LongPIBench: A Long-Context Benchmark for Prompt Injection
Prompt injection attacks pose a serious security risk to large language models in real-world applications. However, existing prompt injection benchmarks primarily focus on short-context inputs, leaving the attacks and defenses in long-context settings largely unexplored. This gap leads to a substantial overestimation of the effectiveness of current defenses. In this paper, we bridge the gap by introducing LongPIBench, a long-context benchmark for prompt injection covering 4 realistic application scenarios: paper peer review, resume screening, code review, and email summary. For each scenario, we construct a synthetic dataset and a real-world dataset, with context lengths ranging from thou...
| Authors | Yupei Liu, Yuqi Jia, Neil Zhenqiang Gong et al. |
|---|---|
| Primary category | cs.CR |
| Published | 28 August 2026 |
| Last updated at source | 28 August 2026 |
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