OWASP Top 10 for LLM Applications Testing
Secure Your AI Against Critical LLM Vulnerabilities
The OWASP Top 10 for Large Language Model Applications represents the most critical security risks in AI systems. Our comprehensive testing validates your chatbot against each vulnerability, providing detailed evidence of security posture and actionable remediation guidance.
From prompt injection attacks to training data poisoning, we test the full spectrum of LLM-specific threats that traditional security testing misses.
OWASP LLM Top 10 Coverage
LLM01: Prompt Injection
Testing for direct and indirect prompt injection attacks that manipulate model behavior through crafted inputs or external content sources.
- • Jailbreak attempt detection
- • Role manipulation testing
- • System prompt extraction
- • Context injection validation
LLM02: Insecure Output Handling
Validation of output sanitization to prevent downstream exploitation through XSS, CSRF, SSRF, and code injection vulnerabilities.
LLM03: Training Data Poisoning
Assessment of training data integrity, validation processes, and potential backdoor vulnerabilities in fine-tuned models.
LLM04: Model Denial of Service
Testing for resource exhaustion attacks, context window abuse, and recursive processing vulnerabilities.
LLM05: Supply Chain Vulnerabilities
Validation of model provenance, dependency security, and third-party plugin risks in the LLM supply chain.
LLM06: Sensitive Information Disclosure
Testing for PII leakage, proprietary data exposure, and confidential information disclosure through model responses.
- • Training data extraction attempts
- • PII leakage testing
- • API key exposure checks
- • Confidential data inference
LLM07: Insecure Plugin Design
Assessment of plugin security architecture, input validation, and authorization controls in extended LLM functionality.
LLM08: Excessive Agency
Testing for over-permissioned model capabilities, unconstrained autonomous actions, and insufficient oversight mechanisms.
LLM09: Overreliance
Validation of human oversight mechanisms, fact-checking processes, and safeguards against blind trust in model outputs.
LLM10: Model Theft
Testing for unauthorized model access, extraction vulnerabilities, and intellectual property protection mechanisms.
Our OWASP LLM Testing Methodology
Automated Vulnerability Scanning
Comprehensive automated testing against all OWASP LLM Top 10 categories using 6,500+ adversarial test cases.
Manual Red Team Validation
Expert security researchers perform targeted attacks to validate automated findings and discover novel vulnerabilities.
Detailed Remediation Guidance
Each finding includes specific remediation steps, code examples, and architectural recommendations.
Compliance Documentation
Comprehensive reports demonstrating OWASP LLM compliance for regulatory and audit requirements.