Unverified50% confidenceFactExact time
Large models lack a natural mechanism for distinguishing 'instruction source trustworthiness' when processing context, making it difficult to automatically identify which text constitutes authorized executable instructions and which is merely data content to be processed.
1
Sources
50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
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Related Claims
VerifiedBecause large models themselves cannot strictly distinguish between instructions and data, prompt injection is fundamentally very difficult to completely eliminate.80% similarUnverifiedBecause the decision paths of LLM reasoning are difficult to enumerate in advance, rule-based whitelist strategies are often insufficient, and detection systems also need semantic understanding and anomaly baseline modeling capabilities.75% similarUnverifiedRelying solely on keyword filtering or rule engines is insufficient to defend against prompt injection attacks, because attack payloads often disguise themselves as legitimate instructions at the semantic level, requiring a model with language understanding capabilities to effectively identify them.74% similarUnverifiedIndirect prompt injection is more dangerous than direct injection because agents often cannot distinguish between content to be processed and instructions to be followed.74% similar
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