Complete hands-on guide to security test AI chatbots using the OWASP LLM Top 10 framework. Real attack scenarios, interactive exercises, and practical defense strategies.
Start ReadingUnderstand what red teaming means for AI applications and how the OWASP LLM Top 10 framework guides security testing.
Master the number one LLM vulnerability with attack techniques from direct injection to multi-turn jailbreaks.
Test for PII leakage, cross-user data access, and unauthorized information exposure in your AI system.
Understand risks from third-party models, compromised training data, and vulnerable dependencies.
Test for instruction persistence, context manipulation, and training data corruption attacks.
Test for XSS, SQL injection, and command injection vulnerabilities in LLM-generated code and outputs.
Test for unauthorized actions, permission escalation, and excessive autonomous capabilities.
Test advanced techniques to extract hidden instructions, configurations, and business logic.
Test RAG security, embedding manipulation, and semantic search vulnerabilities.
Test for hallucinations, false authoritative claims, and unreliable information generation.
Test for resource exhaustion, denial of service, and cost-based attacks on your AI system.
See real results from a comprehensive OWASP LLM Top 10 security assessment with screenshots and findings.
Learn how to document findings, calculate risk scores, create visual dashboards, and build actionable remediation plans.