AI Agents for Cybersecurity: A Guided Tour of a Repository with Tons of Resources and Examples
Omar Santos walks through his eight-part AI-agents-for-cybersecurity repository: LLM building blocks (LangChain, RAG), then security agents with LangGraph, CrewAI, DeepAgents and MCP servers (nmap, CISA KEV, Shodan), a hardening guide for six agentic frameworks, token-cost control for agents, and a spec for a supervisor-led, human-gated security-assessment harness. It covers concrete design lessons such as least-privilege subagents, staged response actions, single-use approvals bound to exact actions, kill switches, and mapping controls to the OWASP Top 10 for Agentic Applications. Also notes Project CodeGuard rules shipped for AI coding assistants.
Organisations named here
- Artificial Analysis Cyber Index
- CoSAI
- MITRE ATT&CK
- Omar Santos
Technologies named here
- AI-agents-for-cybersecurity repository
- OpenClaw
- OpenHands
- LangChain 1.x / LangGraph
- CrewAI
- Hermes
- deepagents
- MCP stacks with 10,000–25,000 schema tokens per call
- Exploit-DB search
- subfinder and nuclei
- CISA Known Exploited Vulnerabilities Catalog
- NVD API
- Chroma
- Ollama
- Part 6 frameworks
- Artificial Analysis Cyber Index
- MITRE ATT&CK
- PentestGPT, CyberSecEval 4
- LangChain
- Model Context Protocol
- Python
- Nmap
- Shodan
- CISA KEV
- Project CodeGuard
- OWASP Top 10 for Agentic Applications
- Foundry Security Spec
Techniques named here
- Indirect prompt injection
- Skill and plugin supply-chain attacks
- Persistent Memory Poisoning
- Command injection via crafted hostname
- Approval fatigue with fail-open defaults
- Exposed agent control surfaces
- Compaction summaries laundering prompt injection
- Shared cache leakage across tenants
- Agentic RAG
- Context quarantine via subagents
- Embedding clustering of CVEs
- Simulated attack-surface management
- Denial of wallet
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