Skip to content
Get packs

AI Agent Security

Adds defense-in-depth guardrails to AI agents against prompt injection, tool abuse and data leaks.

Source Download skill
Repository
sickn33/agentic-awesome-skills
Stars
49,023
Licence
MIT
Files
2 files

What it does

This skill teaches an AI agent how to help you design and review security controls for agentic AI systems, meaning AI that calls tools, reads documents and takes actions. It walks through a STRIDE threat model for agents and provides example Python code for screening inputs for prompt-injection patterns, blocking unsafe input before it reaches the model, and logging security events. It is docs-and-examples guidance: the skill itself does not protect anything by being installed, and its own text warns that the regex and classifier code is a partial sketch, not a working security boundary.

Great for

  • Developers building agents with frameworks such as LangChain, CrewAI or custom code who want a starting threat model and input-screening patterns
  • Security reviewers who need a checklist of agent-specific threats like tool abuse, cross-tenant leakage and privilege escalation
  • Teams writing design docs that must explain how approvals, tool permissions and audit logging will work

Skip it if

  • Production security on its own: the regex filters have false positives and negatives, and the skill states that prompt text cannot grant permissions, so real enforcement must live in server-side policy and tool services
  • Attacking or testing third-party systems: the compatibility note says active assessments need an authorized scope and the skill bundles no scanners or scripts
  • Non-developers looking for a turnkey tool: the content assumes Python, Docker, OpenTelemetry and a policy engine such as OPA or Cedar

Try asking

  • “Create a STRIDE threat model for my customer-support agent that can read orders and issue refunds”
  • “Review this Python input guard and tell me where prompt-injection filtering will fail”
  • “Design approval flow for an agent that sends emails so approvals are bound to the exact arguments”
  • “Outline audit logging and rate limits for a multi-tenant agent that uses a shared vector store”
Step-by-step guide: how to use AI Agent SecurityInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 2 original files, the MIT licence and an attribution note.

    ai-agent-security.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip ai-agent-security.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip ai-agent-security.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Treat the provided regex lists as examples to extend, and rely on server-side authorization, not input filtering, for real control
  • Ask the agent to produce tests for failure paths and concurrency, since the skill says these must be tested before production use
  • State your framework, tenancy model and tools up front so the agent tailors the threat model instead of giving generic advice

What's inside

  • references/details.md
  • SKILL.md

Redistributed unmodified from sickn33/agentic-awesome-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.