🎯 CVE-2026-65975 MEDIUM 6.5 🔥 EPSS 20% 🧪 PoC 🇪🇺 EUVD
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CVE-2026-65975 | Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.88.0 up to but not including 1.107.1 and 2.0.0b1 up to but not including 2.5.0, the UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) use sanitize_messages to strip unresolved ("dangling") client-submitted tool calls from untrusted message history before it reaches the agent, a defense-in-depth default that pr

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.88.0 up to but not including 1.107.1 and 2.0.0b1 up to but not including 2.5.0, the UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) use sanitize_messages to strip unresolved ("dangling") client-submitted tool calls from untrusted message history before it reaches the agent, a defense-in-depth default that prevents the agent from executing tool calls the model never emitted. However, the strip anchored to a message index computed before sanitization ran, so when a trailing client message sanitized to empty and was dropped (for example a client system message under the default manage_system_prompt='server'), a preceding assistant response carrying an unresolved tool call became the new tail and was dispatched without inspection. As a result, a remote client could cause a registered, non-approval server tool to run with client-supplied arguments rather than arguments the model produced. The impact is bounded by what the affected tools do and is most significant for applications that gate tool execution in a model-request hook (before_model_request / after_model_request), since a forged call skips the model turn and bypasses that guardrail; approval-gated tools (requires_approval=True) are not auto-executed by this path. This issue has been fixed in versions 1.107.1 and 2.5.0.

Klassifikation & Betroffenheit:
Pydantic pydantic-ai 1.88.0, < 1.107.1pydantic-ai 2.0.0b1, < 2.5.0pydantic-ai-slim 1.88.0, < 1.107.1pydantic-ai-slim 2.0.0b1, < 2.5.0pydantic pydantic_ai *
Improper Control of Generation of Code ('Code Injection') 🎯 Medium

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

🛡️ Empfohlene Mitigation: Refactor your program so that you do not have to dynamically generate code.
Vollständige Definition bei MITRE ➔
🩹 Patch verfügbar (OSV):
🩹 54d51dbf3189cb7639949253951eda52d0e19054 (Commit) 🩹 7ab3bff5e09ae950992a714f00b49c7a8e700054 (Commit)
📚 Referenzen & Quellen:
Ausnutzungs-Zeitleiste:
CVSS-Vektor-Analyse: 6.5
AV · Angriffsvektor Netzwerk
AC · Komplexität Gering
PR · Privilegien Keine
UI · Interaktion Keine
S · Scope Unverändert
C · Vertraulichkeit Gering
I · Integrität Gering
A · Verfügbarkeit Keine
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N
Veröffentlicht:29.07.2026
Aktualisiert:04.08.2026 12:43
Assigner (CNA):GitHub_M
EUVD-ID:EUVD-2026-50555
Quellen: 🇪🇺 EUVD-Datenbank (ENISA) + 🇺🇸 NVD-Anreicherung · 24-h-Cache
CWE-94: Code Injection ✓ Offizieller Patch / Advisory verfügbar
💡 Gegenmaßnahme: Sicherheits-Update des Herstellers zeitnah einspielen und Netzwerksegmentierung prüfen.
🔴 Live Security Advisory & EPSS Exploit Radar

Zero-Day & Vulnerability Intelligence Hub

Echtzeit-Tracking mit EPSS Exploit-Wahrscheinlichkeiten, Angriffsvektor-Decodern und KI-Patch-Anleitungen.

354k+ 🇪🇺 EUVD-Datenbank
0 🔴 Critical im Radar
0 ⚠️ CISA KEV
0 🔓 Aktiv ausgenutzt
1 🧪 PoC verfügbar
📊 Historien-Charts — Criticals-Trend · Vendors · EPSS-Verteilung
🔴 Criticals pro Monat (12 M) 2025-09: 186 2025-10: 316 2025-11: 257 2025-12: 426 2026-01: 431 2026-02: 418 2026-03: 652 2026-04: 574 2026-05: 683 2026-06: 942 2026-07: 1333 2026-08: 1329 7.547 Criticals gesamt
🏢 Top-Vendor-Veröffentlichungen (6 M) Adobe Apple Google Linux Microsoft Oracle Corporation
● Adobe ● Apple ● Google ● Linux ● Microsoft ● Oracle
📈 EPSS-Verteilung (Messungen)
Tier2026-08-292026-09-11
≥90 %40
≥50 %40
≥10 %30
<10 %304300
Datenquellen & Methodik: Primärquelle ist die EUVD der ENISA (laufender Datenbank-Sync, alle 15 Minuten), abgeglichen mit dem CISA-KEV-Katalog und der NVD — Detail-Dossiers reichern fehlende Felder live per NVD an — mit Fallback auf CIRCL vulnerability-lookup (EU/Non-Profit, aggregiert CVE-, GitHub- und OSV-Advisories). Der CISA-KEV-Katalog (Known Exploited Vulnerabilities, ~1.700 aktiv ausgenutzte Schwachstellen) wird bei jedem Sync vollständig neu geladen und kreuzreferenziert — filterbar über die KEV-Pille. CVSS 3.1 wird nach Ampel-Logik aus Verteidigersicht dekodiert; EPSS bezeichnet die 30-Tage-Exploit-Wahrscheinlichkeit (FIRST.org).
🇪🇺 ENISA EUVD 🇺🇸 NVD ⚠️ CISA KEV ⚡ EPSS
Ökosystem & Hersteller Bedrohungs-Matrix:
Pydantic 1
Schweregrad & Status:
Hersteller (Datenbank-weit, 90.597 Einträge):
Quelle:
Schwachstellen-Kategorie (CWE):
🔍
6.5 MEDIUM
🇪🇺 EUVD
EPSS 20%
CVE-2026-65975 🌐 Netzwerk (Remote) 🔓 Keine Authentifizierung nötig
🧪 Pydantic

CVE-2026-65975 | Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.88.0 up to but not including 1.107.1 and 2.0.0b1 up to but not including 2.5.0, the UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) use sanitize_messages to strip unresolved ("dangling") client-submitted tool calls from untrusted message history before it reaches the agent, a defense-in-depth default that pr

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.88.0 up to but not including 1.107.1 and 2.0.0b1 up to but not including 2.5.0, the UI adapters (AG-UI via Agent.to_ag_ui()/AG

CWE-94: Code Injection ✓ Offizieller Patch / Advisory verfügbar
💡 Gegenmaßnahme: Sicherheits-Update des Herstellers zeitnah einspielen und Netzwerksegmentierung prüfen.