potential victims by exploiting novel vulnerabilities and, when necessary, use social engineering techniques to assist with their efforts. The authoring agencies recommend organizations regularly update their mail service software and continuously monitor their email systems and emails for malicious activity.

For a downloadable list of IOCs, see:

• AA26-204A.stix.xml (STIX XML)
• AA26-204A.stix.json (STIX JSON)

Cybersecurity industry tracking

The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to these Russian state-supported cyber actors. While not exhaustive, the following are threat group names commonly used for these actors within the cybersecurity community:

• LAUNDRY BEAR
• Void Blizzard [2]
• CL-STA-1114 [3]
• TA488 (formerly UNK_PitStop) [4]

Note: Cybersecurity companies have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the U.S. government’s understanding for all activity related to these groupings.

Background

Public advisories from Netherlands General Intelligence and Security Service (AIVD), Netherlands Defence Intelligence and Security Service (MIVD), and Microsoft highlighted these Russian state-supported advanced persistent threat (APT) actors in May 2025, calling them LAUNDRY BEAR and Void Blizzard respectively [1] [2]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.  

The May 2025 advisories highlighted a cluster of activity targeting cloud-based email environments, including Microsoft Exchange in particular, and abusing legitimate APIs to perform data exfiltration in bulk [T1114.002]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [T1078], and using social engineering techniques to lure targets into interacting with a malicious site masquerading as a legitimate one. As of April 2025, one of these sites resembled a European Defence & Security Summit registration portal that required registrants to sign in to their Microsoft account to view. Once a user entered their Microsoft credentials into this malicious site, LAUNDRY BEAR’s modified version of the open source adversary emulation toolkit, Evilginx, intercepted the user’s credentials. LAUNDRY BEAR then used this authentication data, including passwords and session tokens, to access the compromised account and conduct mass email exfiltration, as well as harvest other information. This method of compromise is commonly known as an adversary-in-the-middle (AiTM) technique [T1557].  

Beginning around July 2025, LAUNDRY BEAR shifted toward a more technical method of email compromise, highlighting their continued efforts to covertly acquire email communications from a variety of Western organizations of interest and deliver them to the Russian Federation. Using a custom-developed capability [T1587.001] named “Улей” or “Ulej” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [T1114]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:

• Last 90 days of emails,
• Email address,
• Password [T1589.001],
• Global Address List (GAL) [T1087],
• Two-factor authentication (2FA) tokens, and
• Newly-created Application Passcode [T1098].

The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing. Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.

Targeting details

LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:

• the Defense Industrial Base (DIB),  
• the federal and local government,
• education,
• energy,
• law enforcement,  
• media,  
• non-governmental organizations, and
• technology.

Technical details

Note: This advisory uses the MITRE ATT&CK® Matrix for Enterprise framework, version 19. This advisory also uses MITRE D3FEND^TM version 1.4.0¹⁵. See Appendix A and Appendix B for tables of the activity mapped to MITRE ATT&CK and D3FEND tactics, techniques, and countermeasures.

Ulej is a novel data exfiltration and aggregation capability, that currently (as of the publication of this report) supports a campaign specifically targeting users of ZCS webmail servers. This capability is used to exploit CVE-2025-66376 [Common Weakness Enumeration (CWE) CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')], but likely could be adapted to exploit other vulnerabilities. It exfiltrates emails and other sensitive user data from a victim’s system immediately after exploitation and stores the data in an actor-controlled unattributable virtual private server (VPS) [T1074.002] running LAUNDRY BEAR’s “Flowerbed” collection framework. The collected data is almost certainly further exfiltrated to internal network resources for review and long-term retention.

Reconnaissance

LAUNDRY BEAR uses the Ulej capability to exploit the CVE-2025-66376 vulnerability in organizations using ZCS. This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations. LAUNDRY BEAR likely identifies organizations with public-facing Zimbra infrastructure by port scanning [T1595] and fingerprinting datasets easily procured through various commercial vendors [T1596.005].  

After identifying a target organization, the group likely compiles email addresses for individual users to target with the exploit [T1589.002] from datasets offered by commercial vendors [T1597.002], open source intelligence [T1593], or previously exfiltrated data [T1597].  

Resource development

The actors procure VPSs from a variety of providers [T1583.003], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [T1583] when interacting with these servers, further demonstrating the group’s intent to mask their identity and maintain operations security (OPSEC). After the server is provisioned, an automated process deploys the Docker containers necessary for Ulej’s Flowerbed framework [T1608], which then receives and aggregates the data Ulej exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.

Flowerbed framework

Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:

• Catcher,
• Certbot,
• Nginx, and
• Gardener.

Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [T1048]. For additional information on Catcher, refer to the Exfiltration section of this advisory. Flowerbed’s next container, Certbot, is based on one of the official Certbot containers, which allows for automated generation of Let’s Encrypt certificates using DNS challenges through Cloudflare. This certificate can then be used by the Nginx container, which serves as an HTTPS reverse proxy for Catcher, enabling Flowerbed to disguise some of its exfiltration activity through an encrypted communications channel [T1048.002]. The Nginx reverse proxy also validates that the Server Name Indicator (SNI) value contains “*.i.*” prior to forwarding the traffic to Catcher. If the SNI does not contain that string, the Nginx server returns a 444 error to the client. This is likely an attempt to reject non-Ulej connections. Finally, the Gardener container functions as a health check for the Catcher service. Gardener is a simple Python script that validates Catcher correctly receives and processes data.

The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development. This highlights how AI is increasingly being used to develop malicious capabilities [T1588.007]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [T1588.002], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.

Initial access

To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [T1566]. Through exploitation of CVE-2025-66376, this JavaScript payload is immediately executed once the user views the malicious email [T1203], such as the one shown in Figure 1, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [T1199], as shown in the email metadata in Figure 2. These compromised accounts were likely previous victims of this, or another LAUNDRY BEAR, campaign and their use is intended to further obfuscate and frustrate anti-phishing tools and training.

According to the National Vulnerability Database (NVD), CVE-2025-66376 was initially published on 5 January 2026. This vulnerability allows for execution of a JavaScript payload included in email content due to improper sanitization of Cascading Style Sheet’s (CSS) @import directives within an email [5]. Because the activity attributed to this campaign began in July 2025—months before Synacor released a patch and the CVE was published—the payload initially exploited a zero-day vulnerability at that time [T1587.004].  

Utilization of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability.

Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [T1027.017], as shown in Figure 3. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage CVE-2025-66376. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see Figure 3) [T1027.013]. The outer payload decodes and decrypts the inner payload using an XOR function and a hardcoded key and then executes the script contained within the inner payload containing the collection and exfiltration logic. By changing the key used for the XOR encryption of the inner payload or adding additional @import directives with non-functional code [T1027.010], LAUNDRY BEAR can easily generate new payloads that bypass basic threat detection signatures. This malicious payload attempts to collect and exfiltrate information in 12 asynchronous stages [T1119]. The stages in order of appearance within the payload are as follows:

1. sendStartPing,
2. gather_email,
3. gather_environment,
4. gather_2fa_codes,
5. gather_app_password,
6. gather_device_status,
7. gather_oauth_consumers,
8. gather_autocomplete_password,
9. enable_mail_protocols,
10. gather_gal,
11. sendArchives, and
12. sendFinishPing. 

Use of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability [T1587].

Persistence and credential access

To establish sustained persistence into the victim’s email account, the script attempts to modify account preferences and collect authentication information. Any collected credentials are later exfiltrated, as further described in the Exfiltration section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [T1550.004], and the Zimbra campaign follows a similar trend.

The script used in this campaign tries to discover the victim’s email address during the gather_email stage [T1087]. The script searches for this email address in two ways. First, it examines the batchInfoResponse variable, which an HTML script element on the webpage can define, for an email address. Even if the script finds an email address there, it also checks whether it acquired a Cross-Site Request Forgery (CSRF) token as described later in the Collection section of this advisory. If so, the script uses the “GetIdentitiesRequest” Simple Object Access Protocol (SOAP) command under the “ZimbraAccount” namespace to determine the victim’s email address [T1185] and then exfiltrates it. However, if the script does not have a CSRF token or the SOAP request fails, the script exfiltrates the email value recovered from the first method instead. If both attempts fail to capture the victim’s email, the script sends a JavaScript Object Notation (JSON) payload with a key of “email” and value of null over HTTPS and does not attempt DNS exfiltration.

During the gather_autocomplete_password stage, the script attempts to collect the victim’s saved password via the autocomplete feature of the victim’s password manager. The script injects two HTML div elements requesting login credentials onto the page outside of the victim’s view, as shown in Figure 4 and Figure 5. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in Figure 4. If there is no value in that input field, it checks the password input field shown in Figure 5. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of null is sent over HTTPS and DNS exfiltration is not attempted.

LAUNDRY BEAR almost certainly relies on a mail client using the Internet Message Access Protocol (IMAP) for persistent access to the victim’s mailbox. During the enable_mail_protocols stage, a SOAP request leveraging the “ModifyPrefsRequest” command under the “ZimbraAccount” namespace is sent. This request attempts to set the “zimbraPrefImapEnabled” preference to TRUE. While the default setting for “zimbraPrefImapEnabled” is not well documented, this action is almost certainly intended to ensure that IMAP access to the victim’s mailbox is enabled.

ZCS does not support 2FA for some mail clients, including IMAP. To support users who rely on IMAP clients, ZCS allows for the generation of Application Passcodes. Application Passcodes are randomly generated passwords that can be used for clients that cannot support the normal 2FA process to authenticate. During the gather_app_password stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [T1556.006]. The SOAP request uses “ZimbraWeb” as the name of the application.

Additionally, the script also attempts to collect 2FA tokens. During the gather_2fa_codes stage, the script makes a SOAP request using the “GetScratchCodesRequest” command under the “ZimbraAccount” namespace. The script then attempts to exfiltrate any non-null 2FA codes collected this way. The number of codes can vary, and each code is exfiltrated to Flowerbed individually.

Collection

As demonstrated in the Persistence and credential access section, this script relies heavily on SOAP requests to collect victim information. To make these requests, the script aims to acquire the victim’s current CSRF token, which it attempts to access within the webpage’s local storage using localStorage.getItem("csrfToken"). If the script is unable to acquire this CSRF token, it will be unable to make any SOAP requests. In addition to the SOAP commands documented in the Persistence and credential access section, other SOAP commands executed to collect victim information are shown in Table 1.

The script attempts to collect the victim’s GAL through brute force by searching for each two-character combination from a character set of “abcdefghijklmnopqrstuvwxyz1234567890.-_”. These queries are conducted using 20 batches of SOAP requests with 77 “SearchGalRequest” SOAP commands in each batch except for the last request containing only 58.

During the gather_environment stage, the script attempts to determine which type of ZCS webmail client the victim is using. The script checks the user’s current URL to determine the client type being used, checking for certain indicators (shown in Table 2) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.

As part of collection, the script attempts to harvest any emails not marked as “junk” from the last 90 days from the victim’s account. Emails are collected daily by an HTTP GET request to the URL path, “/home/~/?fmt=tgz&meta=0&query=date:-{DAY_OFFSET}d AND (not in:junk)”. The {DAY_OFFSET} value would be between 0 and 89 representing how many days ago the email was sent or received. To prevent redundant collection and exfiltration of emails, a variable with a name based on the email date being queried, using a format of zd_comp_YYYY-MM-DD, and value of true, is saved to the window.top.localStorage property. This variable is saved regardless of whether the email is successfully exfiltrated.  

According to Mozilla documentation, if the user is not in a private browsing session, any data stored to localStorage does not typically expire. This means that if the user happens to execute the script again from the same computer, the script avoids attempting to re-exfiltrate previously captured emails. However, the script always attempts to pull any emails with a {DAY_OFFSET} of zero. In other words, the script always pulls emails sent or received the same day it is run. After email results are returned from the query for each day of email activity, those results are then passed to Flowerbed as described in the Exfiltration section.

The script also provides LAUNDRY BEAR with telemetry on any errors that occur during the collection process. This is accomplished by executing any collection or exfiltration code through helper functions that contain error handling logic. If an error occurs, a payload containing information on the error itself, the context of the error happening, and the stage in which the error occurred is sent to Flowerbed as described in the Exfiltration section below. For cases where the error occurs within a SOAP request, “:api” is concatenated to the stage value in the payload. If an error occurs during the batch SOAP requests that occur when collecting the GAL of the victim, the stage value will use a format of gather_gal:{VAL}:api. The {VAL} placeholder indicates which batch request, a number from 0 to 19, the error occurred in. Errors that occur during the password autocomplete interception process will use “gather_autocomplete_password:dom” for the stage value. Finally, if an error occurs when attempting to collect or exfiltrate a specific day’s emails, the stage will include which day the error occurred on, using the previously defined placeholder {DAY_OFFSET}, with a format of sendArchive:day-{DAY_OFFSET}.

Exfiltration

At the end of each stage in the collection process, the script attempts to exfiltrate acquired information to Flowerbed. The script primarily relies on two forms of data exfiltration: DNS [T1048.003] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.

Prior to exfiltration, a randomized 10- or 11-character alphanumeric string is generated as an identifier for the victim. This identifier is included in the URL of both the DNS- and HTTPS-based exfiltration.  

DNS exfiltration

DNS exfiltration occurs through DNS A record queries. To ensure data exfiltrated through DNS is not corrupted when traversing through non-actor-controlled DNS infrastructure, Ulej maintains compliance with RFC 1035, Domain Names - Implementation and Specification, specifically accounting for the case insensitivity and subdomain length requirements. Base32 encoding is used to create a case-insensitive payload. Once the payload is encoded, a period (“.”) is added every 60 characters to ensure each subdomain is under 63 characters long. The script then creates a new image object sourced from a URL with the scheme defined in Figure 6. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.

When the script generates an image object, the browser tries to retrieve the complete domain of the URL specified as the source of the image. This triggers a DNS request sent to the actor-controlled server and processed by Flowerbed. Table 3 lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.  

HTTPS exfiltration

Any information exfiltrated via DNS is also exfiltrated through HTTPS, as well as additional data including email content, contacts, attachments, and error logging information. By using Let’s Encrypt certificates, this group can quickly deploy new infrastructure and leverage encrypted HTTPS communications with valid server certificates when exfiltrating information from the victim’s environment. The HTTPS exfiltration capability only uses two HTTP content types, defined in Table 4. Traffic associated with HTTPS exfiltration will use the URL scheme shown in Figure 7.  

Some of the data transmitted via HTTPS uses the standard JSON content type format. The script includes the information in a POST request to actor-controlled infrastructure.  

Table 5 provides a summary of the JSON-based exfiltration.

The script transmits all HTTPS exfiltration not identified in Table 5 using the Octet-Stream content type as binary data. The POST requests for this method include a filename in the “X-Filename” header. Traditionally, developers use headers prefixed with “X-” to denote custom headers that do not follow a defined standard. The purpose of including this header remains unclear since the Catcher capability ignores the provided filename when saving the data. Table 6 summarizes the data exfiltrated in this format.

The script sends all exfiltrated data identified in Table 6 to the Catcher service exactly as received from the SOAP request in a JSON payload, except for email exfiltration. For email exfiltration, the script sends it as a GZIP compressed archive [T1560]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in Table 6 using the application/octet-stream content typing rather than application/json.

At the beginning and end of the collection and exfiltration activity, during the sendStartPing and sendFinishPing stages respectively, the script submits a POST request with a JSON payload to indicate that the script is starting or finishing execution. Throughout execution, the script also logs error events and send the logs using similar JSON payloads. The script sends the JSON in a POST request to the URL documented in Figure 2, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (start, finish, or error).  

Catcher

Ulej exfiltrates information to Flowerbed to be handled by a service named Catcher. Catcher is a containerized Python application, running in Docker as part of Flowerbed, which is detailed in the Resource development section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.

Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the Resource development section, the Flowerbed project uses an additional Docker container running an Nginx reverse proxy to enable HTTPS support. This reverse proxy uses a certificate generated by Let’s Encrypt and forwards all traffic with an SNI containing “*.i.*” to port 8000 within the Catcher container.

The DNS service can accept A, AAAA, MX, TXT, and CAA queries. For any MX, AAAA, or CAA queries, the server will always provide an empty response. The system only supports TXT records as needed to process Automatic Certificate Management Environment (ACME) requests, which enable the assignment of Let’s Encrypt certificates. If the server receives an A query, Catcher will always respond with the public IP address of the Flowerbed server.  

