6 papers
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…
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…
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…
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…
MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts?
Muntasir Wahed, Xiaona Zhou, Kiet A. Nguyen +5
Recent advancements in Large Language Models (LLMs) have significantly enhanced their code generation capabilities. However, their robustness against adversarial misuse, particular…
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…