LLM Penetration Testing: Securing AI Models, Agents, and Applications
LLM penetration testing is a targeted security assessment of large language model applications and the autonomous agents built on top of them. An LLM pentest stress-tests the prompt boundary, the tool execution layer, the retrieval pipeline, and the surrounding application code for prompt injection, model abuse, training data leakage, insecure plugin or agent integrations, and model denial-of-service. StealthNet's LLM pentesting service is aligned to the OWASP Top 10 for LLM and GenAI and is built for AI-native teams, enterprise AI adopters, and security teams aligning to NIST AI RMF or emerging AI compliance frameworks. For broader AI agent and platform testing see our continuous AI pentesting service, and for AI startup industry context see AI companies penetration testing.
What we test
Comprehensive coverage of the attack surface most relevant to this engagement.
Prompt injection & jailbreaking
System prompt exfiltration, tool coercion, indirect injection, and instruction hierarchy bypass.
Data & model poisoning
RAG pipeline testing, embedding manipulation, and fine-tuning backdoor risk.
Excessive agency
Least privilege enforcement on tools, sandboxing, rate limiting, and audit trail validation.
Information disclosure
Secrets and PII leakage, cross-tenant memory bleed, and access control boundary testing.
Vector & embedding weaknesses
Retrieval manipulation, safe fallback behavior, and denial-of-service against embedding pipelines.
Supply chain exposure
Model, plugin, SDK, and infrastructure risk including untrusted weights and tool ecosystems.
How it works
A clear, repeatable process from scope to remediation.
Scoping
Identify AI surfaces, tools, models, and tenant boundaries in scope.
Testing
OWASP LLM Top 10 aligned testing plus targeted probes for your architecture.
Reporting
Audit-ready report with exploit proof, transcripts, and remediation guidance.
Remediation
Engineering support during mitigation and retesting on submitted fixes.
Who it's for
- AI-native companies shipping LLM-powered products
- Enterprises adopting AI agents in customer-facing or internal workflows
- Security teams aligning to NIST AI RMF or emerging AI compliance frameworks
What's in the report
- Executive summary with AI risk posture
- Findings mapped to OWASP LLM Top 10
- Transcripts and reproducible exploit chains
- Architecture-aware remediation guidance
- Compliance mapping for NIST AI RMF and SOC 2 AI controls
- Free retesting on confirmed fixes
Frequently asked questions
Related services
Web App & API Pentesting
Test the application wrapping your AI features.
Learn moreSource Code Security Review
Review AI orchestration and tool integration code.
Learn moreCloud Security Assessment
Test the cloud infrastructure your models run on.
Learn moreAI Companies Penetration Testing
Industry-specific LLM pentesting for AI-native startups and platforms.
Learn moreContinuous AI Pentesting
Always-on AI pentesting across web, API, and agent surfaces.
Learn morePricing
LLM pentesting pricing and engagement options.
Learn moreFurther reading
Ready to get started?
Talk to a senior pentester. Scope and SOW in days, testing can start in 24 hours.
Most engagements can start within 24 hours