However, if a query includes a domain formatted as shown in Figure 6 and Figure 7, the service saves a log file in JSON format to disk containing the following details of the DNS query:

• Time of query,
• Source IP address for query,
• Queried domain, and
• Type of query.

The HTTP server typically responds with OK, except in cases where the path is “pixel.gif” when the response contains a 1x1 gif image with a SHA-256 hash of ef1955ae757c8b966c83248350331bd3a30f658ced11f387f8ebf05ab3368629. Like the DNS service, the HTTP service will only log entries when the domain found in the host header of the request follows the expected formatting as seen in Figure 6 and Figure 7. As the HTTPS exfiltration uses non-standardized binary and JSON-formatted payloads when exfiltrating to Catcher, Catcher will check the content type of the request. If the content type is set to “application/json”, Catcher encodes the data in Base64 and includes it in the JSON log entry written to disk. If the content type is set to any other value, Catcher leaves the Base64 payload in the JSON log entry blank and saves the payload to a separate file with the same filename as the JSON log entry with a “.bin” file extension. An HTTPS exfiltration event causes Catcher to save a JSON formatted log file to disk containing the following information from the HTTP request:

• Time,
• Source IP address,
• Request method,
• Host,
• Path,
• Query string,
• Headers, and
• Base64 payload.

These JSON event log files and binary output files are then initially saved to the directory /root/hits/tmp and later moved to the /root/hits/ready directory once processed. This prevents incomplete files, which are still being uploaded to Catcher, from premature exfiltration from the server. Approximately every 60 seconds, a likely automated workflow establishes a Secure Shell (SSH) connection with the server hosting Flowerbed for a few seconds, almost certainly exfiltrating the data processed by Catcher to non-public-facing infrastructure. The command in Figure 8 also executes hourly to remove all files last modified at least two days ago from the /root/hits/ready directory.

Response strategies

Mitigations

In many cases, by the time an organization identifies a compromise related to this campaign, numerous sensitive and proprietary emails have already been exfiltrated. The significant risk posed by this cyber threat emphasizes the importance for organizations that use ZCS and other similar webmail solutions to take proactive steps to mitigate this risk.

All organizations that use the ZCS webmail service should immediately prioritize ensuring that their ZCS is not running a vulnerable version. A patch for CVE-2025-66376 was released for both 10.1.13 and 10.0.18 versions of ZCS [D3-AH]. If immediate patching is not feasible, organizations should advise employees to use alternative mail clients to access email and avoid using the Classic ZCS webmail client until ZCS is updated to a non-vulnerable version [d3f:Isolate].

System administrators should closely monitor any Internet-connected ZCS or other email systems and the workstations that access those systems and promptly apply available software updates [D3-AH]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including CISA’s Known Exploited Vulnerabilities Catalog and NCSC-UK’s Responding to active exploitation of vulnerabilities guidance.

Organizations should consider using a third-party authentication service that supports passkeys for authentication to mediate access to ZCS and other services that do not natively support passkeys. By doing so, organizations can work to eliminate the possibility of automated password collection from autocomplete or password reuse [D3-CH]. However, Application Passcodes may still be necessary and should be monitored closely.  

Organizations should implement network monitoring capabilities with collection and short-term retention of packet capture or NetFlow data and maintain log collection and storage [CPG 3.Q]. This will allow organizations to monitor for and identify suspicious network activity [CPG 4.B], such as:

• Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [D3-NTA];
• Frequent DNS queries for a suspicious domain with seemingly random subdomains [D3-DNSTA];
• A sudden spike of connections to a server associated with a recently established domain [D3-NTCD]; and  
• Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [D3-NTCD].

Additionally, for organizations that can inspect the content of outbound HTTPS connections via break-and-inspect infrastructure, security teams should identify traffic matching the characteristics described in the Exfiltration section of this advisory.

Indicators of compromise (IOCs)

Flowerbed infrastructure

The following indicators have been attributed to use by LAUNDRY BEAR for their campaign targeting ZCS’s webmail service as of the publication of this advisory. (Disclaimer: Due to the frequency of operational structure changes by this group, these indicators are intended solely for historic attribution purposes. Some indicators, such as IPs, compromised emails, and domains, may be outdated, so organizations should check for current activity before acting on these IOCs.) Table 7 provides details about the server infrastructure used to host Flowerbed, and Table 8 lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [D3-IAA].

LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:

• ivanka.zurabishvili@proton[.]me,
• zmul1@buildandconsulting[.]com,
• garrysmithme@pinmx[.]net, and
• hostingclient@pinmx[.]net.

Phishing distribution

LAUNDRY BEAR primarily relied on ProtonMail for distribution of malicious email. However, as stated above, LAUNDRY BEAR’s more recent efforts likely have shifted to distributing the payload through previous victims.  

The following email addresses have distributed payloads attributed to this campaign:

• c.laurent.ejfa@proton[.]me,
• j.moreau.epsc@proton[.]me,
• liberty.insights@proton[.]me,
• certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and
• certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).

Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:

• 98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,
• 60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,
• b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and
• 1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.

Post-compromise artifacts

Currently, the script does not remove artifacts. This leaves additional opportunities to identify victims of this activity. While emphasis should always be placed on consistent monitoring of network traffic and endpoint activity, there are a variety of persistent artifacts described below that can be used to identify victims of this campaign.

This Ulej capability relies on creating a significant number of SOAP requests to collect account information for exfiltration. ZCS logs from these requests are stored, by default, in the /opt/zimbra/log/mailbox.log file [D3-PA]. A significant amount of SOAP request activity that aligns with what was described in the Persistence and credential access and Collection sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:

• Many SearchGalRequest command requests from a single user over a short period of time;
• Use of the CreateAppSpecificPasswordRequest command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and
• Use of the GetScratchCodesRequest command.

While LAUNDRY BEAR uses the localStorage property to track what days had emails previously exfiltrated, defenders can use this property to identify victims of this campaign and determine the scope of exfiltrated information [D3-PA]. Review of the items stored in that property for an organization’s ZCS webmail client page on an endpoint device could indicate compromise if there are items named with a format of zd_comp_YYYY-MM-DD, as explained in the Collection section of this advisory.

While Application Passcodes have non-malicious purposes, in this case instances of these passcodes with the name “ZimbraWeb” are almost certainly malicious. The ZCS webmail application can support 2FA natively and does not require the use of an Application Passcode, so there is no reason that there should be one named “ZimbraWeb.”

In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [D3-MA]. If an email that has a payload exploiting CVE-2025-66376 is discovered, steps should be taken immediately to identify and quarantine other instances of emails with similar body content, senders, and subject lines to prevent further exploitation and exfiltration.  

Remediation

In the event an organization identifies activity associated with this campaign, that organization should take steps to minimize further exploitation. The organization should consider requesting that employees minimize use of the ZCS webmail client until the organization updates to a patched version that is not vulnerable to CVE-2025-66376.

Organizations should use identifiers from the IOCs section of this report to identify any individuals compromised by this campaign and record the date(s) of compromise(s) to determine the scale and scope of emails exfiltrated.

All users from the organization should have all Application Passcodes and 2FA scratch keys revoked. Affected organizations should require all employees to change passwords in line with establishing minimum password strength requirements [CPG 3.B] and creating unique credentials [CPG 3.C], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.

Works cited

[1] Netherlands General Intelligence and Security Service (AIVD) and Netherlands Defence Intelligence and Security Service (MIVD). AIVD and MIVD identify a new Russian cyber threat actor. 2025. https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf

[2] Microsoft Corporation. New Russia-affiliated actor Void Blizzard targets critical sectors for espionage. 2025. https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/

[3] Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. https://unit42.paloaltonetworks.com/russian-webmail-espionage/ 

[4] Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit

[5] Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/  

Footnotes

¹ Národní úřad pro kybernetickou a informační bezpečnost
² Forsvarets Efterretningstjeneste
³ Välisluureamet
⁴ Sotilastiedustelu
⁵  Suojelupoliisi
⁶ Direction générale de la sécurité intérieure
⁷ Agence nationale de la sécurité des systèmes d’information
⁸ Agenzia Informazioni e Sicurezza Esterna
⁹ Agenzia Informazioni e Sicurezza Interna
¹⁰ Serviciul de Informații și Securitate al Republicii Moldova
¹¹ Agencja Wywiadu
¹² Służba Kontrwywiadu Wojskowego
¹³ Centro Nacional de Inteligencia
¹⁴ Nationellt Cybersäkerhetscenter
¹⁵ MITRE and ATT&CK are registered trademarks of The MITRE Corporation. MITRE D3FEND is a trademark of The MITRE Corporation.

Acknowledgements

The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.

Disclaimer of endorsement

The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.

Organizations have no obligation to respond or provide information back to the authoring organizations in response to this joint advisory. If, after reviewing the information provided, an organization decides to provide information to the authoring organizations, reporting must be consistent with all applicable laws and policies.

Purpose

This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.

Contact

Appendix A: MITRE ATT&CK tactics and techniques

See Table 9 through Table 19 for all the threat actor tactics and techniques referenced in this advisory.

Appendix B: MITRE D3FEND countermeasures

See Table 20 for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.

A few years ago we deployed Matrix with docker-compose. Now, let's give it a go on Kubernetes!

00:00 Introduction
01:40 Kubernetes Makes Things Simple
04:59 Getting Started
06:21 Installing Kubernetes
14:41 Deploying and Removing a Wordpress
20:53 Deploying A Matrix Stack
31:02 More Services Almost For Free

This Week in Matrix: https://matrix.org/twim

Find Matrix.org on the internet:
🐘 https://mastodon.matrix.org/@matrix
🤝 https://www.linkedin.com/company/matrix-org
🦋 https://bsky.app/profile/matrix.org
[m] Office of the Matrix Foundation https://matrix.to/#/%23foundation-office:matrix.org

Ein Netflix-Abo hat mittlerweile so gut wie jeder, doch der eine oder andere wartet vielleicht noch auf eine Möglichkeit, das Streaming-Angebot kostenlos zu testen. Das war seit den Anfängen von Netflix nicht mehr möglich, doch jetzt gibt es wieder einen kostenlosen Probezeitraum.

Bis zu 30 Tage können Sie den Streamingtest jetzt kostenlos nutzen. Teilweise werden auch nur 14 Tage angeboten, der Gratis-Zeitraum scheint also je nach Standort oder genutztem Browser zu variieren. Auf der Webseite von Netflix Deutschland wurden uns auch nur 14 Tage für 0 Euro angezeigt. Es kann aber helfen, wenn Sie auf ein anderes Gerät wechseln oder Cookies löschen.

Wichtig: Das Angebot gilt explizit nur für Neukunden, nicht für wiederkehrende Abonnenten. Allerdings ist es recht einfach, diesen Umstand zu umgehen, wenn Sie sich einfach mit einer anderen E-Mail-Adresse als zuvor registrieren. Dann haben Sie zwar keinen Zugriff auf Ihren alten Account inklusive persönlicher Daten, Listen und Streaming-Historie, doch das ist sicher zu verschmerzen.

Nach Ablauf des Probezeitraums müssen Sie sich für ein Abo entscheiden (oder vorher kündigen). Zur Wahl stehen Standard mit Werbung für 4,99 Euro monatlich, Standard ohne Werbung für 13,99 Euro monatlich oder Premium für 19,99 Euro monatlich.

Warum genau Netflix gerade jetzt ein Probe-Abo wieder einführt, ist nicht ganz klar. Vermutlich versucht der Anbieter aber, neue Abonnenten dazu zu gewinnen, nachdem die Zahlen zuletzt stagnierten. Zwar ist Netflix der größte Anbieter für Streaming, doch die Konkurrenz schläft nicht. Seit Januar 2026 gibt es beispielsweise auch HBO Max in Deutschland, das mit großen Namen wie Game of Thrones, House of the Dragon, Harry Potter oder Superman wirbt.

Eine Übersicht aller wichtigen Streaming-Dienste finden Sie hier, inklusive Preisen, Vorteilen und Nachteilen.

Zwei große Änderungen hat es in den vergangenen Jahren bei Phishing-Angriffen gegeben: Die Kriminellen erstellen mithilfe von generativer KI sprachlich fast perfekte Mails, die in Stil, Struktur und Tonalität kaum noch von legitimen Nachrichten zu unterscheiden sind. Wo früher holpriges Deutsch sofort Misstrauen geweckt hat, liest sich heute eine Phishing-Mail wie eine echte Mitteilung von Microsoft, einer Bank oder einem Paketdienst.

Auch das Design wirkt meist höchst professionell. Zum anderen sind auch die technischen Tricks beim Datendiebstahl heute höher entwickelt. Einige Maschen umgehen sogar eine Zwei-Faktor-Authentifizierung. Das Ziel der Angreifer bleiben vor allem Zugangsdaten, Session-Tokens und persönliche Infos.

1. Microsoft-365-Log-in-Falle trickst Zwei-Faktor-Anmeldung aus

Eine neue Angriffsmethode verwendet den originalen Microsoft-Anmeldedialog und kommt entsprechend fast ohne gefälschte Webseiten aus. Die Kriminellen nutzen dafür den Oauth-Device-Code-Flow. Das ist ein Anmeldeverfahren für Geräte oder Programme, die keinen brauchbaren Browser oder keine komfortable Texteingabe bieten, etwa Smart-TVs, IoT-Geräte, Drucker oder CLI-Tools.

Offiziell heißt er „OAuth 2.0 Device Authorization Grant“. Mit der Methode lassen sich auch Konten übernehmen, die mit einer Zwei-Faktor-Authentifizierung geschützt sind.

Die Kriminellen schicken an ihre Opfer eine Phishing-Nachricht und geben vor, das Gerät der Opfer müsste für den Log-in ins Microsoft-365-Konto neu autorisiert werden. Die Nachrichten beginnen meist harmlos, etwa mit „Ihre Sitzung ist abgelaufen“, und bieten einen Link zur Neuanmeldung. Wenn das Opfer dem Link in der Nachricht folgt, landet es zunächst auf einer gefälschten Website, schließlich aber beim offiziellen Microsoft-Authentifizierungsverfahren für Geräte und Anwendungen (Oauth-Device-Code-Flow).

Proofpoint

Es handelt sich um echte Microsoft-Meldungen und Webseiten. Allerdings autorisiert das Opfer nicht den Zugang zu seinem eigenen PC oder Smartphone, sondern eine Anwendung der Kriminellen. Diese bekommen nach der Freigabe durch das getäuschte Opfer einen Access-Token. Damit kann die feindliche Anwendung per API auf das Microsoft-Konto zugreifen, ohne dass noch einmal ein Passwort eingegeben werden muss.

Übrigens: Die meisten dieser Angriffe verstecken den Link zur gefälschten Website in einem QR-Code. Dieser entgeht den Spam-Filtern eher als ein üblicher Link, und es lässt die meisten Opfer vom PC auf das Smartphone wechseln.

Auf diesem ist es wegen des kleineren Bildschirms und oft fehlender Sicherheits-Software noch wahrscheinlicher, dass das Opfer die Täuschung nicht bemerkt. Eine ausführliche Analyse der Angriffe auf Microsoft-365-Konten haben die Sicherheitsexperten von Proofpoint veröffentlicht.

2. Support-Masche: Ihr Computer ist gesperrt & Co.

Die Support-Masche ist zwar nicht neu, funktioniert aber nach wie vor: Noch immer fallen zahlreiche Menschen auf die perfide Betrugsstrategie herein. Zu den prominenten Opfern zählt Bundestagspräsidentin Julia Klöckner.

Mutmaßlich staatlich organisierte Angreifer kontaktierten sie über den Messenger-Dienst Signal und gaben sich als vermeintliche Signal-Support-Mitarbeiter aus. Unter einem Vorwand forderten sie Klöckner und weitere Politiker auf, ihre PIN einzugeben. Dadurch erlangten die Angreifer Zugriff auf die Signal-Konten der Betroffenen – und damit auf private Chats und Kontakte.

Das Bundesamt für Verfassungsschutz und das Bundesamt für Sicherheit in der Informationstechnik (BSI) haben gemeinsam einen Leitfaden veröffentlicht, der potenziellen Opfern hilft zu prüfen, ob ihr Signal-Konto übernommen wurde.

Bundesnetzagentur

Ebenfalls weiterhin verbreitet sind Angriffe durch angebliche Microsoft-Support-Mitarbeiter. Die Betrüger kontaktieren ihre Opfer per Telefon, E-Mail oder über gefälschte Pop-up-Warnungen im Browser.

