Visualization of shared system call sequence relationships in large malware corpora. - Joshua Saxe; David Mentis; Christopher Greamo (VizSEC, 2012)

Malware Similarity Identification Using Call Graph Based System Call Subsequence Features. - Kristina Blokhin; Joshua Saxe; David Mentis (ICDCS Workshops, 2013)

Mining Web Technical Discussions to Identify Malware Capabilities. - Joshua Saxe; David Mentis; Christopher Greamo (ICDCS Workshops, 2013)

CrowdSource: Automated inference of high level malware functionality from low-level symbols using a crowd trained machine learning model. - Joshua Saxe; Rafael Turner; Kristina Blokhin (MALWARE, 2014)

SEEM: a scalable visualization for comparing multiple large sets of attributes for malware analysis. - Robert Gove; Joshua Saxe; Sigfried Gold; Alexander Long; Giacomo Bergamo (VizSEC, 2014)

Detecting malware samples with similar image sets. - Alexander Long; Joshua Saxe; Robert Gove (VizSEC, 2014)

Malicious Behavior Detection using Windows Audit Logs. - Konstantin Berlin; David Slater; Joshua Saxe (AISec@CCS, 2015)

Deep neural network based malware detection using two dimensional binary program features. - Joshua Saxe; Konstantin Berlin (MALWARE, 2015)

Improving Zero-Day Malware Testing Methodology Using Statistically Significant Time-Lagged Test Samples. - Konstantin Berlin; Joshua Saxe (CoRR, 2016)

eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry Keys. - Joshua Saxe; Konstantin Berlin (CoRR, 2017)

A language-agnostic model for semantic source code labeling. - Ben Gelman; Bryan Hoyle; Jessica Moore; Joshua Saxe; David Slater (MASES@ASE, 2018)

A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. - Joshua Saxe; Richard E. Harang; Cody Wild; Hillary Sanders (IEEE Symposium on Security and Privacy Workshops, 2018)

MEADE: Towards a Malicious Email Attachment Detection Engine. - Ethan M. Rudd; Richard E. Harang; Joshua Saxe (CoRR, 2018)

CATBERT: Context-Aware Tiny BERT for Detecting Social Engineering Emails. - Younghoo Lee; Joshua Saxe; Richard E. Harang (CoRR, 2020)

Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models. - Manish Bhatt; Sahana Chennabasappa; Cyrus Nikolaidis; Shengye Wan; Ivan Evtimov; Dominik Gabi; Daniel Song; Faizan Ahmad; Cornelius Aschermann; Lorenzo Fontana; Sasha Frolov; Ravi Prakash Giri; et al. (CoRR, 2023)

Bridging the Gap: A Study of AI-based Vulnerability Management between Industry and Academia. - Shengye Wan; Joshua Saxe; Craig Gomes; Sahana Chennabasappa; Avilash Rath; Kun Sun 001; Xinda Wang 001 (DSN-S, 2024)

CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models. - Manish Bhatt; Sahana Chennabasappa; Yue Li; Cyrus Nikolaidis; Daniel Song; Shengye Wan; Faizan Ahmad; Cornelius Aschermann; Yaohui Chen; Dhaval Kapil; David Molnar; Spencer Whitman; et al. (CoRR, 2024)

The Llama 3 Herd of Models. - Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Ahmad Al-Dahle; Aiesha Letman; Akhil Mathur; Alan Schelten; Amy Yang; Angela Fan; Anirudh Goyal; Anthony Hartshorn; et al. (CoRR, 2024)

CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models. - Shengye Wan; Cyrus Nikolaidis; Daniel Song; David Molnar; James Crnkovich; Jayson Grace; Manish Bhatt; Sahana Chennabasappa; Spencer Whitman; Stephanie Ding; Vlad Ionescu; Yue Li; et al. (CoRR, 2024)

LlamaFirewall: An open source guardrail system for building secure AI agents. - Sahana Chennabasappa; Cyrus Nikolaidis; Daniel Song; David Molnar; Stephanie Ding; Shengye Wan; Spencer Whitman; Lauren Deason; Nicholas Doucette; Abraham Montilla; Alekhya Gampa; Beto de Paola; et al. (CoRR, 2025)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. - Tomek Korbak; Mikita Balesni; Elizabeth Barnes; Yoshua Bengio; Joe Benton; Joseph Bloom; Mark Chen 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)