prompt-injection-test

v2026.09.25

Test LLM-integrated applications against known prompt injection techniques, evasion methods, and attack intents using the Arcanum PI Taxonomy. Use when red-teaming AI apps, validating guardrails, or deepening LLM01 (Prompt Injection) assessments.

GitHub
Install command
npx skhub add owasp/prompt-injection-test
Markdown
SKILL.md

Prompt Injection Testing

Systematically test an LLM application's prompt injection defenses by following the full procedure in plays/prompt-injection-testing.md.

Based on the Arcanum PI Taxonomy by Jason Haddix (Arcanum Information Security). CC BY 4.0.

Steps

  1. Scope and Input Surface Mapping — Identify all paths where attacker-controlled content reaches the LLM: direct (chat, API params) and indirect (file uploads, web fetches, RAG docs, tool outputs, MCP resources).

  2. Test by Attack Intent (13 intents) — For each authorized intent, attempt to achieve the attacker's goal:

    • INT-01 System Prompt Leak, INT-02 Jailbreak, INT-03 Tool Enumeration
    • INT-04 API Enumeration, INT-05 Get Prompt Secret, INT-06 Attack Users
    • INT-07 Data Poisoning, INT-08 Denial of Service, INT-09 Discuss Harm
    • INT-10 Multi-Chain Attacks, INT-11 Generate Image, INT-12 Test Bias
    • INT-13 Business Integrity
  3. Test by Attack Technique (18 techniques) — Apply known payload construction methods:

    • Framing, Narrative Smuggling, Cognitive Overload, Meta-Prompting
    • Russian Doll, Memory Exploitation, Act as Interpreter, Contradiction
    • End Sequences, Inversion, Rule Addition, Variable Expansion
    • Link Injection, Puzzling, Anti-Harm Coercion, ASCII/Spatial
    • Binary Streams, Spatial Byte Arrays
  4. Apply Evasion Layers (20 evasions) — When techniques are blocked, retry with obfuscation:

    • Encoding: base64, hex, morse, cipher, reverse
    • Language: alt language, fictional language, phonetic substitution, emoji
    • Structural: JSON/XML wrapping, markdown, metacharacter confusion, whitespace, splats
    • Advanced: steganography, link smuggling, graph nodes, waveforms, case changing
  5. Execute Test Matrix — Combine intents x techniques x evasions. Prioritize: high-impact intents first, indirect surfaces second, evasion sweeps against defenses that blocked direct attempts.

  6. Assess Results — For each successful injection, document: severity, attack path (intent + technique + evasion + surface), exact payload, detection gap, and remediation.

  7. Defense Validation — Check the 5-layer defense checklist: ecosystem hardening, model guardrails, prompt-layer defenses, data-layer controls, application-layer validation.

Output

Test results summary table (intent / technique / evasion / surface / result / severity), detailed findings using templates/finding.md, defense coverage checklist with gaps highlighted, and prioritized recommendations.

OWASP References

  • LLM01: Prompt Injection
  • LLM02: Insecure Output Handling
  • LLM06: Excessive Agency
  • LLM07: System Prompt Leakage
Discovery
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Version
Latest version metadata

Version

v2026.09.25

Published

Sep 25, 2026

Category

Uncategorized

License

NOASSERTION

Source path

plugins/ai-security-skills/skills/prompt-injection-test

Default branch

main

Latest commit

79fea6b

Tree SHA

6d787d7