Dabei behaupten sie, der Windows-PC habe ein Sicherheitsproblem – etwa sei der Computer gesperrt oder mit Schadsoftware infiziert. Anschließend versuchen sie, die Betroffenen zur Installation einer Fernwartungssoftware oder eines vermeintlichen Sicherheitstools zu bewegen. Tatsächlich erhalten die Angreifer dadurch oft vollständigen Zugriff auf den Rechner.

3. Gefälschter Microsoft Defender warnt

Der Microsoft Defender ist ein Windows-Bordmittel und schützt PCs gegen alle bekannten PC-Viren. Entsprechend alarmierend ist für viele Nutzer eine Warnung dieses Antiviren-Tools. Eine gefälschte Form dieser Warnung erscheint mal per E-Mail, mal als Pop-up im Browser. In diesen Nachrichten wird behauptet, der Schutz des Defenders müsse kostenpflichtig erneuert werden. In der Folge werden die Nutzer auf gefälschte Shop-Webseiten geleitet, die eine Zahlung für einen Virenschutz verlangen.

Grundsätzlich gilt: Der Microsoft Defender ist auf Privat-PCs ein Bordmittel und kostenlos in Windows enthalten. Eine Zahlung ist nicht nötig. Sollte die Warnung per Mail bei Ihnen landen, löschen Sie diese einfach. Schlägt sie als Pop-up im Browser auf, schließen Sie einfach das Browser-Fenster, notfalls mit der Tastenkombination „Alt+F4”.

Der Antivirenspezialist Norton hat eine Anleitung veröffentlicht, die erklärt, wie sich solche Pop-up-Warnungen im Browser beseitigen lassen, falls sie sich im System festgesetzt haben.

4. Microsoft-Onedrive: Cloud-Phishing über Freigaben

Cloud-Dienste wie Onedrive von Microsoft nutzen viele Windows-Nutzer mehrmals täglich. Genau deshalb sind sie ein attraktives Ziel für Phishing. Statt klassischer E-Mails mit Dateianhängen erhalten die Nutzer Freigabe-Benachrichtigungen mit einem Betreff wie „Dokument wurde mit Ihnen geteilt“. Der Inhalt wirkt meist harmlos und oft beruflich relevant: Rechnungen, Projektpläne, Gehaltslisten oder interne Dokumente.

Besonders tückisch ist die Kombination aus echten und gefälschten Elementen. Manche Angriffe nutzen tatsächlich legitime Cloud-Plattformen, bieten dort aber manipulierte Dokumente an. Das Ziel dieser Angriffe sind mehrheitlich die Log-in-Daten der Opfer zu Ihren Cloud- und Mail-Konten. Diese werden dann von den Angreifern übernommen und etwa für neue Phishing-Attacken genutzt.

5. Lieferdienste, Lieferdienste und noch mal Lieferdienste

Phishing im Namen von Paketdiensten gehört zu den stabilsten Angriffsmustern überhaupt und wird gleichzeitig immer ausgefeilter. Der Grund ist die hohe Alltagstauglichkeit: Fast jeder erwartet regelmäßig Lieferungen und ist deshalb kaum misstrauisch, wenn eine Mail, SMS oder Whatsapp zum Thema Paketversand eintrudelt. Moderne Varianten enthalten nicht nur einfache Textlinks, sondern vollständige Tracking-Systeme.

Arne Arnold

Diese Seiten sind dynamisch aufgebaut und simulieren echte Logistikprozesse. Beim Sendungsverlauf heißt es dann etwa: „Zustellung fehlgeschlagen – bitte Adresse bestätigen“ oder „Letzte Möglichkeit zur Terminänderung“. Besonders kritisch ist die Kombination aus Zeitdruck und Kontext. Wer Opfer eines solchen Angriffs wird, gibt meist seine Log-in-Daten für Shopping- oder Zahlungsdienste preis. Oder er überweist den Angreifern direkt Geld, da angeblich Steuern, Bearbeitungsgebühren oder ein Expresszuschlag fällig sind.

Arne Arnold

Übrigens: Ab dem 1. Juli 2026 gibt es zusätzliche Abgaben auf Sendungen aus Nicht-EU-Ländern. Für Waren unter 150 Euro sind dann pauschal 3 Euro Zollgebühr und eine Einfuhrumsatzsteuer fällig. Einige Kurierdienste verlangen zusätzlich eine Servicepauschale für diese Zollanmeldung. Über die genauen Kosten informiert eine Seite der Verbraucherzentrale NRW. Es lohnt sich, die tatsächlichen Kosten zu kennen, denn es ist wahrscheinlich, dass zu diesem Termin vermehrt Phishing-Mails zu diesem Thema versendet werden.

6. Phishing zu Online-Banking gibt es immer

Phishing zum Online-Banking gibt es fast schon so lange wie das Online-Banking selbst. Die Bedrohungslage ist aber so angespannt wie nie, denn die Angriffe sind nun wirklich zahlreich. Über die neuesten Phishing-Fallen informieren unter anderem die Verbraucherzentralen.

Beispiele aus dem Mai 2026 lauten etwa so: „Bestätigung Ihrer Mobilfunknummer erforderlich“. Absender ist vorgeblich die Easybank. Eine Fälschung von Commerzbank-Mails warnt vor einem fälligen „Photo-TAN Update“, bei dem ein „einmaliger Abgleich der Zugangsdaten“ nötig ist.

Andere Phishing-Mails geben vor, von der Deutschen Bank zu sein, und fordern eine Reaktivierung des „photoTAN-Sicherheitszertifikats“. Auch Kunden der DKB erhielten im Mai Phishing-Mails.

Verbraucherzentrale

Sollten Sie eine Mail von Ihrer Bank bekommen, klicken Sie auf keinen Fall auf einen der Links in dieser Mail. Wenn Sie sich unsicher sind, ob Sie reagieren sollen, rufen Sie die Website Ihrer Bank über Ihren Browser auf.

Sollte es tatsächlich ein Anliegen der Bank geben, wird es Ihnen nach dem Einloggen in Ihr Online-Konto angezeigt. Oder Sie rufen Ihre Bank einfach per Telefon an und fragen, ob Informationen von Ihnen benötigt werden.

7. Phishing per Post: Kreditbetrug per Postident-Verfahren

Diese Phishing-Angriffe erreichen Sie per Post in Ihrem echten Briefkasten. Die Briefe geben vor, von Ihrer Bank zu stammen, und fordern Sie auf, Ihre Daten erneut per Postident zu bestätigen. Postident ist ein Verfahren der Post, mit dem Sie Ihre Identität gegenüber anderen, etwa einer neuen Bank oder einem Kreditinstitut, bestätigen können. Wer das beigefügte Schreiben nutzt, legitimiert in der Regel einen hohen Kredit bei einer anderen Bank.

Schäden von 15.000 bis 25.000 Euro sind hier keine Seltenheit. Vorangegangen ist meist ein Diebstahl Ihrer genauen Daten (Postadresse, Hausbank, Arbeitgeber, Verdienst), den die Angreifer dann nutzen. An die Daten kommen die Kriminellen etwa über gefälschte Wohnungsinserate bei Immoscout24 oder ähnlichen Portalen. Wer sich auf eine Wohnung oder ein Haus mit Gehaltszetteln und weiteren Angaben bewirbt, hat bereits alle wichtigen Daten für den Postident-Betrug verraten. Seien Sie beim Postident-Verfahren stets besonders vorsichtig. Konkrete Tipps lesen Sie hier.

Sicherheitstipps: Phishing erkennen und blockieren

An diesen Merkmalen erkennen Sie betrügerische Nachrichten:

• Unverlangter Kontakt: Sie erhalten eine E-Mail, Whatsapp oder SMS über eine Gutschrift, eine Lastschrift oder andere finanzielle Ansprüche, obwohl Sie aktuell keine Buchung storniert oder reklamiert haben.
• Zeitdruck: Die Nachricht suggeriert dringenden Handlungsbedarf und fordert zur schnellen Reaktion auf.
• Verdächtige Links: Die Links in der Nachricht sind hinter einem QR-Code maskiert, führen zu unpassenden Domains oder sind ungewöhnlich lang.
• Aufforderung zur Dateneingabe: Seriöse Unternehmen fordern in Nachrichten oder Mails nur äußerst selten zur Eingabe sensibler Daten auf.
• Unpersönliche Anrede: Oft fehlt die namentliche Ansprache oder es werden generische Formulierungen verwendet.

Diese Maßnahmen schützen vor Phishing-Fallen:

• E-Mail, SMS und Whatsapp & Co. sind keine geschlossenen Nachrichtenkanäle: Sie müssen damit rechnen, auch betrügerische Nachrichten zu erhalten.
• Misstrauen Sie Links in Nachrichten: Klicken Sie keine Links an und scannen Sie keine QR-Codes, wenn Log-in-, Zahlungs- oder Sicherheitsaufforderungen in der Mail stehen. Öffnen Sie den jeweiligen Dienst im Browser über die manuelle Eingabe der Adresse.
• Nutzen Sie Browser und Passwortmanager als Frühwarnsystem: Wenn Ihr Passwortmanager Ihre Log-in-Daten auf einer Webseite nicht einfügen möchte, dann ist die Domain vermutlich gefälscht. Achten Sie zudem auf die Warnungen Ihres Browsers.
• MFA aktivieren: Nutzen Sie immer eine Zwei- oder Multifaktor-Authentifizierung, wenn diese angeboten wird. Vor allem Passkeys erhöhen die Sicherheit.
• Remote-Support misstrauen: Installieren Sie keine Fernwartungs-Tools, nachdem Sie unaufgefordert kontaktiert wurden.
• Freigaben hinterfragen: Wenn Sie Freigaben für Dateien in Cloud-Speichern erhalten, kontaktieren Sie zunächst den Absender, idealerweise telefonisch.

Infos zu aktuellen Angriffen: Informieren Sie sich über Phishing-Kampagnen etwa bei der Verbraucherzentrale NRW.

Als letzte Verteidigungslinie lassen sich Antivirenprogramme, Browserschutz und Spezial-Tools einsetzen:

• Antivirus: Große Sicherheits-Suiten wie G Data Internet Security filtern Phishing-Mails heraus, bevor sie diese Nachrichten öffnen.
• Browser-Schutz: Browser von Sicherheitsanbietern blockieren viele aktuelle Phishing-Seiten, etwa der KI-Browser Norton Neo.
• Spezial-Tools: KI-Chatbots wie Scamio von Bitdefender begutachten verdächtige Nachrichten und warnen vor gefährlichen Inhalten.

Arne Arnold

Zimbra Phishing Campaign Uses CVE-2025-66376

LAUNDRY BEAR Targets Email and Sensitive Data

Ulej and Flowerbed Support Email Data Exfiltration

Organizations Urged to Patch Vulnerable Zimbra Systems

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Hallo, ich bin der Michi, willkommen zur vierten Ausgabe des HMX-6-Newsletters. Diese Woche erfahrt ihr, welche Grafikkarten wir in der HMX 6 verbauen. Außerdem verraten wir, warum Halo das Design der HMX 6 prägen wird. Außerdem reisen wir zurück ins Jahr 2012 zur Höllenmaschine 4, die mit vier Grafikprozessoren neue Maßstäbe beim Gaming setzte. Wenn ihr keine Ausgabe verpassen wollt, könnt ihr den Newsletter kostenlos abonnieren – aber vergesst nicht, die Anmeldung via E-Mail zu bestätigen. Viel Spaß beim Lesen!

Hier geht es direkt zum Gewinnspiel der HMX 6 im Gesamtwert von 40.000 Euro.

HMX 6: 2x RTX 5090 von ZOTAC GAMING und Halo-Design

Jetzt können wir endlich verraten, welche Grafikkarten in der HMX 6 stecken: Als primäre Gaming-Grafikkarte der HMX 6 ist die RTX 5090 AMP Extreme INFINITY gedacht, während wir parallel dazu die RTX 5090 ARCTICSTORM AIO für verlustfreie Skalierung verwenden, um Bildqualität und -wiederholrate in praktisch jedem Videospiel zu verbessern. Natürlich könnt ihr die gebündelte Kraft der zwei 5090 auch im kreativen Einsatz nutzen, etwa beim 3D-Rendering oder KI-Berechnungen. Hier findet ihr alle Informationen zu den zwei ZOTAC-Grafikkarten.

ZOTAC

Eigentlich wollten Kris und ich euch diese Woche schon den aktuellen Stand des Casecon im Halo-Design zeigen. Doch unserem Modder Stefan Ulrich fehlen noch diverse Materialien. Jetzt fahren wir wahrscheinlich nächste Woche, doch die Zeit drängt schon wieder, denn wir wollen ja auf die Gamescom mit der HMX 6.

Rückblick: Die Höllenmaschine 4 setzte technische und optische Maßstäbe

Neue Maßstäbe setzten wir 2012 auch bei der Vermarktung der Höllenmaschine 4 – zumindest für unsere Verhältnisse: vier aufwendig produzierte Teaser-Videos mit Engelchen und Teufelsdamen sowie Fritz als Padawan von Obi-Wan Michi. Das hat riesigen Spaß gemacht und uns als Team Hölle zusammengeschweißt – und war der Beginn einer wunderbaren Freundschaft.

PC-WELT

Technisch auf der Höhe der Zeit waren wir mit den beiden Grafikkarten ASUS GTX690-4GD5, die jeweils zwei 915 MHz schnelle Nvidia Geforce GTX 690 beherbergten. Vier Grafikprozessoren gleichzeitig waren damals absoluter Wahnsinn und sorgten regelmäßig für offene Münder. Dazu gab es den Sechskerner Intel Core i7-3960X, 64 GB RAM im Vierkanalmodus, mit der OCZ RevoDrive die erste PCIe-SSD in einer Höllenmaschine und mit 10 Terabyte natürlich auch wieder verrückt viel HDD-Speicherplatz.

Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Sie haben ins Cooler Master Cosmos II ein Sichtfenster gefräst und per Airbrush lodernde Flammen auf die beiden Flügeltüren gezaubert. ARGB war damals noch kein Thema, aber mit dem Multidimmer von Richter waren immerhin individuelle Farbtöne und -wechsel per IR-Fernbedienung möglich. Hier geht es zum liebevoll restaurierten Artikel zur Höllenmaschine 4 aus 2012.

Maus mit Noctua-Lüfter und Steam Machine im Praxis-Test

Diese Woche ist eine skurrile Mail in meinem Postfach gelandet: Pulsar und Noctua präsentieren stolz die Früchte ihrer Zusammenarbeit: die Feinmann F01 Noctua Edition, eine Gaming-Maus mit aktiver Belüftung der Handflächen. Ich bin gespannt, wer sich über kühlere Handflächen beim Zocken freut.

Noctua/Pulsar

Mein Kollege und Namensvetter Michael Crider hat sich die kostspielige (ab 1.039 Euro) Steam Machine gekauft und einem ausführlichen Praxistest unterzogen. Sein Fazit fällt allerdings ernüchternd aus: Ein günstiger Mini-PC mit selbst installiertem SteamOS bietet derzeit nahezu denselben Nutzen für deutlich weniger Geld.

Warum es ein Problem ist, dass in neuen Laptops alte CPUs zum Einsatz kommen, erklärt mein Kollege Mark Hachman.

Vielen Dank fürs Lesen!

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Executive summary 

A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see Cybersecurity industry tracking), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [1].

LAUNDRY BEAR’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data. Previous campaigns indicated LAUNDRY BEAR relied on unsophisticated initial access techniques—including password spraying, phishing, and pass-the-cookie—allowing the group to successfully run high-volume operations. The latest campaign targeting ZCS uses a novel exploit that was a zero-day vulnerability when first exploited and continues to be successfully exploited. The vulnerability, Common Vulnerabilities and Exposures (CVE) CVE-2025-66376, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.

Unlike traditional phishing campaigns that persuade a user into taking an action, such as clicking a link or opening a file, LAUNDRY BEAR’s latest campaign leverages a view-based exploit that only requires a user to view a malicious email within a vulnerable version of the webmail service. Once viewed, the exploit attempts to exfiltrate the victim’s last 90 days of email communications, the organization email directory (i.e., Global Address List [GAL]), and other sensitive information to servers controlled by LAUNDRY BEAR. The exploit also attempts to establish persistent access to victim accounts through a variety of means as detailed in the Persistence and credential access section.

