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cs.CR2026

Reveree: Diagnosing LLM Reverse-Engineering Agents

Hadjer Benkraouda, Hongyu Cai, Berkay Celik +1

Reverse engineering (RE) is critical to security tasks such as malware analysis and vulnerability discovery, and large language model (LLM) agents are increasingly able to perform…

cs.CR2026

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

Asif Shahriar, Hongyu Cai, Hadjer Benkraouda +2

Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs are susceptible to the same cog…

cs.CR2026

CoT-Guard: Small Models for Strong Monitoring

Nirav Diwan, Han Wang, Berkcan Kapusuzoglu +6

Monitoring the chain-of-thought (CoT) of reasoning models is a promising approach for detecting covert misbehavior (i.e., hidden objectives) in code generation tasks. While large m…

cs.CR2026

Beyond BeautifulSoup: Benchmarking LLM-Powered Web Scraping for Everyday Users

Arth Bhardwaj, Nirav Diwan, Gang Wang

Web scraping has historically required technical expertise in HTML parsing, session management, and authentication circumvention, which limited large-scale data extraction to skill…

cs.CR2025

PurpCode: Reasoning for Safer Code Generation

Jiawei Liu, Nirav Diwan, Zhe Wang +11

We introduce PurpCode, the first post-training recipe for training safe code reasoning models towards generating secure code and defending against malicious cyberactivities. PurpCo…