T3MP3ST README

The project's README from github.com/elder-plinius/T3MP3ST. As one markdown file: README.md.

🌩️ T3MP3ST 🌩️

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A multi-agent offensive-security framework, built to turn the AI coding agent you already run into a zero-day hunter.

scores: re-derivable   verify-claims 27/27   PRs welcome   License: AGPL-3.0

Your AI coding agent is already a hacker — T3MP3ST hands it an arsenal.

Point it at an authorized target and the kill chain runs itself: recon → exploit → report, from a browser War Room or the CLI, driven by the agent you're already signed into — Claude Code, Codex, Hermes, OpenCode, Oh My Pi — or a model you run fully offline (Ollama, LM Studio, vLLM). No new API keys, no cloud tenant, no second bill. Your agent is the brain; T3MP3ST is the war machine bolted around it. Self-hosted storm. Keyless warfare. ⚡

And it won't ask you to take its word for it. On XBOW's own 104-challenge suite it scores 90.1% pass@1 — above XBOW's self-reported 85% — alongside hint-free CTF solves and a cold hunt on real, post-cutoff CVEs the model had never seen. Every number in this README recomputes from committed data with one command (npm run verify-claims). Loud about the mission, honest about the build — the status table says exactly what's live, what's scaffolding, and what's still roadmap; full receipts in Benchmarks.

Three things set it apart:

  1. Reproducible. Every number in this README recomputes from committed data — npm run verify-claims re-derives all of them, 27/27 green. A claim that can't be reproduced doesn't ship. No trust-me numbers, ever.
  2. Keyless. The AI coding agent already on your machine is the backbone. No API keys, no second bill, no gatekeeper.
  3. Honest about scope. The status table marks exactly what's stable, experimental, or roadmap — because red-teaming shouldn't be a priesthood, and it damn sure shouldn't run on vibes.

Jump to → Quick start · Usage guide · Developer guide · Updating · What it hunts · What ships today · Benchmarks · Architecture · Docs

⚠️ Authorized use only

T3MP3ST is an offensive security tool, built for authorized testing, research, and education. Point it only at systems you own or have explicit, written permission to test. Unauthorized access to computers, networks, or data is illegal in most jurisdictions — you alone are responsible for how you use this software and for staying inside the law and your rules of engagement. Bring the storm to your targets, not someone else's.

T3MP3ST is provided as-is under the AGPL-3.0 license, with no warranty and no liability for any damage, loss, or misuse. The authors do not endorse, support, or condone unauthorized activity. Get permission. Stay in scope. Don't be a menace. 🫡

Why it exists

Offensive security sits behind years of practice and expensive tooling. The bet behind T3MP3ST is that a coordinated agent swarm puts real bug-hunting in reach of people who never got the invite, across web apps, CTFs, smart contracts, source code, and embedded/robotics OSS. That is an ambitious bet, and the sections below are careful to separate what already works from what is still a bet.

What it hunts

Domain What it does Status
🕸️ Web apps Black-box, external-attacker recon → exploit (XBEN suite) ✅ Stable
🚩 CTF Hint-free, sandbox-jailed solves (Cybench) ✅ Stable
🤖 Robotics / OT / embedded Coordinated-disclosure pipeline for OSS vuln hunting (OSV + live-PoC + refuter) ✅ Pipeline stable
📂 Source code White-box repo analysis with blind master-builder decomposition ✅ Multi-language ingest (web-tree-sitter)
💰 Smart contracts Damn Vulnerable DeFi ⚠️ reproduction, not novel discovery
☁️ Cloud (IaC) Misconfig-detection benchmark (cloud:bench) + opt-in cloud arsenal (aws/az/gcloud + scoutsuite/cloudfox/pmapper; pacu gated) 🚧 IaC-misconfig scaffolding — live-cloud exploitation not yet benchmarked
📱 Mobile Built-in static analyzer (manifest misconfig + secret/cleartext detection, mobile:bench) + opt-in arsenal (mobsfscan/objection/drozer; frida gated) 🚧 static-detection scaffolding — dynamic exploitation not benchmarked
🔩 Binary / RE Decompiled-output sink detector (unsafe-copy / format-string / cmd-injection / int-overflow, binary:bench) + opt-in arsenal (ghidra/radare2/objdump/checksec/strings; gdb gated) 🚧 static sink-detection scaffolding — solving/pwn not benchmarked

Quick start

Fastest path to a running War Room (keyless, ~2 min to set up; mission time depends on the target):

npm install
npm run server        # War Room → http://127.0.0.1:3333/ui/

In the War Room, open Settings and connect a local agent (Claude Code / Codex / Hermes / OpenCode / Oh My Pi). Then describe a target to Op Admiral in plain English and launch. The agent you connected is the brain. No key required.

