PIArena: A Platform for Prompt Injection Evaluation

Runpeng Geng, Chenlong Yin, Yanting Wang, Ying Chen, Jinyuan Jia


Abstract
Prompt injection attacks pose serious security risks across a wide range of real-world applications. While receiving increasing attention, the community faces a critical gap: the lack of a unified platform for prompt injection evaluation. This makes it challenging to reliably compare defenses, understand their true robustness under diverse attacks, or assess how well they generalize across tasks and benchmarks. For instance, many defenses initially reported as effective were later found to exhibit limited robustness on diverse datasets and attacks. To bridge this gap, we introduce PIArena, a unified and extensible platform for prompt injection evaluation that enables users to easily integrate state-of-the-art attacks and defenses and evaluate them across a variety of existing and new benchmarks. We also design a dynamic strategy-based attack that adaptively optimizes injected prompts based on defense feedback. Through comprehensive evaluation using PIArena, we uncover critical limitations of state-of-the-art defenses: limited generalizability across tasks, vulnerability to adaptive attacks, and fundamental challenges when an injected task aligns with the target task. The code and datasets are available at https://github.com/sleeepeer/PIArena.
Anthology ID:
2026.acl-long.1533
Volume:
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Maria Liakata, Viviane P. Moreira, Jiajun Zhang, David Jurgens
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
33170–33192
Language:
URL:
https://preview.aclanthology.org/ingest-acl/2026.acl-long.1533/
DOI:
Bibkey:
Cite (ACL):
Runpeng Geng, Chenlong Yin, Yanting Wang, Ying Chen, and Jinyuan Jia. 2026. PIArena: A Platform for Prompt Injection Evaluation. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 33170–33192, San Diego, California, United States. Association for Computational Linguistics.
Cite (Informal):
PIArena: A Platform for Prompt Injection Evaluation (Geng et al., ACL 2026)
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https://preview.aclanthology.org/ingest-acl/2026.acl-long.1533.pdf
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