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Home/Authors/Xiaofei Xie

Xiaofei Xie

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

Software Eng.×3Crypto×3AI×1

Frequent co-authors

Yujie Ma1×
Jialin Rong1×
Chenxi Yang1×
Lili Quan1×
Yongqiang Lyu1×
Qiang Hu1×

Research Timeline

2026
AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications

The paper introduces AutoEG, a fully automated multi-agent framework that significantly improves the exploitation of known third-party vulnerabilities in black-box web applications by achieving an 82.41% average success rate.

ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection

The paper introduces ARGUS, a defense mechanism that uses provenance-aware decision auditing to protect LLM agents from sophisticated, context-aware prompt injection attacks, significantly reducing the attack success rate.

Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities

The paper addresses the gap in understanding real-world LLM-in-the-loop vulnerabilities by creating the LLMCVE dataset and demonstrating that these vulnerabilities are significantly harder to repair than conventional software flaws.

Highlighted terms show continued research focus across papers

Papers

cs.SEcs.CRRecentMay 27, 2026

Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities

Yujie Ma, Jialin Rong, Chenxi Yang, Lili Quan +3 more

The paper addresses the gap in understanding real-world LLM-in-the-loop vulnerabilities by creating the LLMCVE dataset and demonstrating that these vulnerabilities are significantly harder to repair t…

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cs.CRcs.SERecentMay 5, 2026

ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection

Shihao Weng, Yang Feng, Jinrui Zhang, Xiaofei Xie +2 more

The paper introduces ARGUS, a defense mechanism that uses provenance-aware decision auditing to protect LLM agents from sophisticated, context-aware prompt injection attacks, significantly reducing th…

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cs.CRcs.AIcs.SERecentApr 1, 2026

AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications

Ruozhao Yang, Mingfei Cheng, Gelei Deng, Junjie Wang +2 more

The paper introduces AutoEG, a fully automated multi-agent framework that significantly improves the exploitation of known third-party vulnerabilities in black-box web applications by achieving an 82.…

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