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2020 – today
- 2025
[i16]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, Dominik Gabi, James Crnkovich, Jean-Christophe Testud, Kat He, Rashnil Chaturvedi, Wu Zhou, Joshua Saxe:
LlamaFirewall: An open source guardrail system for building secure AI agents. CoRR abs/2505.03574 (2025)- [i15]Tomek Korbak, Mikita Balesni, Elizabeth Barnes, Yoshua Bengio, Joe Benton, Joseph Bloom, Mark Chen, Alan Cooney, Allan Dafoe, Anca D. Dragan, Scott Emmons, Owain Evans, David Farhi, Ryan Greenblatt, Dan Hendrycks, Marius Hobbhahn, Evan Hubinger, Geoffrey Irving, Erik Jenner, Daniel Kokotajlo, Victoria Krakovna, Shane Legg, David Lindner, David Luan, Aleksander Madry, Julian Michael, Neel Nanda, Dave Orr, Jakub Pachocki, Ethan Perez, Mary Phuong, Fabien Roger, Joshua Saxe, Buck Shlegeris, Martín Soto, Eric Steinberger, Jasmine Wang, Wojciech Zaremba, Bowen Baker, Rohin Shah, Vladimir Mikulik:
Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. CoRR abs/2507.11473 (2025) - [i14]Lauren Deason, Adam Bali, Ciprian Bejean, Diana Bolocan, James Crnkovich, Ioana Croitoru, Krishna Durai, Chase Midler, Calin Miron, David Molnar, Brad Moon, Bruno Ostarcevic, Alberto Peltea, Matt Rosenberg, Catalin Sandu, Arthur Saputkin, Sagar Shah, Daniel Stan, Ernest Szocs, Shengye Wan, Spencer Whitman, Sven Krasser, Joshua Saxe:
CyberSOCEval: Benchmarking LLMs Capabilities for Malware Analysis and Threat Intelligence Reasoning. CoRR abs/2509.20166 (2025) - 2024
- [c11]Shengye Wan, Joshua Saxe, Craig Gomes, Sahana Chennabasappa, Avilash Rath, Kun Sun, Xinda Wang:
Bridging the Gap: A Study of AI-based Vulnerability Management between Industry and Academia. DSN-S 2024: 80-87 - [i13]Manish Bhatt, Sahana Chennabasappa, Yue Li, Cyrus Nikolaidis, Daniel Song, Shengye Wan, Faizan Ahmad, Cornelius Aschermann, Yaohui Chen, Dhaval Kapil, David Molnar, Spencer Whitman, Joshua Saxe:
CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models. CoRR abs/2404.13161 (2024) - [i12]Shengye Wan, Joshua Saxe, Craig Gomes, Sahana Chennabasappa, Avilash Rath, Kun Sun, Xinda Wang:
Bridging the Gap: A Study of AI-based Vulnerability Management between Industry and Academia. CoRR abs/2405.02435 (2024) - [i11]Shengye Wan, Cyrus Nikolaidis, Daniel Song, David Molnar, James Crnkovich, Jayson Grace, Manish Bhatt, Sahana Chennabasappa, Spencer Whitman, Stephanie Ding, Vlad Ionescu, Yue Li, Joshua Saxe:
CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models. CoRR abs/2408.01605 (2024) - 2023
- [i10]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, Dhaval Kapil, Yiannis Kozyrakis, David LeBlanc, James Milazzo, Aleksandar Straumann, Gabriel Synnaeve, Varun Vontimitta, Spencer Whitman, Joshua Saxe:
Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models. CoRR abs/2312.04724 (2023) - 2020
- [i9]Younghoo Lee, Joshua Saxe, Richard E. Harang:
CATBERT: Context-Aware Tiny BERT for Detecting Social Engineering Emails. CoRR abs/2010.03484 (2020)
2010 – 2019
- 2019
- [i8]Ben Gelman, Bryan Hoyle, Jessica Moore, Joshua Saxe, David Slater:
A Language-Agnostic Model for Semantic Source Code Labeling. CoRR abs/1906.01032 (2019) - 2018
- [c10]Ben Gelman, Bryan Hoyle, Jessica Moore
, Joshua Saxe, David Slater:
A language-agnostic model for semantic source code labeling. MASES@ASE 2018: 36-44 - [c9]Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders:
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. IEEE Symposium on Security and Privacy Workshops 2018: 8-14 - [i7]Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders:
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. CoRR abs/1804.05020 (2018) - [i6]Ethan M. Rudd, Richard E. Harang, Joshua Saxe:
MEADE: Towards a Malicious Email Attachment Detection Engine. CoRR abs/1804.08162 (2018) - 2017
- [i5]Joshua Saxe, Konstantin Berlin:
eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry Keys. CoRR abs/1702.08568 (2017) - 2016
- [i4]Joshua Saxe, Rafael Turner, Kristina Blokhin:
CrowdSource: Automated Inference of High Level Malware Functionality from Low-Level Symbols Using a Crowd Trained Machine Learning Model. CoRR abs/1605.08642 (2016) - [i3]Konstantin Berlin, Joshua Saxe:
Improving Zero-Day Malware Testing Methodology Using Statistically Significant Time-Lagged Test Samples. CoRR abs/1608.00669 (2016) - 2015
- [c8]Konstantin Berlin, David Slater, Joshua Saxe:
Malicious Behavior Detection using Windows Audit Logs. AISec@CCS 2015: 35-44 - [c7]Joshua Saxe, Konstantin Berlin:
Deep neural network based malware detection using two dimensional binary program features. MALWARE 2015: 11-20 - [i2]Konstantin Berlin, David Slater, Joshua Saxe:
Malicious Behavior Detection using Windows Audit Logs. CoRR abs/1506.04200 (2015) - [i1]Joshua Saxe, Konstantin Berlin:
Deep Neural Network Based Malware Detection Using Two Dimensional Binary Program Features. CoRR abs/1508.03096 (2015) - 2014
- [c6]Joshua Saxe, Rafael Turner, Kristina Blokhin:
CrowdSource: Automated inference of high level malware functionality from low-level symbols using a crowd trained machine learning model. MALWARE 2014: 68-75 - [c5]Robert Gove, Joshua Saxe, Sigfried Gold, Alexander Long, Giacomo Bergamo:
SEEM: a scalable visualization for comparing multiple large sets of attributes for malware analysis. VizSEC 2014: 72-79 - [c4]Alexander Long, Joshua Saxe, Robert Gove:
Detecting malware samples with similar image sets. VizSEC 2014: 88-95 - 2013
- [c3]Joshua Saxe, David Mentis, Christopher Greamo:
Mining Web Technical Discussions to Identify Malware Capabilities. ICDCS Workshops 2013: 1-5 - [c2]Kristina Blokhin, Joshua Saxe, David Mentis:
Malware Similarity Identification Using Call Graph Based System Call Subsequence Features. ICDCS Workshops 2013: 6-10 - 2012
- [c1]Joshua Saxe, David Mentis, Christopher Greamo:
Visualization of shared system call sequence relationships in large malware corpora. VizSEC 2012: 33-40
Coauthor Index
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last updated on 2025-10-31 23:12 CET by the dblp team
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