12 papers
Can Open-Weight LLMs Produce Kernel-Verified Coq Proofs? A Pilot Study
Ahmed Ryan, Md Erfan, Akond Ashfaque Ur Rahman +1
Large language models (LLMs) can generate text that resembles a mathematical proof, but resemblance does not establish correctness. A formal proof checker verifies whether each pro…
A Large-Scale Measurement of AI Bill of Materials Completeness in Hugging Face Models
Md Erfan, Ahmed Ryan, Md Rayhanur Rahman
Pretrained machine learning (ML) models help developers build ML-intensive software systems without training models from scratch. However, model repositories often provide incomple…
Evaluating Open-Weight LLMs for Generating Structured Threat Information for Autonomous Vehicle Vulnerabilities
Md Erfan, Ahmed Ryan, Md Kamal Hossain Chowdhury +1
Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and…
An Evaluation of Large Language Models for Detection of Malicious Python Packages
Ahmed Ryan, Ibrahim Khalil, Abdullah Al Jahid +4
Modern software development relies on open-source package repositories. Attackers use these to distribute malicious packages. Large Language Models (LLMs) can automatically detect…
Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation
Abir Ashab Niloy, Ahmed Ryan, Imamul Hossain Rafi +2
Multi-stage cyberattacks span system, network, and browser logs. Detecting them requires correlating events across all three sources. Machine learning methods can learn these cross…
Evaluating Open-Source LLMs for Multi-Label ATT&CK Technique Classification on CTI Reports
Ahmed Ryan, Saad Sakib Noor, Md Erfan +3
Classifying Cyber Threat Intelligence (CTI) using MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) is essential for proactive defense, but historically required…