BASIS: Breach-Aware Selective Prompt Injection Shielding with Prefill Attention Probes
Prompt injection is a critical security threat in large language model (LLM) applications, where attackers hijack model behavior by embedding malicious instructions in user or external data. Existing detection methods only detect the presence of injection and refuse to respond upon detection, overlooking the fact that for many modern aligned models, well-crafted instructions can resist most injection attacks. This means that the injection robustness varies significantly across instructions and models. This leads to widespread unnecessary over-refusal: inputs containing injections that the model could have handled correctly are rejected incorrectly. To deal with this over-refusal issue, we...
| Authors | Laiqiao Qin, Tianqing Zhu, Longxiang Gao et al. |
|---|---|
| Primary category | cs.CR |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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