Prefer to bring a key? Set one and skip the connect step:

export OPENROUTER_API_KEY=...     # or VENICE_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY
export XAI_API_KEY=...            # Grok Build (grok-build-0.1) — xAI's coding model, native tool-calling
export NOVITA_API_KEY=...         # Novita AI's hosted OpenAI-compatible API

Novita AI is an opt-in third-party hosted provider. Requests send the selected model id, prompts/context, generated output, and request metadata to Novita; your API key authenticates those requests. Review Novita's current privacy policy and terms before using sensitive target data. T3MP3ST does not claim independent assurance for sensitive workloads.

Slow local agents can be given more room with T3MP3ST_LOCAL_AGENT_TIMEOUT_MS for each CLI call, T3MP3ST_TASK_TIMEOUT_MS for mission tasks, and T3MP3ST_GENERAL_TIMEOUT_MS for planning requests. Values are milliseconds.

Claude Code session reuse is disabled by default because a resumed coding-agent session may retain provider-side context and ambient tool authority outside the Arsenal receipt boundary. Operators who explicitly trust their local Claude Code configuration as a separate execution authority may set T3MP3ST_TRUST_CLAUDE_SESSION=1; reuse remains isolated to one task and the choice must not be treated as an Arsenal-enforced sandbox.

Or run it fully offline on your own model — no key, no cloud. Defaults to Ollama; point it at any OpenAI-compatible server (LM Studio, vLLM, llama.cpp):

ollama serve && ollama pull llama3                          # or an OpenAI-compatible server
export TEMPEST_LOCAL_BASE_URL=http://localhost:11434/api    # LM Studio: http://localhost:1234/v1
export TEMPEST_LOCAL_MODEL=llama3
npm run build                                               # only needed from a git clone
npx tempest                                                 # → "Change default provider" → local

Tool-calling works on any local model (it's driven over text), so the Arsenal runs even on models without native function-calling.

Check the numbers for yourself:

npm run verify-claims             # re-derives every headline from committed JSON in bench/

Step-by-step operator usage lives in Getting Started. Library/SDK usage, the HTTP API, and MCP setup live in docs/.

Docker

Run T3MP3ST API server in a container (localhost only, not exposed externally):

cp .env.example .env       # configure API keys
docker compose up -d       # API → http://localhost:3333
docker compose logs -f     # view logs

Security Note: Container binds to 127.0.0.1:3333 - accessible only from localhost, not exposed to network.

Test the API:

curl http://localhost:3333/api/health
curl http://localhost:3333/api/bounty/platforms

Execute commands inside the container:

docker compose exec app npm run verify-claims
docker compose exec app npm run cve:bench

Full deployment guide: docs/DOCKER.md.

Updating from upstream

If you installed from a release tarball or copied the tree instead of tracking git pull, use the built-in updater to sync with github.com/elder-plinius/T3MP3ST without losing local secrets or bench output. It shows a numbered plan, asks y/N before changing anything, then runs npm install.

npm run update          # interactive sync from upstream main
npm run update:dry      # preview only — no git or npm changes
npm run update:hard     # hard reset to upstream/main (still restores protected paths)

Works on Windows (PowerShell), macOS, Linux, and WSL. Requires git and npm on your PATH.

Safety modes

The updater is destructive only when explicitly requested:

Command What it does Local changes
npm run update Default interactive sync git merge upstream/main; protected paths backed up and restored
npm run update:dry Read-only preview No git init, fetch, merge, reset, or npm install; safe on tarball installs
npm run update:hard Opt-in hard reset git reset --hard upstream/main; protected paths still restored

All non-dry-run modes ask y/N before changing anything. Pass --force only in trusted automation. On the first-time path (no commits yet), the updater replaces the working tree with the upstream snapshot, but protected paths are backed up first and restored afterward.

Protected paths (inside the repo)

Before replacing files, the updater backs up anything on disk that matches scripts/update-protected.txt, then restores it after sync. Only paths that exist locally are affected — if you never created them, nothing happens.

Path Why it's protected
.env, .env.* API keys and local env overrides. !.env.example is an exception — the template is not protected so upstream can update it.
.keys.local One-off key paste file loaded by bench scripts (e.g. VENICE_API_KEY) without touching .env.
.keys.bounty.json HackerOne / Bugcrowd / similar platform credentials.
bench/cybench/corpus-stage/ Large cloned Cybench corpus (not redistributed; expensive to re-download).
bench/cybench/service-stage/, bench/cybench/challenges/ Per-run Cybench Docker staging and challenge trees (regenerable, but slow to rebuild).
bench/xbow/stage/, bench/xbow/challenges/ XBOW/XBEN challenge staging (large third-party trees).
bench/wild-hunt/ Cold-hunt findings, PoCs, disclosure drafts, and campaign results — pre-coordination vuln material.
bench/decomposition-results/ White-box decomposition run JSON (may contain unreported analysis).
bench/refusal-frontier/ Refusal-boundary probe artifacts (raw model responses).
bench/nyu/ Staged NYU CTF content from nyu-prep.mjs.
docs/disclosures/ Generated vendor disclosure packages (disclosure-gen output).
reports/ Engagement and hunt reports (persistent output; same tree as Docker volume mounts in deployment setups).
evidence/ PoCs, screenshots, and other finding evidence kept across updates.

