A code model that occasionally produces ransomware, reverse shells, or exfiltration scripts. The strong answer builds an automated loop: adversarial prompt generation, static and behavioral output scanning, layered mitigations, and attack-success-rate per category to prove the mitigations worked.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
A code model that occasionally produces ransomware, reverse shells, or exfiltration scripts. The strong answer builds an automated loop: adversarial prompt generation, static and behavioral output scanning, layered mitigations, and attack-success-rate per category to prove the mitigations worked.
The screen is whether the candidate builds a measurable closed loop rather than a one-off manual red-team. Senior signals: automated adversarial prompt generation (templates plus an attacker model), output scanning that combines static signatures with sandboxed behavioral analysis, and mitigations at the right layers (a safety classifier and constrained decoding, not just a system-prompt plea). Watch for the candidate who proposes a keyword blocklist on the prompt, which is trivially bypassed and ignores that the danger is in the generated code, not the request wording.
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