16 papers
Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware
Sadib Hassan Rumman, Md. Shariful Islam, Md Rayhanur Rahman
IoT firmware vulnerability detection is constrained by ecosystem heterogeneity, resource-limited platforms, and benchmark quality limitations. Existing datasets are often synthetic…
LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehicles
Md Wasiul Haque, Sagar Dasgupta, Mizanur Rahman +1
Autonomous vehicles depend on large safety-critical software stacks, where weaknesses reachable from adversarial inputs may affect steering, braking, or other control decisions. St…
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…
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…
From Natural Language to Verified Code: Toward AI Assisted Problem-to-Code Generation with Dafny-Based Formal Verification
Md Erfan, Md Kamal Hossain Chowdhury, Ahmed Ryan +1
Large Language Models (LLMs) show promise in automated software engineering, yet their guarantee of correctness is frequently undermined by erroneous or hallucinated code. To enfor…
Beyond Single Reports: Evaluating Automated ATT&CK Technique Extraction in Multi-Report Campaign Settings
Md Nazmul Haque, Sivana Hamer, Brandon Wroblewski +2
Large-scale cyberattacks, referred to as campaigns, are documented across multiple CTI reports from diverse sources, with some providing a high-level overview of attack techniques…
What Are Adversaries Doing? Automating Tactics, Techniques, and Procedures Extraction: A Systematic Review
Mahzabin Tamanna, Shaswata Mitra, Md Erfan +4
Adversaries continuously evolve their tactics, techniques, and procedures (TTPs) to achieve their objectives while evading detection, requiring defenders to continually update thei…
AgenticCyOps: Securing Multi-Agentic AI Integration in Enterprise Cyber Operations
Shaswata Mitra, Raj Patel, Sudip Mittal +2
Multi-agent systems (MAS) powered by LLMs promise adaptive, reasoning-driven enterprise workflows, yet granting agents autonomous control over tools, memory, and communication intr…
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…
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…
Relative Positioning Based Code Chunking Method For Rich Context Retrieval In Repository Level Code Completion Task With Code Language Model
Imranur Rahman, Md Rayhanur Rahman
Code completion can help developers improve efficiency and ease the development lifecycle. Although code completion is available in modern integrated development environments (IDEs…
Security Vulnerabilities in Software Supply Chain for Autonomous Vehicles
Md Wasiul Haque, Md Erfan, Sagar Dasgupta +2
The interest in autonomous vehicles (AVs) for critical missions, including transportation, rescue, surveillance, reconnaissance, and mapping, is growing rapidly due to their signif…
FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection
Shaswata Mitra, Subash Neupane, Martin Duclos +5
Signature-based Intrusion Detection Systems (IDS) detect malicious activity by matching network or host events against predefined rules. Security analysts manually develop these ru…