LLM Output Verification: Detecting Hallucinations and Injection in Production
One of the most overlooked attack surfaces in production LLM deployments is the output channel. Why Output Matters An LLM can produce harmful output through successful prompt injection, hallucination with con
One of the most overlooked attack surfaces in production LLM deployments is the output channel.
Why Output Matters
An LLM can produce harmful output through successful prompt injection, hallucination with consequences, or data exfiltration via response.
Three Layers of Output Validation
- Structural validation - define expected response schemas and reject deviations
- Content policy enforcement - scan for internal endpoints, credential patterns, and system prompt leakage
- Consistency checks - compare factual claims against trusted sources
Key Takeaways
- Schema-first approach: define what a legitimate response looks like
- Reject, don't sanitize: block failed validation entirely
- Log every validation failure as a signal
Full article: https://aisecurities.uk/posts/2026-06-29-output-verification/
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