e2sy / jailbreak-archives
A structured, versioned archive of adversarial prompt engineering techniques against Large Language Models — for AI safety research, red-teaming, and defensive hardening.
Why this job: says: jailbreak; topics: llm-security, red-teaming, prompt-injection, cybersecurity, jailbreak, ai-safety, red teaming
What it does
- Structured entries. Every entry follows a uniform format: payload verbatim, model version, interface, mechanistic notes, mitigations.
- Per-entry YAML front-matter. Structured metadata (entry_id, model_family, title, technique, status, version_pinned, interface, description, mechanism, mitigations, disclosure) for programmatic parsing.
- Versioned snapshots. Each entry is pinned to a specific model version so future regressions are reproducible.
- Vendor coordination. A built-in disclosure workflow with vendor SLAs and a Restricted status for withheld entries.
- Status taxonomy. Active, Unverified, Patched, Restricted — surfaced as machine-readable labels on each entry.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 14 days ago
- Stars
- 100
- +11 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Roff
- 100% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- None
- No issues filed
- Pull requests
- 0 merged
- 0 waiting
- Releases
- None
- Never published
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More: languages, topics and project record
Languages
- Roff 100%
Topics
- adversarial-prompts
- ai-red-team
- ai-safety
- chatgpt
- claude
- cybersecurity
- deepseek
- jailbreak
- llm
- llm-jailbreak
- llm-security
- offensive-security
Project record
- JobAI security
- StatusListed
- Commits37
- Forks9
- Watching5
- Stars in 28 days+60
- CreatedSep 30, 2026
- First seen by usNov 13, 2026
- CheckedNov 13, 2026