---------------- 🛠️ Tool =================== T3MP3ST is a multi-agent offensive security framework designed to transform AI coding agents into zero-day hunters. It does not introduce its own model or require separate infrastructure. Instead, it wraps around whichever AI coding agent is already running on the host machine (Claude Code, Codex, Hermes) and orchestrates a full kill chain: recon, exploit, report. Interaction happens through a web-based War Room interface or the command line. Architecture The framework uses an 8-operator swarm architecture. Each operator covers a different phase or capability in the offensive pipeline. The recon engine is described as live and tool-backed, meaning it already integrates with external tooling for discovery and enumeration. The exploit loop has been benchmarked against a formal challenge suite. The system is self-hosted and keyless. It uses whatever agent credentials you already authenticate with. No additional API keys, no separate billing, no cloud dependency. Benchmark Results On XBOW's XBEN benchmark (104 challenges), T3MP3ST achieved 90.1% pass@1. Every solve was graded against a committed flag oracle. The npm run verify-claims command recomputes all performance numbers from committed data. The current score is 24/24 green, meaning every claim in the README can be independently verified from the repository's own data. This reproducibility mechanism is worth emphasizing. In a space where AI security tools routinely ship with unverified or selectively reported numbers, a committed verification pipeline that any user can run is a meaningful design choice. It does not prove the tool works in all scenarios, but it does make the claims auditable. On a held-out test of 10 real CVEs disclosed in 2026, spanning 7 programming languages, a single agent pinned 8 out of 10 to the exact file, line, and CWE classification. The full operator pack surfaced all 10 CVEs. The authors explicitly note the small sample size (n=10) and describe the results as "directional" rather than definitive. They also state that both memorization and overfitting are off the table, since the CVEs were disclosed after the model's training cutoff. Design Principles Three stated principles. First, reproducible: every number recomputes from committed data. Claims that cannot be reproduced do not ship. Second, keyless: no additional API keys, no gatekeeper. Third, honest about scope: a status table marks exactly what is stable, experimental, or still on the roadmap. Practical Considerations Offensive tool under AGPL-3.0, authorized use only. Not all 8 operators are fully live. The small-n CVE results are promising but preliminary, as the authors acknowledge. 🔹 T3MP3ST #tool #offensive_security #AI_agent #zero_day 🔗 Source: https://github.com/elder-plinius/T3MP3ST