Policy Enforcement Point (PEP)

The PEP acts as a reverse proxy or interceptor, sitting directly in the critical path between the retrieval engine and the LLM. It is not merely an advisor; it physically blocks or filters the response. Unlike the Policy Decision Point (PDP) which makes the logical choice, the PEP executes the binary action:

• Intercepts the retrieval payload containing document chunks.
• Validates the integrity of the security context.
• Physically prevents unauthorized data from entering the prompt assembly window.

While pre-retrieval filtering restricts the search space, the PEP is the primary engine for post-retrieval filtering. It operates on the result set after the vector similarity search is complete:

• Re-ranking: Strips out documents that the user is not permitted to see based on real-time entitlements.
• Redaction: Applies pattern-matching to black out sensitive text spans (e.g., PII) before the model ingests them.
• Data Masking: Replaces sensitive values with realistic but fictitious tokens to preserve semantic structure without exposing raw data.

The PEP must operate with the end-user's identity, not the service account's. It relies on secure identity propagation to bind the original requester's context to the enforcement action:

• Extracts claims from forwarded JWT tokens or secure headers.
• Correlates the user's security principals (roles, attributes) against the metadata of the retrieved chunks.
• Ensures that the authorization decision is made in the context of the specific human or agent making the request, preventing privilege escalation.

Beyond access control, the PEP functions as a guardrail against indirect threats. It sanitizes the content flowing into the model to prevent prompt injection:

• Scans retrieved text for hidden instructions that could hijack the LLM's behavior.
• Strips markdown or code blocks that attempt to override system prompts.
• Enforces Data Loss Prevention (DLP) policies by inspecting the final assembled context for sensitive patterns before generation occurs.

As the final hop before the model, the PEP is the ideal point for audit logging. It captures the definitive record of what was actually sent to the LLM:

• Records the user identity, timestamp, and original query.
• Logs the specific chunk IDs and content that passed the enforcement filter.
• Creates an immutable trail for compliance and forensic analysis, proving exactly which data was exposed during the generation process.

A robust PEP supports continuous authorization, not just a one-time check. It can be configured to re-evaluate policies mid-session:

• Stateless mode: Enforces a decision once per retrieval call.
• Stateful mode: Monitors the user's risk profile (e.g., location change, device posture) and revokes access to the stream if the security context degrades.
• This aligns with Zero-Trust principles, ensuring trust is never assumed implicitly.