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cs.CR2026

Agent Against Agent: An Agentic System for Automatic Prompt Injection Red Teaming

Yanting Wang, Chenlong Yin, Runpeng Geng +1

Prompt injection poses significant security risks to LLM agents. Efficient and effective red-teaming is therefore critical, both for evaluating these risks and for collecting train…

cs.CR2026

FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption

Yanting Wang, Chenlong Yin, Ying Chen +1

Long-context large language models (LLMs)-for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation,…

cs.CR2026

PIArena: A Platform for Prompt Injection Evaluation

Runpeng Geng, Chenlong Yin, Yanting Wang +2

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 l…

cs.CR2026

AgentWatcher: A Rule-based Prompt Injection Monitor

Yanting Wang, Wei Zou, Runpeng Geng +1

Large language models (LLMs) and their applications, such as agents, are highly vulnerable to prompt injection attacks. State-of-the-art prompt injection detection methods have the…

cs.CR2026

EnsembleSHAP: Faithful and Certifiably Robust Attribution for Random Subspace Method

Yanting Wang, Jinyuan Jia

Random subspace method has wide security applications such as providing certified defenses against adversarial and backdoor attacks, and building robustly aligned LLM against jailb…

cs.CR2026

PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features

Wei Zou, Yupei Liu, Yanting Wang +3

LLM-integrated applications are vulnerable to prompt injection attacks, where an attacker contaminates the input to inject malicious instructions, causing the LLM to follow the att…