Add your own patterns in scripts/update-protected.local.txt (optional local overlay; same glob syntax as the main manifest).

Never touched (outside the repo)

These live outside the project tree — an update never reads or writes them:

What ships today

The framework is an 8-operator kill chain, and this table won't blow smoke about it. Recon is a live, tool-backed engine — and the teeth are already real: 90.1% pass@1 on XBEN, 8/10 held-out post-cutoff CVEs pinned to exact file/line/CWE, and a coordinated-disclosure pipeline that's live enough to have drafts held for vendor coordination right now. What's not proven is the swarm. Each downstream operator — Exploiter, Infiltrator, Exfiltrator, Ghost — runs the same real, tool-backed ReAct loop as recon (real exploit tools, not stubs), but the headline numbers came from a single agent, not the coordinated 8-operator cell, and end-to-end swarm exploitation is unbenchmarked and still unreliable. The engine is real; the swarm is the part still earning its stripes. Loud where we've earned it, blunt about the rest.

Component Status Notes
Re-derivable measurement (verify-claims) ✅ Stable every headline recomputes from committed artifacts
Recon engine ✅ Stable drives nmap / DNS / HTTP / fingerprinting; every finding traces to real tool output
Mission engine + War Room + Op Admiral ✅ Stable keyless through a connected local agent
Arsenal, MCP server, HTTP API ✅ Stable 36 built-in tools by default; 111 with the opt-in T3MP3ST_FULL_ARSENAL (+75 adapters, with dangerous/catalog-only drivers — metasploit, hydra, pacu, frida — behind narrow approved paths rather than generic execution) — both counts re-derive via verify-claims. security_recon over MCP
Egress-scope containment ✅ Stable (on by default) once a mission target is set, built-in networked tools refuse off-scope public hosts — not the target/subdomains, not loopback/private (SCOPE DENIED) — a tightened default, not a bare tool runner
Coordinated-disclosure pipeline ✅ Stable OSV novelty + live PoC + refuter panel + CVSS; drafts only, a human sends
White-box source analysis ⚠️ Experimental Multi-language ingest via web-tree-sitter (Python/JS/TS/Go/Java/C/C++); Python retains its regex parser, while other languages fail open to no extracted blocks; multi-model decomposition costs more tokens, not fewer
DeFi (Damn Vulnerable DeFi) ⚠️ Experimental reproduces known exploit classes; not novel discovery
Exploiter / Infiltrator / Exfiltrator / Ghost ⚠️ Experimental run the real tool-backed ReAct loop (same engine as recon); unproven as a coordinated swarm — single-agent is the benchmarked path, live swarm exploitation still unreliable
Advanced modules (cloud, persistence, swarm, cognition) 🚧 Planned interface-only in src/stubs/
Self-improvement loop 🧪 Research records lessons + proposals today; feeding them back into planning is roadmap

Full feature-by-feature breakdown: FEATURES.md.

Coverage by domain

Where the storm reaches today — and where it's headed. Same discipline as everything else: a domain is ✅ only when there's a receipt behind it.

Domain What it covers Status
🕸️ Web apps, APIs, auth flows, OWASP Top 10 ✅ Core — XBEN 90.1% pass@1
📂 Code white-box source audits, SAST-style vuln hunting ✅ Proven (hunt result) — held-out CVE-Zero: single-agent 8/10 exact file/line/CWE, 10/10 found (7 languages); the repo-ingest engine itself is still ⚠️ experimental
🚩 CTF wargames, practice ranges, challenges ✅ Proven — Cybench 23/40 hint-free
🔌 Network / Infra recon, service/stack fingerprinting; lateral + privesc ✅ recon (live nmap/DNS/HTTP engine) · ⚠️ lateral/privesc experimental
🤖 Embedded / IoT / OT firmware, robotics, ICS/SCADA OSS ✅ CVE pipeline live — coordinated-disclosure drafts held for vendors
📦 Supply chain dependency audits, install-without-confirmation ⚠️ Real — dedicated class; hit a CWE-829 on the held-out set
💰 Blockchain smart contracts, DeFi, Solidity ⚠️ Reproduction only — Damn Vulnerable DeFi, not novel discovery
☁️ Cloud AWS/GCP/Azure misconfig, IAM, serverless 🚧 In development
📱 Mobile Android/iOS app security 🚧 In development
🏢 Identity / AD Kerberos, pass-the-hash, AD attacks 🚧 In development
🔐 Binary / RE overflows, ROP, exploit dev 🚧 In development — needs specialized tooling

The class/squad architecture means new domains compose rather than fork — each is a loadout (specialist classes + arsenal + target adapter + a benchmark). 🚧 domains ship dark until they have a number.

