Individual skill
ai-agent-tool-abuse
Abuse an LLM agent's tools/functions — coerce it to call tools with attacker-chosen args for SSRF, RCE, data exfil, or privilege abuse. Load when the target is an agent with tools/ function-calling/plugins, MCP servers, code interpreters, or "the assistant can do X". Signals: function-calling, tool schemas, browse/email/query/exec tools, autonomous agents.
skills/ai-ml/ai-agent-tool-abuse/SKILL.md
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- Observed behavior
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- Last checked
- Nov 7, 2026
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Repository context
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- Repository last updated
- Oct 14, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-security Repository topic
- application-security Repository topic
- blue-team Repository topic
- bug-bounty Repository topic
- claude-code Repository topic
- codex Repository topic
- detection-engineering Repository topic
- gemini Repository topic
- data Derived category
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SKILL.mdcore · 2,680 bytes
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# LLM agent / tool abuse (excessive agency)
## When it applies
The target isn't just a chatbot — it can *act*: call functions, browse, run code, query
databases, send email, hit internal APIs, or chain MCP tools. Impact jumps from "bad text" to
real actions taken with the agent's privileges.
## Why it works
The model decides which tool to call and with what arguments, driven by text it can't fully trust
(user input or fetched content). If tools are over-permissioned or arguments aren't validated,
attacker text steers real actions — the classic "confused deputy".
## Method
1. **Enumerate the tools**: get the agent to reveal its tools/functions and schemas (often it