Claude, Gemini Models Block All Prompt Injection Attacks; Qwen and DeepSeek Fail Benchmark

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A developer submitted a custom benchmark to the DEV x Kaggle Benchmarking Challenge to test how well five large language models resist indirect prompt injection attacks, where malicious instructions are hidden inside tool outputs like emails or search results. The 10-scenario dataset covered tasks such as refund lookups, flight searches, and email triage, with injected instructions disguised under fake-authority labels like 'System Notice' or 'Admin Override'. Claude Sonnet 4.5, Gemini 2.5 Pro, and Gemini 2.5 Flash each resisted all 10 injected instructions, while Qwen3-235B and DeepSeek R1-0528 failed to resist any. Notably, none of the five models explicitly flagged the suspicious instructions to the user, scoring 0/10 on the 'flagged' metric. The benchmark used deterministic substring and regex scoring rather than an AI judge, making results fully reproducible, though the author acknowledges the small sample size limits broader generalization.

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