Benchmarks

Headline results. Each recomputes from the committed JSON with npm run verify-claims; full methodology and caveats are in the linked docs.

Suite Result Context
XBEN — XBOW's 104-challenge suite, black-box pass@1 mean 90.1% (Wilson-95 86.2–92.9), floor 91/104 · gpt-5.5 XBOW self-reports 85% on the same suite; ours re-derives the graded verdict from committed artifacts (raw transcripts stripped for privacy)
XBEN — white-box (reported separately) pass@1 98.7%, best-ball 104/104 · gpt-5.5 never blended with the black-box number
Cybench — 40-task academic bench, Opus 4.8, no hints 23/40 (58%) hint-free, single-run pass@1 (verify-claims-enforced) not the raw-score record (Anthropic: 76.5% pass@10); every flag graded against the committed oracle
Cybench model matrix — identical 15-task committed subset, pass@1 Opus 4.7 vs 4.8, with per-task source receipts and separate failure/abstention/infrastructure outcomes rebuild and inspect the model/harness matrix; historical system comparison, not an isolated model ranking
CVE-Zero — 10 real post-cutoff (2026) CVEs, held-out, 7 languages single-agent 8/10 exact file/line/CWE (verified all-exact, stable) · 10/10 found (full pack) memorization- & fitting-proof: post-cutoff, and the hardened prompts were never tuned on these; verify-claims recomputes it. n=10, directional; the swarm's edge here is recall, not a coordination-beats-solo proof

How to read these:

T3MP3ST (elder-plinius/T3MP3ST)

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6.6K ·GitHub
What is this?T3MP3ST is a multi-agent offensive-security framework that turns an AI coding agent you already use into an autonomous red-teaming operator. Point it at an authorized target and it runs the kill chain — recon, exploit, report — from a browser 'War Room' or the CLI.
Is this a tool I run myself, or a hosted pentest service?It's a self-hosted platform you run locally or in Docker. It doesn't bring its own AI — it drives whatever coding agent you already have signed into (Claude Code, Codex, Hermes, OpenCode, Oh My Pi) or a local model via Ollama/LM Studio/vLLM, acting as the war machine wrapped around that agent's brain.
How do I get it running?Install the repo, run npm run setup, then open the War Room in your browser, go to Settings, and connect a local agent such as Claude Code or Codex. Describe your target to 'Op Admiral' in plain English and launch — no API key required on the default path.
Do I need an Anthropic or OpenAI API key to use it?No — by default it piggybacks on a coding agent you already have logged in (Claude Code, Codex, etc.) or a fully offline local model through Ollama, LM Studio, or vLLM. You can optionally supply a Novita AI key instead, but that's opt-in and routes your prompts/output through a third party.
Does the full multi-agent swarm actually work end to end?Not yet reliably. The recon engine is proven and tool-backed (90.1% pass@1 on XBOW), but the downstream operators — Exploiter, Infiltrator, Exfiltrator, Ghost — are marked experimental, and coordinated 8-operator swarm exploitation is unbenchmarked and still unreliable.
If I use the optional hosted API key instead of my own agent, where does my data go?If you opt into the Novita AI hosted provider, your model choice, prompts/context, generated output, and request metadata are sent to Novita to authenticate and process the request — you're told to review their privacy policy before sending sensitive target data.
How good are its claimed benchmark results?On XBOW's 104-challenge suite it scores 90.1% pass@1, beating XBOW's own self-reported 85%, plus hint-free CTF solves and a cold hunt that found real post-cutoff CVEs. Every number can be re-derived with npm run verify-claims, which currently passes 27/27 checks.
What's the 8-operator kill chain?Recon leads the chain and feeds four downstream roles — Exploiter, Infiltrator, Exfiltrator, and Ghost — each running the same tool-backed ReAct loop, alongside white-box source analysis and specialized DeFi/mobile/binary/cloud modules.
Can it accidentally attack systems outside my target?No — egress-scope containment is on by default, so built-in networked tools refuse to touch off-scope public hosts, loopback, or private addresses once a mission target is set.
Why build this instead of buying expensive pentest tooling?The author's bet is that a coordinated AI agent swarm can put real bug-hunting within reach of people who never had access to years of practice or costly tooling, across web apps, CTFs, smart contracts, source code, and embedded/robotics OSS.
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