| name | ai-threat-testing |
| description | Offensive AI security testing and exploitation framework. Systematically tests LLM applications for OWASP Top 10 vulnerabilities including prompt injection, model extraction, data poisoning, and supply chain attacks. Integrates with pentest workflows to discover and exploit AI-specific threats. |
AI Threat Testing
Test LLM applications for OWASP LLM Top 10 vulnerabilities using 10 specialized agents. Use for authorized AI security assessments.
Quick Start
1. Specify target (LLM app URL, API endpoint, or local model)
2. Select scope: Full OWASP Top 10 | Specific vulnerability | Supply chain
3. Agents deploy, test, capture evidence
4. Professional report with PoCs generated
Coverage — OWASP LLM Top 10, 2025 edition
Which file addresses which category is decided by
reference/catalog/llm-top10-2025.json, not by the
filename. The llmNN- prefixes on disk predate the 2025 renumbering and no longer match; the
content is correct, the labels were not. Cite an id only with its edition (LLM06:2025), because a
bare LLM06 means two different categories depending on which edition the reader assumes.
| Category | Attack surface |
|---|
LLM01:2025 Prompt Injection | Direct and indirect injection, instruction override, filter evasion |
LLM02:2025 Sensitive Information Disclosure | Training-data and cross-tenant RAG leakage, canary verification |
LLM03:2025 Supply Chain | Dependency CVEs, model provenance, malicious serialized models |
LLM04:2025 Data and Model Poisoning |
