Researchers root prompt injection in models failing to separate prompts from context
jeremyakahn · x · 2026-09-18
AI safety researcher mmitchellai highlighted the root of a prompt injection risk on X: text a model generates about its own task gets re-ingested with the same authority as the developer's system prompt. She argues the minimal fix is provenance/privilege separation — model-written task text should be re-ingested as untrusted or less-trusted data.
jeremyakahn replied that this is exactly why prompt injection attacks work: models struggle to distinguish the prompt from other context. The exchange centers on trust-leveling of context as a concrete security design issue.
Related event: Researchers Debate Root Causes and Defenses for Prompt Injection(4 posts)→
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