This Cybersecurity Advisory (CSA) warns of this ongoing malicious threat activity and urges organizations to update their vulnerable software and implement additional mitigations to thwart these Russian state-supported actors’ continued success. The CSA is being released by the following authoring and co-sealing agencies:

• United States National Security Agency (NSA)
• United States Federal Bureau of Investigation (FBI)
• Netherlands Defence Intelligence and Security Service (MIVD)
• Netherlands General Intelligence and Security Service (AIVD)
• United States Cybersecurity and Infrastructure Security Agency (CISA)
• United States Defense Counterintelligence and Security Agency (DCSA)
• United States Department of Defense Cyber Crime Center (DC3)
• United States Department of the Treasury
• United States Naval Criminal Investigative Service (NCIS)
• Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
• Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
• New Zealand National Cyber Security Centre (NCSC-NZ)
• United Kingdom National Cyber Security Centre (NCSC-UK)
• Czech Republic National Cyber and Information Security Agency (NÚKIB)¹
• Danish Defence Intelligence Service (DDIS)²
• Estonian Foreign Intelligence Service (EFIS)³
• Finnish Defence Intelligence (FDI)⁴
• Finnish Security and Intelligence Service (SUPO)⁵
• French General Directorate for Internal Security (DGSI)⁶
• French National Cybersecurity Agency (ANSSI)⁷
• Italian External Intelligence and Security Agency (AISE)⁸
• Italian Internal Intelligence and Security Agency (AISI)⁹
• Security and Intelligence Service of the Republic of Moldova (SIS RM)¹⁰
• Polish Foreign Intelligence Agency (AW)¹¹
• The Military Counterintelligence Service of Poland (SKW)¹²
• Spain National Intelligence Centre (CNI)¹³
• Sweden National Cyber Security Centre (NCSC-SE)¹⁴

The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the Mitigations section of this advisory to reduce the risk associated with this activity. This CSA also includes specific remediations for organizations to implement if they discover the presence of the listed Indicators of compromise (IOCs).  

As more organizations update their ZCS software based on this CSA, LAUNDRY BEAR may discontinue the current campaign exploiting this vulnerability; however, based on the success of this and previous campaigns, it is very likely that the group will continue to target ZCS and other email systems used by organizations in Western countries. The actors will almost certainly continue to rely on email to engage potential victims by exploiting novel vulnerabilities and, when necessary, use social engineering techniques to assist with their efforts. The authoring agencies recommend organizations regularly update their mail service software and continuously monitor their email systems and emails for malicious activity.

For a downloadable list of IOCs, see:

• AA26-204A.stix.xml (STIX XML)
• AA26-204A.stix.json (STIX JSON)

Cybersecurity industry tracking

The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to these Russian state-supported cyber actors. While not exhaustive, the following are threat group names commonly used for these actors within the cybersecurity community:

• LAUNDRY BEAR
• Void Blizzard [2]
• CL-STA-1114 [3]
• TA488 (formerly UNK_PitStop) [4]

Note: Cybersecurity companies have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the U.S. government’s understanding for all activity related to these groupings.

Background

Public advisories from Netherlands General Intelligence and Security Service (AIVD), Netherlands Defence Intelligence and Security Service (MIVD), and Microsoft highlighted these Russian state-supported advanced persistent threat (APT) actors in May 2025, calling them LAUNDRY BEAR and Void Blizzard respectively [1] [2]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.  

The May 2025 advisories highlighted a cluster of activity targeting cloud-based email environments, including Microsoft Exchange in particular, and abusing legitimate APIs to perform data exfiltration in bulk [T1114.002]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [T1078], and using social engineering techniques to lure targets into interacting with a malicious site masquerading as a legitimate one. As of April 2025, one of these sites resembled a European Defence & Security Summit registration portal that required registrants to sign in to their Microsoft account to view. Once a user entered their Microsoft credentials into this malicious site, LAUNDRY BEAR’s modified version of the open source adversary emulation toolkit, Evilginx, intercepted the user’s credentials. LAUNDRY BEAR then used this authentication data, including passwords and session tokens, to access the compromised account and conduct mass email exfiltration, as well as harvest other information. This method of compromise is commonly known as an adversary-in-the-middle (AiTM) technique [T1557].  

Beginning around July 2025, LAUNDRY BEAR shifted toward a more technical method of email compromise, highlighting their continued efforts to covertly acquire email communications from a variety of Western organizations of interest and deliver them to the Russian Federation. Using a custom-developed capability [T1587.001] named “Улей” or “Ulej” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [T1114]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:

• Last 90 days of emails,
• Email address,
• Password [T1589.001],
• Global Address List (GAL) [T1087],
• Two-factor authentication (2FA) tokens, and
• Newly-created Application Passcode [T1098].

The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing. Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.

Targeting details

LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:

• the Defense Industrial Base (DIB),  
• the federal and local government,
• education,
• energy,
• law enforcement,  
• media,  
• non-governmental organizations, and
• technology.

Technical details

Note: This advisory uses the MITRE ATT&CK® Matrix for Enterprise framework, version 19. This advisory also uses MITRE D3FEND^TM version 1.4.0¹⁵. See Appendix A and Appendix B for tables of the activity mapped to MITRE ATT&CK and D3FEND tactics, techniques, and countermeasures.

Ulej is a novel data exfiltration and aggregation capability, that currently (as of the publication of this report) supports a campaign specifically targeting users of ZCS webmail servers. This capability is used to exploit CVE-2025-66376 [Common Weakness Enumeration (CWE) CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')], but likely could be adapted to exploit other vulnerabilities. It exfiltrates emails and other sensitive user data from a victim’s system immediately after exploitation and stores the data in an actor-controlled unattributable virtual private server (VPS) [T1074.002] running LAUNDRY BEAR’s “Flowerbed” collection framework. The collected data is almost certainly further exfiltrated to internal network resources for review and long-term retention.

Reconnaissance

LAUNDRY BEAR uses the Ulej capability to exploit the CVE-2025-66376 vulnerability in organizations using ZCS. This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations. LAUNDRY BEAR likely identifies organizations with public-facing Zimbra infrastructure by port scanning [T1595] and fingerprinting datasets easily procured through various commercial vendors [T1596.005].  

After identifying a target organization, the group likely compiles email addresses for individual users to target with the exploit [T1589.002] from datasets offered by commercial vendors [T1597.002], open source intelligence [T1593], or previously exfiltrated data [T1597].  

Resource development

The actors procure VPSs from a variety of providers [T1583.003], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [T1583] when interacting with these servers, further demonstrating the group’s intent to mask their identity and maintain operations security (OPSEC). After the server is provisioned, an automated process deploys the Docker containers necessary for Ulej’s Flowerbed framework [T1608], which then receives and aggregates the data Ulej exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.

Flowerbed framework

Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:

• Catcher,
• Certbot,
• Nginx, and
• Gardener.

Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [T1048]. For additional information on Catcher, refer to the Exfiltration section of this advisory. Flowerbed’s next container, Certbot, is based on one of the official Certbot containers, which allows for automated generation of Let’s Encrypt certificates using DNS challenges through Cloudflare. This certificate can then be used by the Nginx container, which serves as an HTTPS reverse proxy for Catcher, enabling Flowerbed to disguise some of its exfiltration activity through an encrypted communications channel [T1048.002]. The Nginx reverse proxy also validates that the Server Name Indicator (SNI) value contains “*.i.*” prior to forwarding the traffic to Catcher. If the SNI does not contain that string, the Nginx server returns a 444 error to the client. This is likely an attempt to reject non-Ulej connections. Finally, the Gardener container functions as a health check for the Catcher service. Gardener is a simple Python script that validates Catcher correctly receives and processes data.

The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development. This highlights how AI is increasingly being used to develop malicious capabilities [T1588.007]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [T1588.002], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.

Initial access

To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [T1566]. Through exploitation of CVE-2025-66376, this JavaScript payload is immediately executed once the user views the malicious email [T1203], such as the one shown in Figure 1, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [T1199], as shown in the email metadata in Figure 2. These compromised accounts were likely previous victims of this, or another LAUNDRY BEAR, campaign and their use is intended to further obfuscate and frustrate anti-phishing tools and training.

According to the National Vulnerability Database (NVD), CVE-2025-66376 was initially published on 5 January 2026. This vulnerability allows for execution of a JavaScript payload included in email content due to improper sanitization of Cascading Style Sheet’s (CSS) @import directives within an email [5]. Because the activity attributed to this campaign began in July 2025—months before Synacor released a patch and the CVE was published—the payload initially exploited a zero-day vulnerability at that time [T1587.004].  

Utilization of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability.

Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [T1027.017], as shown in Figure 3. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage CVE-2025-66376. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see Figure 3) [T1027.013]. The outer payload decodes and decrypts the inner payload using an XOR function and a hardcoded key and then executes the script contained within the inner payload containing the collection and exfiltration logic. By changing the key used for the XOR encryption of the inner payload or adding additional @import directives with non-functional code [T1027.010], LAUNDRY BEAR can easily generate new payloads that bypass basic threat detection signatures. This malicious payload attempts to collect and exfiltrate information in 12 asynchronous stages [T1119]. The stages in order of appearance within the payload are as follows:

1. sendStartPing,
2. gather_email,
3. gather_environment,
4. gather_2fa_codes,
5. gather_app_password,
6. gather_device_status,
7. gather_oauth_consumers,
8. gather_autocomplete_password,
9. enable_mail_protocols,
10. gather_gal,
11. sendArchives, and
12. sendFinishPing. 

Use of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability [T1587].

Persistence and credential access

To establish sustained persistence into the victim’s email account, the script attempts to modify account preferences and collect authentication information. Any collected credentials are later exfiltrated, as further described in the Exfiltration section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [T1550.004], and the Zimbra campaign follows a similar trend.

The script used in this campaign tries to discover the victim’s email address during the gather_email stage [T1087]. The script searches for this email address in two ways. First, it examines the batchInfoResponse variable, which an HTML script element on the webpage can define, for an email address. Even if the script finds an email address there, it also checks whether it acquired a Cross-Site Request Forgery (CSRF) token as described later in the Collection section of this advisory. If so, the script uses the “GetIdentitiesRequest” Simple Object Access Protocol (SOAP) command under the “ZimbraAccount” namespace to determine the victim’s email address [T1185] and then exfiltrates it. However, if the script does not have a CSRF token or the SOAP request fails, the script exfiltrates the email value recovered from the first method instead. If both attempts fail to capture the victim’s email, the script sends a JavaScript Object Notation (JSON) payload with a key of “email” and value of null over HTTPS and does not attempt DNS exfiltration.

During the gather_autocomplete_password stage, the script attempts to collect the victim’s saved password via the autocomplete feature of the victim’s password manager. The script injects two HTML div elements requesting login credentials onto the page outside of the victim’s view, as shown in Figure 4 and Figure 5. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in Figure 4. If there is no value in that input field, it checks the password input field shown in Figure 5. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of null is sent over HTTPS and DNS exfiltration is not attempted.

LAUNDRY BEAR almost certainly relies on a mail client using the Internet Message Access Protocol (IMAP) for persistent access to the victim’s mailbox. During the enable_mail_protocols stage, a SOAP request leveraging the “ModifyPrefsRequest” command under the “ZimbraAccount” namespace is sent. This request attempts to set the “zimbraPrefImapEnabled” preference to TRUE. While the default setting for “zimbraPrefImapEnabled” is not well documented, this action is almost certainly intended to ensure that IMAP access to the victim’s mailbox is enabled.

ZCS does not support 2FA for some mail clients, including IMAP. To support users who rely on IMAP clients, ZCS allows for the generation of Application Passcodes. Application Passcodes are randomly generated passwords that can be used for clients that cannot support the normal 2FA process to authenticate. During the gather_app_password stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [T1556.006]. The SOAP request uses “ZimbraWeb” as the name of the application.

Additionally, the script also attempts to collect 2FA tokens. During the gather_2fa_codes stage, the script makes a SOAP request using the “GetScratchCodesRequest” command under the “ZimbraAccount” namespace. The script then attempts to exfiltrate any non-null 2FA codes collected this way. The number of codes can vary, and each code is exfiltrated to Flowerbed individually.

Collection

As demonstrated in the Persistence and credential access section, this script relies heavily on SOAP requests to collect victim information. To make these requests, the script aims to acquire the victim’s current CSRF token, which it attempts to access within the webpage’s local storage using localStorage.getItem("csrfToken"). If the script is unable to acquire this CSRF token, it will be unable to make any SOAP requests. In addition to the SOAP commands documented in the Persistence and credential access section, other SOAP commands executed to collect victim information are shown in Table 1.

The script attempts to collect the victim’s GAL through brute force by searching for each two-character combination from a character set of “abcdefghijklmnopqrstuvwxyz1234567890.-_”. These queries are conducted using 20 batches of SOAP requests with 77 “SearchGalRequest” SOAP commands in each batch except for the last request containing only 58.

During the gather_environment stage, the script attempts to determine which type of ZCS webmail client the victim is using. The script checks the user’s current URL to determine the client type being used, checking for certain indicators (shown in Table 2) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.

As part of collection, the script attempts to harvest any emails not marked as “junk” from the last 90 days from the victim’s account. Emails are collected daily by an HTTP GET request to the URL path, “/home/~/?fmt=tgz&meta=0&query=date:-{DAY_OFFSET}d AND (not in:junk)”. The {DAY_OFFSET} value would be between 0 and 89 representing how many days ago the email was sent or received. To prevent redundant collection and exfiltration of emails, a variable with a name based on the email date being queried, using a format of zd_comp_YYYY-MM-DD, and value of true, is saved to the window.top.localStorage property. This variable is saved regardless of whether the email is successfully exfiltrated.  

According to Mozilla documentation, if the user is not in a private browsing session, any data stored to localStorage does not typically expire. This means that if the user happens to execute the script again from the same computer, the script avoids attempting to re-exfiltrate previously captured emails. However, the script always attempts to pull any emails with a {DAY_OFFSET} of zero. In other words, the script always pulls emails sent or received the same day it is run. After email results are returned from the query for each day of email activity, those results are then passed to Flowerbed as described in the Exfiltration section.

The script also provides LAUNDRY BEAR with telemetry on any errors that occur during the collection process. This is accomplished by executing any collection or exfiltration code through helper functions that contain error handling logic. If an error occurs, a payload containing information on the error itself, the context of the error happening, and the stage in which the error occurred is sent to Flowerbed as described in the Exfiltration section below. For cases where the error occurs within a SOAP request, “:api” is concatenated to the stage value in the payload. If an error occurs during the batch SOAP requests that occur when collecting the GAL of the victim, the stage value will use a format of gather_gal:{VAL}:api. The {VAL} placeholder indicates which batch request, a number from 0 to 19, the error occurred in. Errors that occur during the password autocomplete interception process will use “gather_autocomplete_password:dom” for the stage value. Finally, if an error occurs when attempting to collect or exfiltrate a specific day’s emails, the stage will include which day the error occurred on, using the previously defined placeholder {DAY_OFFSET}, with a format of sendArchive:day-{DAY_OFFSET}.

Exfiltration

At the end of each stage in the collection process, the script attempts to exfiltrate acquired information to Flowerbed. The script primarily relies on two forms of data exfiltration: DNS [T1048.003] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.

Prior to exfiltration, a randomized 10- or 11-character alphanumeric string is generated as an identifier for the victim. This identifier is included in the URL of both the DNS- and HTTPS-based exfiltration.  

DNS exfiltration

DNS exfiltration occurs through DNS A record queries. To ensure data exfiltrated through DNS is not corrupted when traversing through non-actor-controlled DNS infrastructure, Ulej maintains compliance with RFC 1035, Domain Names - Implementation and Specification, specifically accounting for the case insensitivity and subdomain length requirements. Base32 encoding is used to create a case-insensitive payload. Once the payload is encoded, a period (“.”) is added every 60 characters to ensure each subdomain is under 63 characters long. The script then creates a new image object sourced from a URL with the scheme defined in Figure 6. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.

When the script generates an image object, the browser tries to retrieve the complete domain of the URL specified as the source of the image. This triggers a DNS request sent to the actor-controlled server and processed by Flowerbed. Table 3 lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.  

HTTPS exfiltration

Any information exfiltrated via DNS is also exfiltrated through HTTPS, as well as additional data including email content, contacts, attachments, and error logging information. By using Let’s Encrypt certificates, this group can quickly deploy new infrastructure and leverage encrypted HTTPS communications with valid server certificates when exfiltrating information from the victim’s environment. The HTTPS exfiltration capability only uses two HTTP content types, defined in Table 4. Traffic associated with HTTPS exfiltration will use the URL scheme shown in Figure 7.  

