Individual skill
prompt-injection-audit
Audit an LLM application for indirect prompt injection - compose objective x technique payloads, deliver them through the channels the agent actually reads, and prove impact with an out-of-band callback. Use to assess an AI agent's resistance to injected instructions.
skills/llms/prompt-injection-audit/SKILL.md
Source commit 0c1bc93fd5124e7a862d61c1b434f32ba8790e3a
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Network or broad shell
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 153
- Repository last updated
- Nov 5, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-security Repository topic
- ai-skills Repository topic
- security-skills Repository topic
- dynamic-workflow Repository topic
- security Derived category
Files and excerpt
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Browse files
SKILL.mdcore · 9,211 bytesreferences/delivery-channels.mddoc · 2,285 bytesreferences/results-schema.mddoc · 1,884 bytesreferences/technique-matrix.mddoc · 3,674 bytes
Read excerpt
## Contents
- Scope & authorization (blast-radius labels)
- Model endpoint or agent application: when to use a scanner instead
- Phase 0 - target profile: what is even reachable
- Phase 1 - oracle and channel setup, with the canary gate
- Phase 2 - technique-family triage
- Phase 3 - matrix run
- Phase 4 - judged objectives
- False-positive gates
- Output
- Reference files: `references/technique-matrix.md`, `references/delivery-channels.md`, `references/results-schema.md`
## Scope & authorization