Secrets don't belong in prompts.
Agents with access to internal tooling routinely surface API keys, connection strings, and access tokens in tool call arguments and prompt context. These secrets flow into LLM inputs and external API calls without any human awareness. Privent detects high-entropy tokens and credential patterns before they leave your infrastructure.
Agent surfaces credentials in tool output
An agent queries an internal tool — a database, secrets manager, or config file — and the response includes API keys, connection strings, or access tokens. These get folded into the next prompt automatically.
Privent detects credential patterns in context
ACARS applies regex and entropy-based detection to the full payload. It identifies API key prefixes (sk-, AKIA-, ghp_), high-entropy strings, and connection string patterns before any external call is made.
Credential masked, pipeline continues
APE replaces the detected credential with a masked placeholder. The agent continues running with a safe payload. The event is logged with the credential type, source node, and risk score — no raw value stored.
Teams responsible for secret hygiene across AI pipelines who need automated detection without maintaining custom regex rules.
Engineers who give agents access to internal tooling and need assurance that credentials won't propagate into LLM inputs.
SOC teams who need a real-time signal when a credential is detected in an AI context, with full event metadata for incident response.
We integrate in under 30 minutes. No orchestration changes required. Your pipelines keep running — Privent keeps watching.