Some of the data transmitted via HTTPS uses the standard JSON content type format. The script includes the information in a POST request to actor-controlled infrastructure.  

Table 5 provides a summary of the JSON-based exfiltration.

The script transmits all HTTPS exfiltration not identified in Table 5 using the Octet-Stream content type as binary data. The POST requests for this method include a filename in the “X-Filename” header. Traditionally, developers use headers prefixed with “X-” to denote custom headers that do not follow a defined standard. The purpose of including this header remains unclear since the Catcher capability ignores the provided filename when saving the data. Table 6 summarizes the data exfiltrated in this format.

The script sends all exfiltrated data identified in Table 6 to the Catcher service exactly as received from the SOAP request in a JSON payload, except for email exfiltration. For email exfiltration, the script sends it as a GZIP compressed archive [T1560]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in Table 6 using the application/octet-stream content typing rather than application/json.

At the beginning and end of the collection and exfiltration activity, during the sendStartPing and sendFinishPing stages respectively, the script submits a POST request with a JSON payload to indicate that the script is starting or finishing execution. Throughout execution, the script also logs error events and send the logs using similar JSON payloads. The script sends the JSON in a POST request to the URL documented in Figure 2, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (start, finish, or error).  

Catcher

Ulej exfiltrates information to Flowerbed to be handled by a service named Catcher. Catcher is a containerized Python application, running in Docker as part of Flowerbed, which is detailed in the Resource development section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.

Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the Resource development section, the Flowerbed project uses an additional Docker container running an Nginx reverse proxy to enable HTTPS support. This reverse proxy uses a certificate generated by Let’s Encrypt and forwards all traffic with an SNI containing “*.i.*” to port 8000 within the Catcher container.

The DNS service can accept A, AAAA, MX, TXT, and CAA queries. For any MX, AAAA, or CAA queries, the server will always provide an empty response. The system only supports TXT records as needed to process Automatic Certificate Management Environment (ACME) requests, which enable the assignment of Let’s Encrypt certificates. If the server receives an A query, Catcher will always respond with the public IP address of the Flowerbed server.  

However, if a query includes a domain formatted as shown in Figure 6 and Figure 7, the service saves a log file in JSON format to disk containing the following details of the DNS query:

• Time of query,
• Source IP address for query,
• Queried domain, and
• Type of query.

The HTTP server typically responds with OK, except in cases where the path is “pixel.gif” when the response contains a 1x1 gif image with a SHA-256 hash of ef1955ae757c8b966c83248350331bd3a30f658ced11f387f8ebf05ab3368629. Like the DNS service, the HTTP service will only log entries when the domain found in the host header of the request follows the expected formatting as seen in Figure 6 and Figure 7. As the HTTPS exfiltration uses non-standardized binary and JSON-formatted payloads when exfiltrating to Catcher, Catcher will check the content type of the request. If the content type is set to “application/json”, Catcher encodes the data in Base64 and includes it in the JSON log entry written to disk. If the content type is set to any other value, Catcher leaves the Base64 payload in the JSON log entry blank and saves the payload to a separate file with the same filename as the JSON log entry with a “.bin” file extension. An HTTPS exfiltration event causes Catcher to save a JSON formatted log file to disk containing the following information from the HTTP request:

• Time,
• Source IP address,
• Request method,
• Host,
• Path,
• Query string,
• Headers, and
• Base64 payload.

These JSON event log files and binary output files are then initially saved to the directory /root/hits/tmp and later moved to the /root/hits/ready directory once processed. This prevents incomplete files, which are still being uploaded to Catcher, from premature exfiltration from the server. Approximately every 60 seconds, a likely automated workflow establishes a Secure Shell (SSH) connection with the server hosting Flowerbed for a few seconds, almost certainly exfiltrating the data processed by Catcher to non-public-facing infrastructure. The command in Figure 8 also executes hourly to remove all files last modified at least two days ago from the /root/hits/ready directory.

Response strategies

Mitigations

In many cases, by the time an organization identifies a compromise related to this campaign, numerous sensitive and proprietary emails have already been exfiltrated. The significant risk posed by this cyber threat emphasizes the importance for organizations that use ZCS and other similar webmail solutions to take proactive steps to mitigate this risk.

All organizations that use the ZCS webmail service should immediately prioritize ensuring that their ZCS is not running a vulnerable version. A patch for CVE-2025-66376 was released for both 10.1.13 and 10.0.18 versions of ZCS [D3-AH]. If immediate patching is not feasible, organizations should advise employees to use alternative mail clients to access email and avoid using the Classic ZCS webmail client until ZCS is updated to a non-vulnerable version [d3f:Isolate].

System administrators should closely monitor any Internet-connected ZCS or other email systems and the workstations that access those systems and promptly apply available software updates [D3-AH]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including CISA’s Known Exploited Vulnerabilities Catalog and NCSC-UK’s Responding to active exploitation of vulnerabilities guidance.

Organizations should consider using a third-party authentication service that supports passkeys for authentication to mediate access to ZCS and other services that do not natively support passkeys. By doing so, organizations can work to eliminate the possibility of automated password collection from autocomplete or password reuse [D3-CH]. However, Application Passcodes may still be necessary and should be monitored closely.  

Organizations should implement network monitoring capabilities with collection and short-term retention of packet capture or NetFlow data and maintain log collection and storage [CPG 3.Q]. This will allow organizations to monitor for and identify suspicious network activity [CPG 4.B], such as:

• Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [D3-NTA];
• Frequent DNS queries for a suspicious domain with seemingly random subdomains [D3-DNSTA];
• A sudden spike of connections to a server associated with a recently established domain [D3-NTCD]; and  
• Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [D3-NTCD].

Additionally, for organizations that can inspect the content of outbound HTTPS connections via break-and-inspect infrastructure, security teams should identify traffic matching the characteristics described in the Exfiltration section of this advisory.

Indicators of compromise (IOCs)

Flowerbed infrastructure

The following indicators have been attributed to use by LAUNDRY BEAR for their campaign targeting ZCS’s webmail service as of the publication of this advisory. (Disclaimer: Due to the frequency of operational structure changes by this group, these indicators are intended solely for historic attribution purposes. Some indicators, such as IPs, compromised emails, and domains, may be outdated, so organizations should check for current activity before acting on these IOCs.) Table 7 provides details about the server infrastructure used to host Flowerbed, and Table 8 lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [D3-IAA].

LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:

• ivanka.zurabishvili@proton[.]me,
• zmul1@buildandconsulting[.]com,
• garrysmithme@pinmx[.]net, and
• hostingclient@pinmx[.]net.

Phishing distribution

LAUNDRY BEAR primarily relied on ProtonMail for distribution of malicious email. However, as stated above, LAUNDRY BEAR’s more recent efforts likely have shifted to distributing the payload through previous victims.  

The following email addresses have distributed payloads attributed to this campaign:

• c.laurent.ejfa@proton[.]me,
• j.moreau.epsc@proton[.]me,
• liberty.insights@proton[.]me,
• certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and
• certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).

Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:

• 98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,
• 60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,
• b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and
• 1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.

Post-compromise artifacts

Currently, the script does not remove artifacts. This leaves additional opportunities to identify victims of this activity. While emphasis should always be placed on consistent monitoring of network traffic and endpoint activity, there are a variety of persistent artifacts described below that can be used to identify victims of this campaign.

This Ulej capability relies on creating a significant number of SOAP requests to collect account information for exfiltration. ZCS logs from these requests are stored, by default, in the /opt/zimbra/log/mailbox.log file [D3-PA]. A significant amount of SOAP request activity that aligns with what was described in the Persistence and credential access and Collection sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:

• Many SearchGalRequest command requests from a single user over a short period of time;
• Use of the CreateAppSpecificPasswordRequest command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and
• Use of the GetScratchCodesRequest command.

While LAUNDRY BEAR uses the localStorage property to track what days had emails previously exfiltrated, defenders can use this property to identify victims of this campaign and determine the scope of exfiltrated information [D3-PA]. Review of the items stored in that property for an organization’s ZCS webmail client page on an endpoint device could indicate compromise if there are items named with a format of zd_comp_YYYY-MM-DD, as explained in the Collection section of this advisory.

While Application Passcodes have non-malicious purposes, in this case instances of these passcodes with the name “ZimbraWeb” are almost certainly malicious. The ZCS webmail application can support 2FA natively and does not require the use of an Application Passcode, so there is no reason that there should be one named “ZimbraWeb.”

In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [D3-MA]. If an email that has a payload exploiting CVE-2025-66376 is discovered, steps should be taken immediately to identify and quarantine other instances of emails with similar body content, senders, and subject lines to prevent further exploitation and exfiltration.  

Remediation

In the event an organization identifies activity associated with this campaign, that organization should take steps to minimize further exploitation. The organization should consider requesting that employees minimize use of the ZCS webmail client until the organization updates to a patched version that is not vulnerable to CVE-2025-66376.

Organizations should use identifiers from the IOCs section of this report to identify any individuals compromised by this campaign and record the date(s) of compromise(s) to determine the scale and scope of emails exfiltrated.

All users from the organization should have all Application Passcodes and 2FA scratch keys revoked. Affected organizations should require all employees to change passwords in line with establishing minimum password strength requirements [CPG 3.B] and creating unique credentials [CPG 3.C], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.

Works cited

[1] Netherlands General Intelligence and Security Service (AIVD) and Netherlands Defence Intelligence and Security Service (MIVD). AIVD and MIVD identify a new Russian cyber threat actor. 2025. https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf

[2] Microsoft Corporation. New Russia-affiliated actor Void Blizzard targets critical sectors for espionage. 2025. https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/

[3] Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. https://unit42.paloaltonetworks.com/russian-webmail-espionage/ 

[4] Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit

[5] Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/  

Footnotes

¹ Národní úřad pro kybernetickou a informační bezpečnost
² Forsvarets Efterretningstjeneste
³ Välisluureamet
⁴ Sotilastiedustelu
⁵  Suojelupoliisi
⁶ Direction générale de la sécurité intérieure
⁷ Agence nationale de la sécurité des systèmes d’information
⁸ Agenzia Informazioni e Sicurezza Esterna
⁹ Agenzia Informazioni e Sicurezza Interna
¹⁰ Serviciul de Informații și Securitate al Republicii Moldova
¹¹ Agencja Wywiadu
¹² Służba Kontrwywiadu Wojskowego
¹³ Centro Nacional de Inteligencia
¹⁴ Nationellt Cybersäkerhetscenter
¹⁵ MITRE and ATT&CK are registered trademarks of The MITRE Corporation. MITRE D3FEND is a trademark of The MITRE Corporation.

Acknowledgements

The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.

Disclaimer of endorsement

The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.

Organizations have no obligation to respond or provide information back to the authoring organizations in response to this joint advisory. If, after reviewing the information provided, an organization decides to provide information to the authoring organizations, reporting must be consistent with all applicable laws and policies.

Purpose

This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.

Contact

Appendix A: MITRE ATT&CK tactics and techniques

See Table 9 through Table 19 for all the threat actor tactics and techniques referenced in this advisory.

Appendix B: MITRE D3FEND countermeasures

See Table 20 for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.

Der Artikel WorldMonitor holt die Weltlage ins eigene Heimnetz erschien zuerst auf TARNKAPPE.INFO

Artikel & Newsletter: https://digitaleprofis.de/die-ki-news-der-woche-vom-23-07-2026/

Quellen
OpenAI-Modelle hacken Hugging Face 
Artikel: https://openai.com/index/hugging-face-model-evaluation-security-incident/ 
Hintergrund: https://huggingface.co/blog/security-incident-july-2026 

Digitaleprofis.de hat ein Update bekommen 
Website: https://digitaleprofis.de/ 

Kimi K3 ist da 
Artikel: https://www.kimi.com/de/blog/kimi-k3 
Artikel: https://apnews.com/article/kimi-k3-china-ai-0d8a5e268deb11a673f4d444fc597cc5 
Ausprobieren: https://www.kimi.com/ 

Neue Gemini Modelle 
Artikel: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-6-flash-3-5-flash-lite-3-5-flash-cyber/ 
Modellkarte: https://deepmind.google/models/model-cards/gemini-3-6-flash/ 
Cyber-Modell: https://deepmind.google/blog/introducing-gemini-3-5-flash-cyber/ 

Neue Kennzeichnungspflichten des EU AI Acts 
Artikel: https://digital-strategy.ec.europa.eu/en/news/commission-publishes-guidelines-transparency-obligations-providers-and-deployers-certain-ai-systems 
Doku: https://digital-strategy.ec.europa.eu/en/faqs/transparency-obligations-under-article-50-ai-act 

Anthropic zahlt 1,5 Milliarden Dollar 
Artikel: https://m.investing.com/news/stock-market-news/us-judge-approves-anthropics-15-billion-settlement-of-copyright-lawsuit-4801706?ampMode=1 
Artikel: https://apnews.com/article/74b140444023898aeba8579b6e9f0d63 

NotebookLM wird zu Gemini Notebook 
Artikel: https://blog.google/innovation-and-ai/products/gemini-notebook/notebooklm-gemini-notebook/ 

Microsoft und Mistral Partnerschaft 
Artikel: https://news.microsoft.com/source/2026/07/21/microsoft-and-mistral-expand-strategic-partnership-to-give-enterprises-and-regulated-industries-frontier-ai-they-can-control/ 
Artikel: https://www.tagesschau.de/wirtschaft/unternehmen/microsoft-mistral-ai-ki-deal-100.html 

Qwen-Audio-3.0-TTS 
Artikel: https://www.alibabacloud.com/blog/qwen-audio-3-0-tts-more-multilingual-easier-to-direct_603379 
Doku: https://docs.qwencloud.com/developer-guides/speech/tts-models 

OpenAI-Modelle überwinden bei einem internen Sicherheitstest ihre isolierte Testumgebung und gelangen bis in die Produktionsinfrastruktur von Hugging Face.
Wir ordnen den Vorfall ein und fassen die weiteren wichtigen KI-News der Woche kompakt für euch zusammen.

Außerdem geht es um Kimi K3, drei neue Gemini-Modelle, die kommenden Kennzeichnungspflichten des EU AI Acts und den milliardenschweren Urheberrechtsvergleich zwischen Anthropic und Autoren.

Im Video:
- OpenAIs ungewöhnlicher Sicherheitsvorfall bei Hugging Face
- Kimi K3 und drei neue Gemini-Modelle
- Kennzeichnungspflichten des EU AI Acts ab August 2026
- Anthropics Vergleich über mindestens 1,5 Milliarden US-Dollar
- Gemini Notebook, Microsofts Mistral-Partnerschaft und Qwen-Audio-3.0-TTS

Unsere Website wurde ebenfalls vollständig überarbeitet. Auf digitaleprofis.de findet ihr unsere KI-News mit allen Quellen, ausführliche Artikel und praktische Anleitungen – kostenlos, ohne Paywall und ohne Werbung.

Werde Kanalmitglied und unterstütze damit unsere Arbeit:
https://www.youtube.com/channel/UCv90NdTyTp7ZPPRvvSZaS5w/join

Videoinhalt:
00:00 Die KI-News der Woche vom 23.07.2026
00:24 OpenAI Modelle greifen HuggingFace an
02:06 Unsere neue Website für euch
02:59 Kimi K3 ist da und die USA werfen Diebstahl vor
04:28 Drei neue Gemini Modelle, aber kein Pro
05:53 Die neuen Kennzeichnungspflichten des AI Acts
07:21 Anthropic muss 1,5 Milliarden Dollar Vergleich zahlen
08:48 NotebookLM verschwindet - und wird zu Gemini Notebook
09:30 Partnerschaft von Microsoft und Mistral
10:50 Neuen Text to Speech Modell von Alibabas Qwen

Videovorschläge, Feedback und Kritik kannst Du uns jederzeit in den Kommentaren mitteilen!

Ein Netflix-Abo hat mittlerweile so gut wie jeder, doch der eine oder andere wartet vielleicht noch auf eine Möglichkeit, das Streaming-Angebot kostenlos zu testen. Das war seit den Anfängen von Netflix nicht mehr möglich, doch jetzt gibt es wieder einen kostenlosen Probezeitraum.

