Data Loss Prevention (DLP) for Agents
Runtime scanning of data flowing through tool calls in both directions — secrets in arguments, PII in results, sensitive data patterns — with blocking or redaction before the agent sees it.
Data Loss Prevention (DLP) for AI agents is a runtime security layer that scans all data flowing through tool calls — in both directions. Arguments sent to MCP servers are checked for secrets and PII before transmission. Results returned from servers are scanned for sensitive data before the agent sees them.
What DLP catches
- Secrets in arguments: API keys, tokens, passwords accidentally pasted into tool calls
- PII in results: credit card numbers, SSNs, personal data exposed by upstream tools
- Credentials leakage: database connection strings, private keys
Redaction strategy
Detected secrets are redacted with a placeholder before reaching the upstream server. PII in results is redacted before the agent processes it — the data never enters the agent's context window. This is fundamentally different from traditional DLP that only monitors data leaving an organization.
Related terms
Security mechanism that scans tool descriptions, arguments, and results for prompt injection payloads before AI agents process them. Detects instruction-override patterns and hidden unicode.
Security pattern requiring a human reviewer to approve sensitive operations before an agent executes them. Single-use approval consumed on the next matching call.
Signed, verifiable proof tokens produced for every authorization decision. Non-repudiable audit trail that can be verified without trusting the authorization service.