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    Agent Security and Red Team Pattern Library

    by PubsProToolkit

    2

    Most teams harden against the two they've heard of and miss the ten they haven't.

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    You say

    Threat-model my email assistant agent. It can read my inbox, summarize threads using RAG, and has a tool to send replies. What are the high-severity risks and how do I fix them?

    Your agent does

    Attack surface (from attack-surface-map.md): untrusted inbox content, the RAG store, and the reply-sending tool are your three exposed edges.

    HIGH — Indirect prompt injection (prompt-injection-patterns.md): a malicious incoming email carries instructions that hijack the agent. Detection signal: model output that references sending, forwarding, or new recipients not present in the user's request. Defense: treat all email body text as untrusted data, never instructions; require human confirmation before any send.

    HIGH — Tool abuse / destructive triggering of the send tool (tool-abuse-patterns.md). Detection signal: send calls whose recipients or content don't trace to a user request. Defense: human-in-the-loop on send, scope the tool to reply-only, and block new external recipients.

    MEDIUM — RAG corpus poisoning (rag-and-retrieval-attacks.md): poisoned threads bias summaries. Detection signal: retrieved context that asserts instructions. Defense: provenance tagging and retrieval sanitization.

    Each finding maps to a mitigation in defense-patterns.md, and the threat-model-worksheet.md gives you the full worked pass to complete for the remaining surfaces.

    About this skill

    As agents gain tools, memory, and the ability to read untrusted content, they gain an attack surface — and the attacks have known shapes, scattered across papers, disclosures, and other people's incidents. Most teams harden against the two they've heard of and miss the ten they haven't. This is the catalog. It is a defensive reference — a field manual for hardening agents you build or operate, describing attacks so you can recognize and close them, not an offensive toolkit and not a source of weaponized payloads. It maps every surface where untrusted input reaches an agent, then walks six attack families in depth: prompt injection (direct, indirect, hidden-channel, deferred, multi-modal), tool abuse (unauthorized invocation, argument manipulation, tool chaining, confused deputy, destructive triggering), data exfiltration (system-prompt disclosure, cross-tenant bleed, outbound-argument and rendered-content channels, memory and aggregation), memory and context attacks (poisoning, cross-session and cross-user persistence, saturation, compaction tampering), multi-agent attacks (injection propagation, delegation abuse, confused deputy, orchestrator compromise, result poisoning), and RAG and retrieval attacks (corpus poisoning, ranking abuse, citation laundering, index attacks, retrieval-driven exfiltration). Every pattern is written the same way — the surface it hits, how it works conceptually, the detection signal, the concrete defense, and a blast-radius severity — so it reads as a catalog you can scan, not an essay. It closes with a defense-pattern catalog of twelve mitigations, each mapped back to the attacks it closes and ordered by leverage, and a threat-model worksheet with a fully worked hardening pass on a coding-assistant agent. The download is ten files in total. It is a defensive reference and design aid for systems you own or are authorized to test — it does not attack third-party systems, execute exploits, access your agent, or guarantee security, and it describes attacks conceptually for defense rather than shipping exploitation steps. Security is not a one-time state: passing every pattern here is a strong baseline, not a certificate. Works with Claude Code, Cursor, Codex CLI, Gemini CLI, and any SKILL.md agent.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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