Bis zu 30 Tage können Sie den Streamingtest jetzt kostenlos nutzen. Teilweise werden auch nur 14 Tage angeboten, der Gratis-Zeitraum scheint also je nach Standort oder genutztem Browser zu variieren. Auf der Webseite von Netflix Deutschland wurden uns auch nur 14 Tage für 0 Euro angezeigt. Es kann aber helfen, wenn Sie auf ein anderes Gerät wechseln oder Cookies löschen.

Wichtig: Das Angebot gilt explizit nur für Neukunden, nicht für wiederkehrende Abonnenten. Allerdings ist es recht einfach, diesen Umstand zu umgehen, wenn Sie sich einfach mit einer anderen E-Mail-Adresse als zuvor registrieren. Dann haben Sie zwar keinen Zugriff auf Ihren alten Account inklusive persönlicher Daten, Listen und Streaming-Historie, doch das ist sicher zu verschmerzen.

Nach Ablauf des Probezeitraums müssen Sie sich für ein Abo entscheiden (oder vorher kündigen). Zur Wahl stehen Standard mit Werbung für 4,99 Euro monatlich, Standard ohne Werbung für 13,99 Euro monatlich oder Premium für 19,99 Euro monatlich.

Warum genau Netflix gerade jetzt ein Probe-Abo wieder einführt, ist nicht ganz klar. Vermutlich versucht der Anbieter aber, neue Abonnenten dazu zu gewinnen, nachdem die Zahlen zuletzt stagnierten. Zwar ist Netflix der größte Anbieter für Streaming, doch die Konkurrenz schläft nicht. Seit Januar 2026 gibt es beispielsweise auch HBO Max in Deutschland, das mit großen Namen wie Game of Thrones, House of the Dragon, Harry Potter oder Superman wirbt.

Eine Übersicht aller wichtigen Streaming-Dienste finden Sie hier, inklusive Preisen, Vorteilen und Nachteilen.

• Type GitHub release metadata by @JamieMagee in #15597
• Make GitCommitChecker strongly typed by @JamieMagee in #15598
• Retry corepack prepare and install on signature metadata errors from private registries by @kbukum1 in #15606
• Fix UV DependencyGrapher to detect nested uv.lock in monorepos by @thavaahariharangit with @Copilot in #15520
• Bump library/rust from 1.95.0-bookworm to 1.97.0-bookworm in /cargo by @dependabot[bot] in #15560
• Bump @sigstore/core from 3.1.0 to 3.2.1 in /npm_and_yarn/helpers by @dependabot[bot] in #15455
• Bump maven from 3.9.14 to 3.9.16 in /maven by @dependabot[bot] in #15127
• Support Bundler source cooldown in Dependabot cooldown flow by @robaiken in #15517
• Type shared release metadata by @JamieMagee in #15607
• Make Job strongly typed by @JamieMagee in #15608
• Type Job wire models by @JamieMagee in #15610
• Type Service and ApiClient by @JamieMagee in #15614
• Add support for calendar-based versions for Maven and Gradle by @yeikel in #14114
• Type error reporting by @JamieMagee in #15615
• Type updater dependency helpers by @JamieMagee in #15617
• ensure proper formatting when patching element attributes by @brettfo in #15629
• Bump ws from 8.18.3 to 8.21.1 in /npm_and_yarn/helpers/test/npm/fixtures/vulnerability-auditor/update-needed-across-two-versions by @dependabot[bot] in #15329
• Bump lodash from 4.17.23 to 4.18.1 in /bun/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14608
• Bump lodash from 4.17.23 to 4.18.1 in /npm_and_yarn/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14609
• Bump lodash from 4.17.23 to 4.18.1 in /npm_and_yarn/helpers/test/npm6/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14610
• Bump the dev-dependencies group across 1 directory with 2 updates by @dependabot[bot] in #14694
• Bump pip from 26.1.1 to 26.1.2 in /python/helpers in the pip group across 1 directory by @dependabot[bot] in #11830
• Bump yaml from 2.3.1 to 2.9.0 in /bun/helpers by @dependabot[bot] in #14535
• npm_and_yarn: group vulnerability auditor blocking-dependency messages by top-level ancestor by @thavaahariharangit in #15627
• Bump ip-address and socks in /bun/helpers by @dependabot[bot] in #14924
• Bump brace-expansion from 1.1.13 to 1.1.16 in /bun/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #15634
• Bump brace-expansion from 1.1.13 to 1.1.16 in /npm_and_yarn/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #15633
• Bump sigstore/cosign/cosign from v3.1.1 to v3.1.2 in /docker in the regclient group across 1 directory by @dependabot[bot] in #15621
• Bump lodash from 4.17.23 to 4.18.1 in /bun/helpers/test/npm6/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14606
• Bump @tootallnate/once from 2.0.0 to 2.0.1 in /bun/helpers by @dependabot[bot] in #15107
• Bump the "uv-ecosystem" group with 1 update across multiple ecosystems by @dependabot[bot] in #14969
• Bump ip-address and socks in /npm_and_yarn/helpers by @dependabot[bot] in #14923
• Bump yaml from 2.3.1 to 2.9.0 in /npm_and_yarn/helpers by @dependabot[bot] in #14533
• Bump golang.org/x/mod from 0.37.0 to 0.38.0 in /go_modules/helpers by @dependabot[bot] in #15559
• Bump @sigstore/verify from 3.1.0 to 3.1.1 in /npm_and_yarn/helpers by @dependabot[bot] in #15477
• julia: don't propose compat updates for workspace packages or synthesize member compat entries by @IanButterworth in #15643
• fix: guard against unparseable versions in cooldown fallback by @currantw in #15632
• Type dependency requirement readers by @JamieMagee in #15646
• v0.388.0 by @dependabot-core-action-automation[bot] in #15623

New Contributors

• @currantw made their first contribution in #15632

Full Changelog: v0.387.0...v0.388.0

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

The post Build an LLM Agent That Can Write and Run Code appeared first on Towards Data Science.

Keine Antenne, kein Kabelanschluss, kein Abo: Auf Ihrem Android-Smartphone oder iPhone können Sie Hunderte TV-Sender kostenlos und legal livestreamen – etwa die WM-Spiele in der U-Bahn oder Ihre Lieblingsspielfilme im Freibad. Wir erklären Ihnen, welche Apps sich lohnen und wie Sie sie einrichten.

ARD Mediathek und ZDF: Öffentlich-rechtlich, kostenlos, ohne Einschränkungen

Den einfachsten Einstieg bieten die Apps der öffentlich-rechtlichen Sender. Die ARD Mediathek (Android / iPhone) gibt Ihnen Zugriff auf Live-TV von Das Erste, den Dritten Programmen, arte, tagesschau24 und weiteren Sendern sowie eine Mediathek mit Sendungen, die bis zu 30 Tage nach Ausstrahlung abrufbar sind.

Die ZDF-App (Android / iPhone) funktioniert nach demselben Prinzip und deckt ZDF, ZDFneo und ZDFinfo ab. Beide Apps sind kostenlos, werbefrei und erfordern keine Anmeldung.

So starten Sie den Live Stream in der ARD Mediathek:

1. Öffnen Sie die App nach der Installation.
2. Tippen Sie unten in der Navigation auf “Live”.
3. Wählen Sie einen Sender aus und tippen Sie darauf, um den Stream zu starten.

Tipp: Es gibt ein kostenloses Tool, mit dem Sie das gesamte Angebot von ARD, ZDF, Arte und vielen weiteren öffentlich-rechtlichen Sendern direkt auf Ihr Handy (oder den PC) laden können. Hier erfahren Sie, wie es geht.

Joyn: Private Sender kostenlos im Stream

Mit Joyn (Android / iPhone) kommen die großen Privatsender dazu. Ohne Anmeldung empfangen Sie über 60 Sender wie ProSieben, SAT.1, Kabel eins und DMAX. Mit einem kostenlosen Joyn-Konto schalten Sie noch mehr Inhalte frei. Joyn+ für 6,99 Euro im Monat entfernt die Werbung und fügt HD-Qualität hinzu, ist aber für den Grundbetrieb nicht nötig.

So starten Sie den Live Stream mit Joyn:

1. Laden und installieren Sie die Joyn-App aus dem Play Store oder App Store.
2. Öffnen Sie die App. Sie müssen sich nicht anmelden.
3. Tippen Sie auf “Live TV” in der unteren Navigation und wählen Sie einen Sender.

PC-Welt

Zattoo: Über 170 Sender in der Gratis-Version

Zattoo (Android / iPhone) bietet mit seiner kostenlosen Version eines der umfangreichsten Gratisangebote im deutschsprachigen Raum: über 170 Sender in einem klassischen TV-Guide-Format.

Ein kostenloses Konto ist erforderlich, die Registrierung dauert aber nur wenige Minuten. Kostenpflichtige Tarife ab 6,99 Euro im Monat fügen HD-Qualität, Timeshift und Aufnahmefunktion hinzu. Einen vollständigen Anbietervergleich finden Sie in unserem Artikel TV ohne Kabel: WaipuTV, Zattoo, Joyn & Co. – die besten IPTV-Anbieter im Überblick.

So richten Sie Zattoo ein:

1. Laden Sie die Zattoo-App herunter und öffnen Sie sie.
2. Tippen Sie auf “Registrieren” und legen Sie ein kostenloses Konto an.
3. Bestätigen Sie Ihre E-Mail-Adresse über den Link in der Bestätigungsmail.
4. Melden Sie sich an und tippen Sie auf einen Sender, um den Stream zu starten.

Pluto TV: Hunderte Themenkanäle ohne Anmeldung

Pluto TV (Android / iPhone) funktioniert anders als klassische TV-Apps: Statt linearer Fernsehsender bietet die Plattform über 250 kuratierte Themenkanäle, die rund um die Uhr Inhalte zu bestimmten Themen senden; angefangen von Krimis über Dokumentationen bis zu internationalen Nachrichten. Alles ist kostenlos, werbefinanziert und ohne Registrierung nutzbar.

So starten Sie das Live-Streaming mit Pluto TV:

1. Installieren Sie die App und öffnen Sie sie.
2. Tippen Sie auf “Live TV” in der unteren Navigation.
3. Scrollen Sie durch die Kanalliste oder nutzen Sie die Suche, um einen passenden Kanal zu finden.
4. Tippen Sie auf einen Kanal, um den Stream sofort zu starten.

Beim Thema Streaming: Lohnen sich die Abos für Netflix, Prime Video und Co. überhaupt noch? Unser großer Vergleich von Netflix, Prime Video, Disney+ und Co. gibt die Antwort.

Der US-amerikanische Software-Hersteller Oracle hält nur alle drei Monate einen turnusmäßigen Patch Day ab. Oracle spricht dabei von „Critical Patch Updates“ (CPU). Aufgrund des umfangreichen Produktportfolios sowie des relativ langen Update-Turnus fallen dabei regelmäßig mehrere hundert zu beseitigende Lücken an. Im Juli sind, dem Trend bei anderen Herstellern folgend, 1449 Schwachstellen zusammengekommen – das ist die mit großem Abstand höchste Anzahl, seit es CPU-Tage gibt und mehr als im gesamten Jahr 2025.

Wegen der starken Zunahme der durch „KI“-Tools entdeckten Schwachstellen hat Oracle seit dem vorherigen CPU-Tag im April zusätzlich monatliche Sicherheits-Updates eingeführt. Die so genannten „Critical Security Patch Updates“ (CSPU) erscheinen weiterhin am dritten Dienstag eines Monats. Bislang ist Java nicht davon betroffen – das wird sich jedoch bereits im August ändern.

Etliche der beseitigten Schwachstellen sind als kritisch einzustufen. Angaben dazu, ob Schwachstellen bereits für Angriffe ausgenutzt werden (0-Day-Lücken), macht Oracle in seinem aktuellen Sicherheitsbericht nicht. Für die Risikobewertung nutzt Oracle den Industriestandard CVSS 3.1 (Common Vulnerability Scoring Standard), dessen höchster Wert 10.0 ist. Auch Microsoft gibt seit einiger Zeit einen CVSS-Score für beseitigte Sicherheitslücken an.

▶Microsofts Monster-Patchday sprengt alle Rekorde

Die dicksten Brocken

Die meisten Sicherheitslücken hat Oracle beim CPU-Tag im Juli in seiner bis dahin eher unauffälligen E-Business Suite geschlossen. Von 410 Schwachstellen sind 45 ohne Benutzeranmeldung über das Netzwerk ausnutzbar und eine erreicht den hohen CVSS-Score 9.8. Nicht weit dahinter folgt Fusion Middleware mit 355 Sicherheitslücken, von denen 46 aus der Ferne ausnutzbar sind und zehn den CVSS-Score 10.0 erreichen.

Diesmal erst an dritter Stelle liegt Oracles Produktfamilie für die Telekommunikationsbranche (Communications). Von den 168 geschlossenen Lücken sind 122 ohne Benutzeranmeldung über das Netzwerk ausnutzbar, 12 davon erreichen den CVSS-Score 9.8. In den Fußnoten nennt Oracle über 160 weitere Schwachstellen, die beseitigt, aber nicht mitgerechnet sind. PeopleSoft kommt auf 84 Lücken, von denen 45 ohne Benutzeranmeldung über das Netzwerk ausnutzbar sind und sechs den CVSS-Score 9.9 erreichen.

Beim quelloffenen Datenbank-Server MySQL nennt Oracle 54 behobene Schwachstellen. Hier sind neun Lücken ohne Benutzeranmeldung über das Netzwerk ausnutzbar und eine erreicht den CVSS Score 8.5. Die neuesten verfügbaren MySQL-Versionen (MySQL Community Server) sind 9.7.1 (LTS – Long Term Support) und 8.4.10 (LTS). Der Versionszweig 8.0 hat mit dem CPU-Tag im April das Support-Ende erreicht, die letzte Version ist 8.0.46.

Java-Updates für sechs Versionen

In Java SE (Standard Edition) hat Oracle insgesamt 19 Sicherheitslücken geschlossen (CVSS-Höchstwert 7.8), von denen 17 ohne Benutzeranmeldung übers Netzwerk ausnutzbar sind. Anders als bislang üblich hat Oracle den nächsten Update-Termin für Java bereits für den 18. August angekündigt. Ab 2027 soll Java monatliche Sicherheits-Updates erhalten. Den halbjährlichen Turnus für Feature-Updates (neue Hauptversionen) will Oracle hingegen beibehalten.

Das im März freigegebene Java 26 erhält sein zweites Sicherheits-Update, das zehn Lücken stopft. Nach einem dritten Update im August wird Java 26 bereits im September durch Java 27 abgelöst.

▶Die neuesten Sicherheits-Updates

Java 25 ist hingegen eine LTS-Version (Long Term Support) und soll bis Sommer 2033 gepflegt werden. Auch Java 21, Java 17 und Java 11 sind LTS-Versionen. Sie werden acht Jahre lang mit Updates versorgt, Java 11 sogar bis 2032. Der neueste Stand sind die Versionen 25.0.4, 21.0.12, 17.0.20 und 11.0.32. Wer Java 21 kommerziell nutzt, benötigt dafür ab Oktober 2026 eine kostenpflichtige Lizenz. Für Java 25 gilt dies ab Oktober 2028. Für private Nutzung sowie für Entwickler bleibt jedoch weiterhin alles kostenlos.

Für Anwender bleibt laut Oracle weiterhin vorwiegend Java 8 (JRE – Java Runtime Environment) relevant und von Oracle empfohlen. Die neueste Version ist Java 8 Update 501 (8u501). Darin hat Oracle 18 Schwachstellen beseitigt. Unternehmen und Behörden müssen seit April 2019 für die Java-8-Updates zahlen, Privatpersonen und Entwickler nicht.

Tipp: Unabhängig davon, dass Sie Ihre Programme stets aktuell halten, sollten Sie die Sicherheit Ihres PCs zusätzlich mit geeigneter Antivirus-Software verbessern. Gute Antivirus-Lösungen stellen wir in „Die besten Antivirus-Programme 2025 im Test: So schützen Sie Ihren Windows-PC“ vor. Falls Sie großen Wert auf anonymes Surfen legen, sind wiederum gute VPN-Programme einen Blick wert.

