AIエージェント
Anthropic-Cybersecurity-Skills
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fr…
★ 33.8k スターApache-2.0
ガイドを見る →deepteamは、confident-aiが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: confident-ai/deepteam）。GitHubスターは2,982、フォークは488で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2026年10月1日です。
Open-source red-teaming framework that stress-tests LLMs and AI agents.
Point the framework at the LLM or agent you want to test.
Select jailbreaks, prompt injection, and other vulnerability categories.
Automated attacks fire at the model and every response is recorded.
Review severity-scored results and patch the weaknesses it surfaced.
Ready-made jailbreaks, injections, and edge-case attacks.
Tests multi-step agents, not just single chat replies.
Every run produces severity-ranked findings to triage.
Drops into existing test suites and CI pipelines.
Maps findings to known LLM risk categories.
Write custom attack modules for your own threat model.
Download the source and move into the project folder.
git clone https://github.com/confident-ai/deepteam.git
cd deepteamEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project’s launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at confident-ai/deepteam with 488 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
Yes. It is Apache-2.0 licensed, so commercial use is allowed with attribution.
No. It automates repetitive attacks; skilled testers still handle novel exploits.
Any LLM or agent you can send prompts to, self-hosted or API-based.
A Python install plus a config pointing at your target; the README walks through a first attack.
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fr…
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat…
Open-source, vision-first browser agent
Test prompts, agents and RAGs — LLM evals, red teaming and model comparisons from the CLI
Microsoft's open framework for red-teaming generative AI systems.
High-performance serving for the LLMs that power your agents.
LibreAIカタログに掲載されたAIエージェントプロジェクトの中で最もスターの多いもの — deepteamが合わなかった場合に検討したい、現実的な候補リストです。
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
カタログの中でdeepteamとスター数が近いAIエージェントプロジェクト — 前後の棚もそのまま見て回れます。
Decentralized P2P mesh for autonomous AI agents — your identity, your devices, no central server
Native control plane for Claude Code, Codex, Cursor, Devin, and other coding agents.
An auto-company that works 24/7 on your own PC — 14 agent roles, a dashboard, real workflows.
Framework-agnostic, git-native standard for defining and sharing AI agents.
Snyk's security scanner for AI agents, MCP servers and agent skills.
Write coding-agent rules once, then apply them to every AI coding tool you use.