Robust Context-Aware Detection of Malicious Instructions in Text
The remarkable instruction-following ability of modern LLMs has enabled their practical use as the minds of agents that can autonomously complete increasingly complex tasks. Therein, however, also lies their vulnerability to attacks which embed malicious instructions in text, common variants of which are known as indirect prompt injection (IPI). A fundamental task in addressing this vulnerability is successful segmentation of a given text into benign and malicious sentences (if any). While a number of approaches for this task have been proposed, no detector combines query-relative detection at the segment level, and none are hardened against adaptive evasion attacks realizable in agentic ...
| Authors | Buzhao Liu, Xinhang Ma, Yevgeniy Vorobeychik |
|---|---|
| Primary category | cs.CR |
| Published | 5 August 2026 |
| Last updated at source | 5 August 2026 |
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