973 citations · 1.2k across the 17 of their papers we have counts for
12 papers · 1 filter
ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software
Xiang Mei, Jordi Del Castillo, Pulkit Singh Singaria +8
Achieving reproducibility, quantity, and diversity in vulnerability datasets has long been viewed as an inherent three-way trade-off, where improving one dimension often comes at t…
CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution
Minghao Shao, Haoran Xi, Nanda Rani +9
Large Language Model (LLM) agents can automate cybersecurity tasks and can adapt to the evolving cybersecurity landscape without re-engineering. While LLM agents have demonstrated…
ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software
Xiang Mei, Jordi Del Castillo, Pulkit Singh Singaria +8
Achieving reproducibility, quantity, and diversity in vulnerability datasets has long been viewed as an inherent three-way trade-off, where improving one dimension often comes at t…
NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security
Minghao Shao, Sofija Jancheska, Meet Udeshi +10
Large Language Models (LLMs) are being deployed across various domains today. However, their capacity to solve Capture the Flag (CTF) challenges in cybersecurity has not been thoro…
An Empirical Evaluation of LLMs for Solving Offensive Security Challenges
Minghao Shao, Boyuan Chen, Sofija Jancheska +4
Capture The Flag (CTF) challenges are puzzles related to computer security scenarios. With the advent of large language models (LLMs), more and more CTF participants are using LLMs…
(Security) Assertions by Large Language Models
Rahul Kande, Hammond Pearce, Benjamin Tan +4
The security of computer systems typically relies on a hardware root of trust. As vulnerabilities in hardware can have severe implications on a system, there is a need for techniqu…
Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants
Gustavo Sandoval, Hammond Pearce, Teo Nys +3
Large Language Models (LLMs) such as OpenAI Codex are increasingly being used as AI-based coding assistants. Understanding the impact of these tools on developers' code is paramoun…
Examining Zero-Shot Vulnerability Repair with Large Language Models
Hammond Pearce, Benjamin Tan, Baleegh Ahmad +2
Human developers can produce code with cybersecurity bugs. Can emerging 'smart' code completion tools help repair those bugs? In this work, we examine the use of large language mod…
Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions
Hammond Pearce, Baleegh Ahmad, Benjamin Tan +2
There is burgeoning interest in designing AI-based systems to assist humans in designing computing systems, including tools that automatically generate computer code. The most nota…
NNoculation: Catching BadNets in the Wild
Akshaj Kumar Veldanda, Kang Liu, Benjamin Tan +5
This paper proposes a novel two-stage defense (NNoculation) against backdoored neural networks (BadNets) that, repairs a BadNet both pre-deployment and online in response to backdo…
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg
Deep neural networks (DNNs) provide excellent performance across a wide range of classification tasks, but their training requires high computational resources and is often outsour…
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg
Deep learning-based techniques have achieved state-of-the-art performance on a wide variety of recognition and classification tasks. However, these networks are typically computati…