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cs.CR2026

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…

cs.CR2026

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…

cs.CR2026

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…

cs.CR2026

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…

cs.CR2025

Unveiling Malicious Logic: Towards a Statement-Level Taxonomy and Dataset for Securing Python Packages

Ahmed Ryan, Junaid Mansur Ifti, Md Erfan +2

The widespread adoption of open-source ecosystems enables developers to integrate third-party packages, but also exposes them to malicious packages crafted to execute harmful behav…