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We built git blame for AI agents - here's how it works

Your team uses Claude Code, Cursor, or Gemini to write code. 60-80% of new commits are AI-generated. But when a bug appears - can you answer: which AI wrote this line? We built Origin to solve this. Here's how it works under the hood. …

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Your team uses Claude Code, Cursor, or Gemini to write code. 60-80% of new commits are AI-generated.



But when a bug appears - can you answer: which AI wrote this line?



We built Origin to solve this. Here's how it works under the hood.






The problem



Traditional git blame shows who committed code. But when your whole team uses AI agents, "who committed" is always the developer — even when Claude wrote 90% of the file.



You lose:



• which agent generated the code

• what prompt produced it

• what model was used

• what it cost





How Origin tracks it



Every time an AI agent starts a session, Origin hooks fire:




# Claude Code hooks (auto-installed via origin init)
origin hooks claude-code session-start
origin hooks claude-code user-prompt-submit
origin hooks claude-code stop






When a commit happens, Origin writes session data to git notes:




git notes show HEAD
# Origin-Session: abc123
# Agent: claude-code
# Model: claude-opus-4-6
# Cost: $2.40
# Prompts: 12









AI Blame



Now you can see who wrote every line:




origin blame src/api.ts

Line Tag Model Content
────────────────────────────────────────
1 [HU] import express from 'express'
2 [AI] claude-opus-4-6 const app = express()
3 [AI] claude-opus-4-6 app.use(express.json())
4 [HU] // my custom middleware









Retroactive attribution



Already have a repo with months of AI commits but no tracking?




origin backfill --apply






Origin analyzes commit message patterns, author emails, and code style to detect which commits were AI-generated — even without hooks.






Policy enforcement



Origin also enforces rules before commits land:




# Block commits containing secrets
# Block commits to restricted files
# Enforce budget limits per agent






Pre-commit hook fetches active policies from your Origin dashboard and blocks violations before they hit the repo.






Try it






npm i -g https://getorigin.io/cli/origin-cli-latest.tgz
origin init






Works with Claude Code, Cursor, Gemini CLI, Codex. Data stored in git notes — no server required for standalone mode.



Open source CLI: https://github.com/dolobanko/origin-cli

Team dashboard: https://getorigin.io

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
1 Warnungen
title: Detect Exploitation - We built git blame for AI agents - here's how it works
id: 5f77ad98-ae6f-4a4b-ade5-7cb41547b19e
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "We built git blame for AI agen" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("We built git blame for AI agents - heres")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*We built git blame for AI agents - heres*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "We built git blame for AI agents - heres"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich We built git blame for AI agents - here'.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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