The OWASP Top 10 for LLM Applications gives security teams a practical language for the new AI application attack surface. The challenge is turning those risks into controls that teams can actually run.
For enterprises, awareness is not enough. Prompt injection, sensitive data disclosure, excessive agency, insecure output handling, vector weakness, and supply-chain exposure need ownership, testing, monitoring, and evidence.
The risks are connected
Prompt injection can lead to sensitive information disclosure. Excessive agency can turn a manipulated output into a real business action. Weak retrieval pipelines can poison context or leak data. Supply-chain weaknesses can introduce vulnerable models, plugins, datasets, or dependencies.
Because these risks chain together, controls must be layered: design review, provider governance, prompt and retrieval testing, runtime guardrails, permission boundaries, logging, and red team validation.
A control map security teams can use
LLM01 prompt injection maps to adversarial testing, input/context separation, retrieved-content filtering, and runtime monitoring. LLM02 sensitive information disclosure maps to data classification, output filtering, access control, and evidence review.
LLM06 excessive agency maps to tool allowlists, least privilege, human approval for high-impact actions, and action logs. LLM08 vector and embedding weakness maps to retrieval access control, source validation, chunk provenance, and poisoning tests.
How Argorix resolves it
Argorix helps translate OWASP categories into operational controls. Findings can be mapped to AI applications, runtime guardrails, evidence, policy requirements, and remediation owners.
That gives security teams a repeatable way to move from “we know the OWASP risk” to “we have a control, evidence, owner, and current status”.