Lücken in VirtualBox

In der quelloffene Virtualisierungslösung VirtualBox hat Oracle 16 Schwachstellen (max. CVSS 7.8) beseitigt, von denen keine übers Netzwerk ausnutzbar ist. Womöglich lässt es die eine oder andere der Lücken zu, Code aus der VM auf dem Host-System auszuführen. Die neue, abgesicherte VirtualBox-Version ist 7.2.14. Der ältere Versionszweig 7.1 hat mit dem CPU-Tag im April das Ende der Fahnenstange erreicht: Oracle beendet den Support.

Der nächste turnusmäßige Oracle CPU-Tag ist am 20. Oktober 2026. Seit April 2022 sind diese Termine stets am dritten Dienstag im Januar, April, Juli und Oktober. Seit Mai 2026 werden je nach Dringlichkeit auch monatlich Updates bereitgestellt, die eingangs erwähnten CSPU.

Das Teilen großer Dateien und Datenmengen gelingt sehr einfach über Transferdienste in der Cloud. Mit Boomerang gibt es nun ein neues Angebot, hinter dem Start-up steht einer der Gründer des populären Webservice „WeTransfer“. Boomerang lässt sich gratis nutzen, dazu ist nicht einmal eine Anmeldung erforderlich. Ohne Konto steht über den Dienst bis zu einem Gigabyte Speicherplatz zum Verschicken und für sieben Tage zum Download zur Verfügung.

So geht’s: Ziehen Sie bitte auf der Startseite eine oder mehrere Dateien in den Browser. Im folgenden Schritt können Sie über den „Add more“-Button weitere Daten zum Transfer hinzufügen. Mit „Upload Files“ starten Sie das Hochladen, anschließend sehen Sie alle wichtigen Informationen zum Teilen: Mit „Copy Link“ rechts oben kopieren Sie die Download-URL, die Sie dem Empfänger auf beliebigem Weg zuschicken.

Foundry

Wenn Sie ein kostenloses Boomerang-Konto anlegen, können Sie „Spaces“ anlegen und maximal 3 GB große Dateien verschicken. In einem Space verwalten Sie Ihre Dateien, löschen Einträge oder fügen weitere Daten hinzu. Im Boomerang-Dashboard sehen und verwalten Sie die Spaces.

Oben benennen Sie sie um oder wählen zur Kennzeichnung ein Emoji. Option 3 ist das bezahlte Pro-Konto für knapp sieben Euro pro Monat: Es bietet zusätzliche Funktionen beim Datenschutz, 200 GB Speicherplatz, bis zu fünf GB große Dateien und die Bereitstellung der Download-Links bis zu 90 Tagen.

Lesetipp: Vertrauliche Daten sicher von PC zu PC schicken

Dieser Beitrag Langflow RCE: ENCFORGE verschlüsselt KI-Modelle, Vektoren und Trainingsdaten erschien als erstes auf IT BOLTWISE x Artificial Intelligence.

Hier geht's zum Download: https://lmstudio.ai/bionic
Artikel: https://digitaleprofis.de/lm-studio-bionic-im-test/

LM Studio Bionic soll offene KI-Modelle in lokale KI-Agenten verwandeln. Im Praxistest lassen wir Qwen 3.6 35B drei Dateien analysieren und daraus eine Markdown-Auswertung sowie eine PowerPoint-Präsentation erstellen.

Das Ergebnis entsteht lokal auf einem Mac mini M2 Pro, mit korrekten Kennzahlen aus 36 Feedbackbögen, aber auch rund 20 Minuten Laufzeit und einigen klaren Grenzen.
Wir zeigen euch, wie Work- und Code-Projekte funktionieren, wie ihr zwischen lokalen Modellen, einem eigenen Server und der LM Studio Cloud wählen könnt und wie transparent Bionic seine einzelnen Arbeitsschritte darstellt. Anschließend prüfen wir die erstellte Auswertung und Präsentation auf Inhalt, Daten und Gestaltung.

Im Video:
Work Projects und Code Projects
Lokale Modelle, LM Link und Cloud-Modelle
Kosten und Datenschutz
Qwen 3.6 35B auf dem Mac mini
Analyse von Briefing, Feedback und Branding
Markdown-Auswertung und PowerPoint im Ergebnischeck
Stärken, Schwächen und aktuelle Grenzen

Werde Kanalmitglied und unterstütze damit unsere Arbeit:
https://www.youtube.com/channel/UCv90NdTyTp7ZPPRvvSZaS5w/join

Videoinhalt:
00:00 Was ist LM Studio Bionic?
00:43 Projektarten und Model Picker
01:47 Download, Kosten und Datenschutz
03:33 Work-Projekt einrichten
04:25 Lokales Modell auswählen und installieren
06:03 Modell, Dateien und Testauftrag
07:28 Bionic arbeitet mit den Dateien
08:09 Ergebnis nach 20 Minuten
09:02 Markdown und Daten im Check
09:23 PowerPoint-Präsentation im Check
10:37 Fazit: Leistung, Datenschutz und Grenzen

Videovorschläge, Feedback und Kritik kannst Du uns jederzeit in den Kommentaren mitteilen!

Kimi K3 zeigt, dass Open Weight Modelle definitiv nichht mehr weit weg sind von den besten der besten.

Quellen:
https://www.kimi.com/blog/kimi-k3
https://platform.kimi.ai/docs/guide/kimi-k3-quickstart
https://x.com/Kimi_Moonshot/status/2078855608565207130
https://x.com/cramforce/status/2078574147333152957
https://www.blender.org/lab/mcp-server/
https://openrouter.ai/moonshotai/kimi-k3

Blender Benchmark auf Github:
https://github.com/TheMorpheus407/hogwarts-blender-benchmark

MorphCook Benchmark auf Github:
https://github.com/TheMorpheus407/morphcook/

MorphCook:
https://play.google.com/store/apps/details?id=de.themorpheus.morphcook

Zum MorphReader:
Android: https://play.google.com/store/apps/details?id=de.themorpheus.morph_reader_app
Apple: https://apps.apple.com/de/app/morphreader/id6741467699?platform=iphone

RSS Feed: https://www.patreon.com/collection/880029?view=expanded

Instagram: https://www.instagram.com/themorpheustuts/

Meine anderen Kanäle und Projekte: the-morpheus.de/

_Selbst *kostenlos Informatik lernen* auf meiner Website:_ https://bootstrap.academy/

_Discord:_
https://the-morpheus.de/discord.html

_Unterstützt mich - Danke!:_
https://www.patreon.com/user?u=5322110
https://www.paypal.me/TheMorpheus

Gelöschte Whatsapp-Fotos und -Videos lassen sich in vielen Fällen wiederherstellen – über das lokale Dateisystem, ein Google-Drive-Backup oder die iCloud. Welche Methode für Sie die richtige ist, hängt von Ihrem Betriebssystem ab und davon, ob Sie Whatsapp-Backups aktiviert haben. Wir führen Sie Schritt für Schritt durch alle Optionen.

Schnell-Check: Ist das Bild wirklich weg?

Bevor Sie aufwendige Wiederherstellungsversuche starten, sollten Sie zuerst zwei kurze Checks durchführen. Manchmal ist die Lösung nämlich viel einfacher, als wir denken:

• Galerie prüfen: Öffnen Sie Ihre Fotos- oder Galerie-App und suchen Sie dort nach dem Album “Whatsapp” oder “Whatsapp Images”. In manchen Fällen wird ein Bild nur im Chat nicht mehr angezeigt, ist aber noch vollständig im Speicher Ihres Handys vorhanden. Voraussetzung ist, dass die automatische Medienspeicherung in Whatsapp aktiviert ist. Mehr dazu in unserem Artikel Whatsapp-Speicher aufräumen: So löschen Sie unnötige Dateien sicher.
• Erneut herunterladen: Öffnen Sie den betreffenden Whatsapp-Chat. Falls Sie anstelle des Bildes nur eine verschwommene Vorschau mit einem Download-Pfeil sehen, tippen Sie darauf. Whatsapp lädt das Bild erneut von seinen Servern, sofern es noch nicht zu lange zurückliegt.

PC-Welt

Bleibt das Bild trotz der Checks unauffindbar, haben Sie noch weitere Möglichkeiten. Die wichtigsten stellen wir Ihnen in den folgenden Abschnitten vor.

Methode 1: Dateisystem durchsuchen (Android)

Auch wenn ein Bild aus dem Whatsapp-Chat gelöscht wurde und nicht mehr in der Galerie auftaucht, kann es sich noch im Dateisystem des Smartphones befinden. Auf Android legt Whatsapp Mediendateien im internen Speicher unter folgendem Pfad ab: Interner Speicher → Android → media → com.whatsapp → WhatsApp → Media → WhatsApp Images. Für Videos schauen Sie entsprechend im Ordner “WhatsApp Video” nach.

Um in diesen Ordner zu gelangen, benötigen Sie einen Dateimanager. Auf neueren Android-Versionen reicht dafür oft die vorinstallierte App Dateien aus, alternativ funktionieren kostenlose Apps wie der Total Commander aus dem Play Store. Gehen Sie dann so vor:

1. Öffnen Sie die App Dateien oder einen Dateimanager Ihrer Wahl.
2. Navigieren Sie zu Interner Speicher → Android → media → com.whatsapp → WhatsApp → Media.
3. Öffnen Sie den Ordner Whatsapp Images für Fotos oder WhatsApp Video für Videos.
4. Suchen Sie dort nach der gewünschten Datei und kopieren Sie sie an einen sicheren Ort.

Wichtig: Diese Methode funktioniert nur, wenn das Bild zwar aus dem Chatverlauf entfernt, aber die lokal gespeicherte Kopie noch nicht überschrieben wurde. Je länger Sie warten, desto unwahrscheinlicher wird ein Erfolg.

Methode 2: Backup wiederherstellen (Android & iPhone)

Wenn das Bild weder in der Galerie noch im Dateisystem zu finden ist, bleibt der Weg über ein Backup. Whatsapp sichert Chats und Mediendateien regelmäßig automatisch – auf Android in Google Drive und auf dem iPhone in der iCloud. Entscheidend ist, dass das Backup vor dem Löschen des Bildes erstellt wurde.

Prüfen Sie zunächst, wie weit das letzte Backup zurückliegt: Öffnen Sie Whatsapp und navigieren Sie zu Einstellungen → Chats → Chat-Backup. Dort sehen Sie Datum und Uhrzeit der letzten Sicherung. Liegt dieses Datum vor dem Zeitpunkt, an dem das Bild gelöscht wurde, sind Ihre Chancen gut.

Gehen Sie dann so vor:

1. Deinstallieren Sie Whatsapp. Halten Sie dazu das App-Symbol gedrückt und tippen Sie auf Deinstallieren (Android) oder App entfernen (iPhone).
2. Laden Sie Whatsapp neu herunter und installieren Sie die App.
3. Melden Sie sich mit Ihrer Telefonnummer an. Whatsapp erkennt das vorhandene Backup automatisch.
4. Tippen Sie auf Wiederherstellen, um Chats und Medien zurückzuholen.

Achtung: Alle Nachrichten und Medien, die nach dem letzten Backup eingegangen sind, gehen bei diesem Vorgang verloren.

Sonderfall: Das Bild wurde “für alle” gelöscht

Whatsapp erlaubt es, versendete Nachrichten nachträglich bei allen Empfängern zu entfernen. Hat der Absender ein Bild mit “Für alle löschen” entfernt, erscheint im Chat nur noch der Hinweis “Dieses Medium wurde gelöscht”. Weder Backup noch Dateisystem helfen hier weiter, da das Bild nie dauerhaft auf Ihrem Gerät gespeichert wurde.

Eine Ausnahme gibt es: Hatte Ihr Handy das Bild bereits automatisch in der Galerie gespeichert, bevor der Absender es gelöscht hat, ist diese Kopie weiterhin vorhanden. Whatsapp entfernt bei “Für alle löschen” nur die Kopie im Chat, nicht eine bereits in der Galerie gesicherte Version. Mehr zum Thema Gelöschte Whatsapp-Nachrichten und wie Sie diese trotzdem lesen können, erfahren Sie hier.

Datenrettungs-Software: Finger weg oder sinnvoll?

Im Netz werden zahlreiche Tools beworben, die angeblich gelöschte Whatsapp-Fotos direkt aus dem Speicher retten; darunter “Dr.Fone”, “PhoneRescue” oder “Tenorshare UltData”.

Viele werben damit, ohne Root-Zugriff auszukommen. Das stimmt – mit einer wichtigen Einschränkung: Was diese Tools in der Praxis hauptsächlich tun, ist, den Inhalt eines vorhandenen Google-Drive- oder iCloud-Backups auszulesen und selektiv wiederherzustellen. Das ist durchaus praktisch, hilft aber nur, wenn das gesuchte Bild im Backup enthalten war.

Eine echte Wiederherstellung gelöschter Dateien direkt aus dem freien Gerätespeicher (also ohne jegliches Backup) ist auf modernen Android-Geräten durch das Betriebssystem stark eingeschränkt und gelingt in der Praxis selten zuverlässig. Unser Rat: Bleiben Sie skeptisch, denn die Preise für solche Tools sind oft hoch und die Erfolgsaussichten gering.

So verlieren Sie künftig keine Whatsapp-Medien mehr

Der zuverlässigste Schutz vor Datenverlust ist und bleibt ein aktuelles Backup. Aktivieren Sie in Whatsapp unter Einstellungen → Chats → Chat-Backup die tägliche automatische Sicherung und stellen Sie sicher, dass Ihr Google- oder Apple-Account genug freien Speicher hat.

Zusätzlich empfiehlt es sich, die automatische Medienspeicherung aktiviert zu lassen, damit Fotos direkt in der Galerie landen und damit eine zweite Kopie außerhalb des Chats existiert. Bedenken Sie dabei nur, dass das den Speicher schnell füllen kann.

Weiterführender Lesetipp: 12 neue Whatsapp-Funktionen, die Sie ab sofort nutzen können

Anker hat im Frühjahr mit dem Soundcore Space 2 eine verbesserte Version seines großen Over-Ear-Kopfhörers in den Handel gebracht. Aktuell fährt der Hersteller bei Amazon eine Sonderaktion für das Gerät. So wurde der Preis für den Kopfhörer auf 109 Euro gesenkt und obendrauf bekommt man eine passende stoßfeste Transporttasche kostenlos dazu. Dafür müssen lediglich beide […]

The post Soundcore Space 2: Anker legt Transporttasche kostenlos dazu first appeared on ifun.de.

Release Date: July 20, 2026
Since v0.18.0: ~2,245 commits · ~1,065 merged PRs · ~2,465 files changed · ~300,000 insertions · ~36,000 deletions · ~3,300 issues closed · 450+ community contributors

The Quicksilver Release. Hermes is the messenger god, and this window we made him move like it. First-turn time-to-first-token dropped ~80% on every platform, reasoning streams live by default, the desktop app got a ~20-PR speed overhaul (14× faster streaming markdown, virtualized diffs, snappy session switching), and the TUI renders markdown incrementally. Around that speed spine: you can now manage your Nous subscription without leaving the terminal, plug Bitwarden and 1Password straight into Hermes, let smart approvals judge flagged commands for you by default, watch your subagents work live, and trust that a finished response survives a gateway crash thanks to a durable delivery ledger. This release also rolls up everything from the v0.18.1 and v0.18.2 infrastructure patch tags — those windows are fully documented here.

