prompt-injection

Test prompt injection vulnerabilities by mapping interaction surfaces in your LLM app code and invoking an assessment to see how attacker-controlled content influences model behavior across direct input and indirect RAG pipelines.

Indirect prompt injection in RAG pipelines happens when poisoned documents or external web content plant malicious instructions into retrieved context, manipulating the LLM's behavior during ingestion and generation processes.

Secure your LLM app against OWASP LLM01 attacks by evaluating defense postures including instruction hierarchy, output filtering, privilege separation, and continuous red-teaming to classify and mitigate identified vulnerabilities.

Yes, you can test multi-turn and tool-using LLM contexts for prompt injection by assessing how attacker-controlled content influences model behavior across complex interaction surfaces and external-content ingestion paths.

Yes, prompt injection testing classifies findings using MITRE ATLAS AML.T0051 categories and OWASP LLM01:2025 standards to produce a structured, severity-based report with defensive recommendations.

Automated prompt injection assessment requires mapping interaction surfaces and may not capture all multi-turn manipulation vectors, making continuous red-teaming and defense posture evaluation necessary for comprehensive security.