3 citations · 8 across the 14 of their papers we have counts for
5 papers · 1 filter
Prompting the Priorities: A First Look at Evaluating LLMs for Vulnerability Triage and Prioritization
Osama Al Haddad, Muhammad Ikram, Ejaz Ahmed +1
Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models (LLMs) offer a potential aid by automating parts of the interpr…
RINSER: Accurate API Prediction Using Masked Language Models
Muhammad Ejaz Ahmed, Christopher Cody, Muhammad Ikram +5
Malware authors commonly use obfuscation to hide API identities in binary files, making analysis difficult and time-consuming for a human expert to understand the behavior and inte…
A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem
Sunday Oyinlola Ogundoyin, Muhammad Ikram, Hassan Jameel Asghar +2
Millions of users leverage generative pretrained transformer (GPT)-based language models developed by leading model providers for a wide range of tasks. To support enhanced user in…
Enhancing Malware Fingerprinting through Analysis of Evasive Techniques
Alsharif Abuadbba, Sean Lamont, Ejaz Ahmed +6
As malware detection evolves, attackers adopt sophisticated evasion tactics. Traditional file-level fingerprinting, such as cryptographic and fuzzy hashes, is often overlooked as a…
SpaLLM-Guard: Pairing SMS Spam Detection Using Open-source and Commercial LLMs
Muhammad Salman, Muhammad Ikram, Nardine Basta +1
The increasing threat of SMS spam, driven by evolving adversarial techniques and concept drift, calls for more robust and adaptive detection methods. In this paper, we evaluate the…