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Red-Team Monitoring

  • Here the A.I. model can be continuously tested with hostile, manipulative, or boundary-pushing inputs (i.e., phishing-style questions, attempts to extract restricted data, false compliance claims) to identify weak points.

  • We can monitor whether the A.I. appropriately flags suspicious behavior, refuses harmful actions, and avoids being tricked into providing unauthorized information or taking prohibited steps.

  • Vulnerabilities are documented, as well as repeated failure types, hallucinations, tone drift, and/or manipulation risks. 

  • High-risk failures are converted into training examples, and we can update refusal rules, adjust system prompts, and refine safety guardrails so the model becomes more resilient against future adversarial attempts.

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