Prompt injection and jailbreak testing
Probe direct and indirect prompt injection paths, including RAG inputs and attacker-controlled context.
LLM and agent security assessment
Pentoma AI Red Teaming tests how your AI system behaves under adversarial pressure.
Pentoma AI Red Teaming is offensive testing for LLM, RAG, tool-using, and agentic systems. These products fail differently from traditional software — we focus on prompt injection, disclosure, tool misuse, and boundary failures using language buyers and engineers understand.
AI attack surface
AI security requires adversarial behavior testing.
Pentoma AI Red Teaming aligns with industry language around AI red teaming while keeping the output concrete: replayable prompts, observed behavior, impact, and remediation guidance.
Tool and agent boundary review
Test whether agents, tools, and plugins can be induced to exceed scope, leak data, or perform unsafe actions.
Disclosure and output handling
Evaluate sensitive information disclosure and unsafe downstream handling of model output.
Standards
Mapped to the language AI security teams already use.
Pentoma AI Red Teaming is designed around OWASP LLM Top 10 categories and practical evidence that product teams can reproduce.
OWASP LLM01 Prompt Injection
OWASP LLM02 Sensitive Information Disclosure
OWASP LLM05 Improper Output Handling
OWASP LLM07 System Prompt Leakage
OWASP LLM08 Vector and Embedding Weaknesses
OWASP LLM09 Misinformation and excessive agency patterns
Replayable prompts, observed behavior, and deterministic checks where possible
Make AI behavior visible before it ships.
Want the methodology in depth? Read how AI red teaming works.