✨ Highlights

• Hermes got dramatically faster — first token in a fraction of the time — Cold-start "Initializing agent..." used to eat ~4.3 seconds before your first turn even reached the model; it's now ~0.9s, an ~80% cut that applies to the CLI, gateway, TUI, desktop, and cron alike. Round 2 attacked what you see while waiting: reasoning models now stream their thinking live by default (no more staring at a spinner for 30 seconds), and the response box paints per token instead of per line. If Hermes ever felt like it took a deep breath before answering, that breath is gone. (#59332, #59389 — @teknium1)

• The desktop app speed wave — 20+ targeted perf PRs — Long replies used to cost 14× more CPU in the markdown splitter than they do now; giant diffs froze the review pane until we virtualized it; switching sessions thrashes layout no more. Streaming no longer re-renders the sidebar and every tool row per token, profile backends pre-warm on hover intent, and boot-hidden panes mount at idle instead of on the cold-start critical path. The net effect: the desktop app feels like a native app under load, even with huge transcripts and busy agents. (#67154, #67818, #65898, #66033, #66747, #67742 and more — @OutThisLife)

• Manage your Nous plan from the terminal — /subscription and /topup — Changing your subscription used to mean a trip to the billing website. Now /subscription opens a full flow right in the TUI or classic CLI: see your plan and remaining allowance, preview exactly what an upgrade costs ("Pay $46.30 & upgrade now") or when a downgrade takes effect, and apply it — with scheduled-change banners and undo. The desktop app got a matching billing settings tab. Your wallet never has to leave the keyboard. (#51639, #61054, #61067 — @alt-glitch)

• Smart approvals are now the default — When Hermes wants to run a flagged command, an LLM reviewer now assesses it independently instead of asking you to approve every single one — and each verdict covers only that exact command, so a later command matching the same pattern gets its own review. Combined with the new user-defined deny rules (which block commands even under yolo mode) and /deny <reason> (which tells the agent why you refused so it course-corrects), day-to-day approval fatigue drops sharply without giving up control. (#62661, #59164, #54518 — @teknium1)

• Plug your password manager into Hermes — Bitwarden & 1Password secret sources — API keys no longer have to live in a plaintext .env. A new pluggable SecretSource interface lets Hermes fetch secrets from Bitwarden and 1Password (op:// references) at load time, with multiple vaults enabled simultaneously, deterministic precedence, conflict warnings, and per-variable provenance. This consolidated eleven competing community PRs into one orchestrated interface — future vault providers drop in as plugins. (#59498 — @teknium1, 1Password provider salvaged from @hwrdprkns)

• Watch your subagents work — live transcripts + durable background delegation — delegate_task dispatches now return live transcript files you can tail -f the moment the subagents launch: every tool call, result, and streamed reply, one human-readable log per child. And background delegation completions are now durable — if the process restarts mid-run, results are restored and delivered through an ownership-checked ledger instead of vanishing. Fan out a fleet, watch any worker live, and never lose the results. (#67479, #63494 — @teknium1)

• A finished answer can no longer be lost — the delivery-obligation ledger — If the gateway died between generating your response and confirming the platform actually delivered it, that answer used to be silently gone (and you'd paid for the turn). Final responses are now recorded in a durable ledger in state.db around the platform send and redelivered on the next boot — closing a P1 silent-loss window for Telegram, Discord, Slack, and every other channel. (#67181 — @teknium1)

• One gateway, many profiles — profile-based message routing — A single multiplexed gateway sharing one bot token can now route specific guilds, channels, or threads to different profiles — each with fully isolated config, skills, memory, and secrets. Point your work Discord server at the work profile and your hobby server at personal, from one bot. A second multiplex hardening wave means one misconfigured profile can no longer take down the whole gateway. (#64835 salvaging @Burgunthy, #65700, #60589 — @teknium1, @benbarclay + six salvaged contributors)

• New providers and the newest frontier models — Fireworks AI and DeepInfra land as first-class providers (Fireworks with cost estimation and a #2 slot in the provider picker), Upstage Solar joins via salvage, and the model catalogs picked up GPT-5.6 (Sol/Terra/Luna + Pro variants, wired end-to-end across every route), grok-4.5 (GA), moonshotai/kimi-k3, claude-fable-5 / claude-sonnet-5, and GA tencent/hy3 — plus LM Studio JIT model loading for local setups. (#62593, #63969, #61616 — @kshitijk4poor completing @rob-maron's #61578, #60887, #65913, #64541, #65472)

• Crank the thinking to max — new reasoning effort tiers and per-model control — Reasoning effort gained max and ultra levels (GPT-5.6 and Codex's top tiers), selectable everywhere from the CLI to the desktop, with sane clamping on providers with smaller scales. You can now also pin per-model reasoning-effort overrides in config, set per-slot effort in MoA presets (your advisors think hard, your synthesizer stays fast), and per-task effort for auxiliary models. Thinking depth is now a dial, not a global switch. (#62650, #64458, #64631, #64597 — @teknium1)

• Your sessions, your data — export everything — hermes sessions export now writes Markdown, Quarto, HTML, prompt-only, and even Hugging Face-ready trace formats, with the full filter surface (age, workspace, platform), an opt-in --redact secret-scrubbing pass, and compacted-session lineage stitched into one logical export. Pair with the new prune filters and bulk archive to keep your session store tidy. Your conversation history is a real dataset now, not a black box. (#60186 salvaging @web3blind, #60492, #60507, #59327 — @teknium1)

• Security hardening round — This window closed a long list of credential-surface gaps: Vertex credentials scoped away from subprocess env and through profile secret scopes, media/vision/image-gen local-file reads routed through one shared credential-read guard, a webhook body-size-cap sweep across every aiohttp server, bot-token redaction in Telegram transport errors, Fireworks token prefixes added to the redactor, six P1 browser/MEDIA/.env hardening PRs salvaged in one pass, and CI hardened against untrusted-ref interpolation. (#57660, #58709, #59215, #56582, #57842 — @teknium1, @srojk34, @kshitijk4poor, @jquesnelle)

⚡ Performance — the speed spine

First-turn latency (all platforms)

• ~80% TTFT cut — Discord capability detection off the critical path (token-keyed 24h disk cache + background refresh), Ollama probe skipped for known non-Ollama providers, agent-init blocking work removed; cold submit→dispatch ~4.3s → ~0.9s (#59332 — @teknium1)
• Perceived-latency round 2 — display.show_reasoning default ON (watch the model think instead of a spinner), per-token response-box painting with width-aware force-flush, prompt-build caching, mtime-cached timezone resolution (#59389 — @teknium1)
• Segment mixed tool batches to recover lost concurrency; drop per-call base64 re-serialization from request-size estimates (#64460, #67788 — @teknium1, @OutThisLife)

Desktop speed wave

• 14× less splitter CPU via incremental block lexing for streaming markdown; virtualized review-pane diffs (no more full-Shiki freeze); snappy session switching on large transcripts; killed the layout-thrash cascade on session switch (#67154, #67818, #65898, #66033 — @OutThisLife)
• Cut startup serialization + per-turn REST amplification; pre-warm profile backends and gateway sockets on hover intent; idle-mount boot-hidden panes; fast model picker + dialogs (#66747, #66347, #67857, #66470 — @OutThisLife)
• Stop per-token sidebar + tool-row re-renders during streaming; stop eager JSON.stringify of every tool's args/result; scope tool-diff subscriptions; batch sidebar session slices into one profile-DB pass; targeted file-tree revalidation; rAF-coalesced sash resizes (#67742, #67842, #67195, #67245, #67824, #67838, #67844 — @OutThisLife)
• Systematized perf benchmark harness with trustworthy cold-start + first-token measurement, replacing 12 one-off scripts (#67466, #67697 — @OutThisLife)

Everywhere else

• TUI renders streamed markdown incrementally per block (#67236 — @OutThisLife)
• Skill discovery cached by scan signature; snapshot manifest builds ~5× faster; text prefilter before AST parse in tool discovery (#61414, #61131, #63941 — @kshitijk4poor, @ethernet8023)
• Copy-on-write message prep instead of full deepcopy; model-metadata probe-cache cluster; gateway session.resume model + display history from one SELECT (#61133, #61368, #67247 — @kshitijk4poor, @OutThisLife)
• hermes update skips npm install when Node manifests are unchanged; dashboard session-list payloads trimmed + messages paginated (#61580, #60883 — @kshitijk4poor)
• Byte-stable gateway system prompts — pinned session-context render keeps the prompt cache alive across turns (#67403 — @kshitijk4poor)

🏗️ Core Agent & Architecture

Providers & models

• Fireworks AI provider with cost estimation + cached picker price columns, promoted to #2 in provider pickers (#62593, #65476, #65214 — @teknium1)
• DeepInfra hardened integration; Upstage Solar provider (#42231 salvage) (#63969, #64541 — @kshitijk4poor)
• GPT-5.6 (Sol/Terra/Luna + Pro) end-to-end — context lengths, native/Codex catalogs, pricing, compaction caps across every route (#61616 — @kshitijk4poor, building on @rob-maron)
• grok-4.5 (GA) catalog + reasoning allowlist; kimi-k3 on Nous Portal + OpenRouter (kimi-k2.x retired) + K3 discovery on the Kimi Coding endpoint; claude-fable-5 / claude-sonnet-5 / fugu-ultra curated; GA tencent/hy3 (#60887, #65913, #65922, #56617, #60943 — @teknium1)
• Catalog-labeled silent default (GLM-5.2) + bare-provider /model cost-safe routing; LM Studio JIT load mode; adaptive thinking for Kimi-family Anthropic endpoints (#64771, #65472, #67606 — @teknium1, @kshitijk4poor)
• GLM-5.2 native reasoning_effort controls; Gemini request-context improvements; extra HTTP headers for LLM API calls; per-client model routing on the API server (#58884, #61873 — @vishal-dharm, #57038, #57028 — @teknium1)
• Claude Sonnet 5 fully wired — curated lists, intro pricing, and metadata across every route (#67932 — @teknium1)
• Hide providers you don't use — enabled: false per-provider flag + excluded_providers config scrub unwanted providers from /model pickers and built-in resolution (#67971 — @teknium1)
• Bedrock catalog wave: real context-window probing from the live endpoint, 1M-context rows for current-gen Claude + Fable, geo-prefix parity, versioned profile-ID pricing, Opus 4.8/4.7 rows (#68007, #67977, #68005, #67976 — @teknium1)
• kimi-k3 rollout completed across Kimi-direct catalog surfaces with 1M context on canonical Kimi Coding endpoints (#68108 — @teknium1)
• Provider pickers: Qwen providers folded into one group row; collapsible provider groups in the desktop model picker; friendlier TUI model display grouping same-endpoint providers (#67758, #67904, #67908 — @teknium1)

Reasoning & MoA

• max + ultra effort levels across every surface and route (#62650 — @teknium1)
• Per-model reasoning_effort overrides via a unified resolution chokepoint; per-task auxiliary effort; per-slot MoA preset effort; session-scoped /reasoning in the CLI (#64458, #64597, #64631, #67946 — @teknium1)
• MoA: reference_max_tokens to cap advisor output and cut latency; per-preset fanout cadence (user_turn runs advisors once per user turn); stale presets surfaced without retries; half-filled preset saves rejected at the API boundary; aggregator resolves reasoning like an acting model (#56756, #57591, #64756 — @teknium1)

Delegation, approvals & the agent loop

• Live subagent transcripts + durable background completions (see Highlights) (#67479, #63494 — @teknium1)
• Smart approvals default; user-defined deny rules (block even under yolo); /deny <reason> relays the denial reason; plugin pre_tool_call approve action escalates to a human gate (re-landed with rule keys) (#62661, #59164, #54518, #60504 — @teknium1, @kshitijk4poor)
• Unified delegation concurrency caps (max_async_children deprecated); explain long provider waits on the live status line; deterministic tool-output risk exposure (#56955, #64775, #61793 — @teknium1)
• Codex: live TUI/desktop tool cards for the app-server runtime, commentary streamed as visible interim messages, compaction routed through thread/compact/start, max-output truncation recovery, oversized message ids dropped on replay, banked usage-limit resets via /usage reset (#66514, #66115, #60114, #58155, #62225 — @teknium1, @kshitijk4poor, @JoaoMarcos44, #64280 — @teknium1)
• Hooks: oversized hook-injected context spills to disk (#20468 — @teknium1)
• Vibe reactions — floating hearts on affection across CLI/TUI/desktop, token-free core detection (#62016 — @OutThisLife)

Secrets & config

• Pluggable SecretSource interface + Bitwarden & 1Password providers (see Highlights) (#59498 — @teknium1, @hwrdprkns)
• hermes config get / unset; warn on unknown root config keys + doctor deprecated-key reporting; display.timestamp_format (#65540, #67370, #40622 — @teknium1)
• Auxiliary model usage recorded per task in session accounting; conversation-scoped Nous Portal usage tags across aux/MoA/delegate calls; --usage-file JSON report for hermes -z (#65537, #65468, #59615 — @teknium1)

Sessions & compression

• Sessions export: Markdown/QMD/HTML/prompt-only/trace formats, HF upload, --redact, unified filters; full prune filter surface + bulk archive; CLI workspace filter + restore-cwd-on-resume (#60186, #60492, #60507, #59327, #63091 — @teknium1, @web3blind)
• Compression: preserve human intent and durable handoffs; retain prompt cache when memory is unchanged; flatten multimodal content for the summarizer keeping image handles; gateway compression routing integrity (#67275, #67916, #65046, #56868 — @kshitijk4poor, @teknium1)
• Gateway session metadata consolidated into state.db; routing index moved to state.db (sessions.json now an optional legacy mirror); exact API bytes persisted in an api_content sidecar (#58899, #59203, #67274 — @teknium1, @kshitijk4poor)

🌐 Gateway, Fleet & Relay

• Durable delivery-obligation ledger for final responses (see Highlights) (#67181 — @teknium1)
• Profile-based routing for inbound messages + multiplex hardening wave 2 + GATEWAY_MULTIPLEX_PROFILES override (see Highlights) (#64835, #65700, #60589 — @teknium1, @benbarclay + salvaged contributors)
• Per-session turn lease + conversation-scope funnel; unified session reset boundaries (reset sessions stay reset); truthful runtime readiness checks; per-channel model and system prompt overrides; per-session /model overrides persist across restarts (#67401, #65783, #62645, #56967, #57030 — @teknium1)
• Session auto-reset default off; /sessions search <query>; webhook payload filters + route scripts; platform HTTP event callback routing; configurable long-running status phrases (#60194, #57685, #60944, #65702, #58872 — @teknium1)
• Relay: generic OIDC client-credentials provisioning (NAS-free), routed profile carried from the connector wire source, channel context consumed from the connector; Nous auth forensics + nous_session_valid on /api/status for hosted self-heal; Docker re-seeds a terminally-dead Nous bootstrap session on boot (#60730, #60586, #64649, #59976, #59969, #59983 — @benbarclay)

📱 Messaging Platforms

• Inline choice pickers for /reasoning and /fast on Telegram, Discord, and Matrix — one-tap native buttons instead of typing (#65799 — @teknium1)
• WhatsApp: native Baileys polls (clarify renders as a poll), locations, rich inbound metadata; dashboard pairing flow (#58865, #60571 — @teknium1)
• Discord: recover messages missed during reconnect; auto-created threads renamed to generated session titles; configurable interactive view timeout; opt-in owner mentions on exec-approval prompts; optional admin-only gate for approval buttons (#66149, #60187, #60230, #60493, #51751 — @teknium1)
• Slack: live per-tool status line (#67080 — @teknium1, salvaging #62007)
• Telegram: per-topic free-response allowlist; Google Chat clarify prompts rendered as cards (#65543, #65546 — @teknium1)
• Voice: stt.echo_transcripts toggle; MEDIA: captions attached to the media bubble on standalone sends; display.tool_progress: log option (#58859, #61415, #57014 — @teknium1, @kshitijk4poor)

🖥️ Hermes Desktop App

• Contribution-driven shell on a layout-tree model — panes, zones, and layouts as data; plugin-scoped i18n locale bundles followed (#60638, #67303 — @OutThisLife)
• Capabilities page — Skills/Tools/MCP + Hub in one place, with responsive overlay nav; CLI/dashboard parity for skills hub, MCP test/toggle/catalog, maintenance ops, log filters; five UX fixes from live testing (#57590, #57441, #67482 — @OutThisLife, @teknium1)
• Hermes Cloud connection mode (salvage of #55402); soft gateway switch + gateway-settings polish; terminal execution backend picker with health probes (#61912, #61916, #67203 — @OutThisLife, @teknium1)
• Keybind hint tooltips + keybinds settings tab + unified worktree dialog; base-branch picker for new worktrees; green unread dot for background-finished sessions; background-task sidebar indicators; grouped tool calls across text-less messages; auto-scrolling window for long tool-call runs (#65204, #62243, #65109, #65174, #61147, #57913 — @ethernet8023, @OutThisLife)
• Session + project color system (inherit from project, per-session override, shared across sidebar/tabs); unified active-project identity in chat status; workspace path status action (#67469, #67681, #67282, #63086 — @OutThisLife)
• Declarative memory-provider panel + full-config modal; config-defined TTS/STT providers + xAI TTS params; custom endpoint settings; per-job cron model picker; profile-aware approval mode control; UI scale setting; Ctrl/Cmd+wheel zoom; chat backdrop toggle; /journey opens the memory graph overlay (#67206 salvaging @erosika, #67209, #67759 — @austinpickett, #67472, #63520, #60457, #67029, #64598, #57267 — @teknium1, @OutThisLife)
• Full TypeScript conversion of the desktop tree (#57855 — @ethernet8023)