Brendan Dolan-Gavitt's Research Home Page
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Note: This page is a (hopefully) temporary placeholder until I get around to making a proper lab page.
I am currently an Assistant Professor in the Computer Science and Engineering Department at the NYU Tandon School of Engineering. My research interests include program analysis, virtualization security, memory forensics, and embedded and cyber-physical systems. Currently, my research focuses on developing techniques to ease or automate the understanding of large, real-world software systems in order to develop novel defenses against attacks, typically by subjecting them to static and dynamic analyses that reveal hidden and undocumented assumptions about their design and behavior.
I received my PhD from Georgia Tech in August 2014, and my B.A. in Mathematics and Computer Science from Wesleyan University in 2006. I also spent two years working as an information security analyst and researcher for the MITRE Corporation.
If you need to get in touch privately, you can find my PGP key on KeyBase.
- Tianyu Gu, Siddharth Garg, and Brendan Dolan-Gavitt. BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain. Machine Learning and Computer Security Workshop (Colocated with NIPS), December 2017 [pdf] (Best Attack Paper) Press coverage: WIRED, The Register, The Independent, Quartz.
- Patrick Hulin, Andy Davis, Rahul Sridhar, Andrew Fasano, Cody Gallagher, Aaron Sedlacek, Tim Leek, and Brendan Dolan-Gavitt. AutoCTF: Creating Diverse Pwnables via Automated Bug Injection. USENIX Workshop on Offensive Technologies (WOOT), August 2017 [pdf]
- Brendan Dolan-Gavitt, Patrick Hulin, Engin Kirda, Tim Leek, Andrea Mambretti, Wil Robertson, Frederick Ulrich, Ryan Whelan. LAVA: Large-scale Automated Vulnerability Addition. Proceedings of the IEEE Symposium on Security and Privacy (Oakland), May 2016. [pdf] [slides]
- Brendan Dolan-Gavitt, Tim Leek, Josh Hodosh, and Wenke Lee. Tappan Zee (North) Bridge: Mining Memory Accesses for Introspection. Proceedings of the ACM Conference on Computer and Communications Security (CCS), November 2013. [pdf] [Slides: Keynote | PDF] [Presentation Audio] [BibTex]
- Brendan Dolan-Gavitt, Tim Leek, Michael Zhivich, Jonathon Giffin, and Wenke Lee. Virtuoso: Narrowing the Semantic Gap in Virtual Machine Introspection. Proceedings of the IEEE Symposium on Security and Privacy (Oakland), May 2011. [pdf] [Slides: Keynote | PDF | PDF with Notes] [BibTex]
- Brendan Dolan-Gavitt, Abhinav Srivasta, Patrick Traynor, and Jonathon Giffin. Robust Signatures for Kernel Data Structures. Proceedings of the ACM Conference on Computer and Communications Security (CCS), November 2009. [pdf] [slides] [BibTex]
- Brendan Dolan-Gavitt. The VAD tree: A process-eye view of physical memory. Digital Investigation, Volume 4, Supplement 1, September 2007, Pages 62-64. [pdf] [slides] [BibTex]
- Brendan Dolan-Gavitt. Forensic analysis of the Windows registry in memory. Digital Investigation, Volume 5, Supplement 1, September 2008, Pages S26-S32. [pdf] [slides] [BibTex]
- Brendan Dolan-Gavitt, Josh Hodosh, Patrick Hulin, Tim Leek, and Ryan Whelan. Repeatable Reverse Engineering for the Greater Good with PANDA. Technical Report: CUCS-023-14, October, 2014. [pdf]
- Brendan Dolan-Gavitt, Bryan Payne, and Wenke Lee. Leveraging Forensic Tools for Virtual Machine Introspection. Technical Report: GT-CS-11-05, May, 2011. [pdf]
- Brendan Dolan-Gavitt and Yacin Nadji. See No Evil: Evasions in Honeymonkey Systems. May 2010. [pdf]
- Brendan Dolan-Gavitt and Patrick Traynor. Using Kernel Type Graphs to Detect Dummy Structures. December 2008. [pdf]
- Dynamic Analysis Kung-Fu with PANDA
- Presented at RECON 2014 in Montreal. [ Video ] [ Slides ]
- PANDA: Platform for Architecture-Neutral Dynamic Analysis
- PANDA is the Platform for Architecture-Neutral Dynamic Analysis. It is a platform based on QEMU and LLVM 3.3 for performing dynamic software analysis, abstracting architecture-level details away with a clean plugin interface. Particularly notable features include Android platform emulation and support for deterministic record and replay. It is currently being developed in collaboration with MIT Lincoln Laboratory, Georgia Tech, and Northeastern University.
- Virtuoso is a system for automatically generating tools that can be used to introspect into virtual machines or extract information from memory images. It consists of a dynamic tracing system that records the execution of an in-guest program, and an analysis and translation component that converts the traces into a compact, out-of-guest program that computes the same result. More details can be found in our 2011 IEEE Security and Privacy paper.
- Virtual Address Descriptor Tools
- The VAD tools are a set of scripts for working with Virtual Address Descriptor structures in dumps of Windows physical memory to provide detailed information about a process's memory allocations to a forensic investigator. (Note: the functionality of these tools has now been implemented in Volatility, and their use is no longer recommended.)
- PDBparse is a GPL-licensed library for parsing Microsoft PDB files. Support for these is already available within Windows through the Debug Interface Access API, however, this interface is not usable on other operating systems. PDB files provide a way to access debugging information about programs compiled with Microsoft Visual Studio, and can enable interesting applications such as extracting the Windows kernel data structures or finding non-exported kernel global vairables, all without access to the source.
- Along with AAron Walters and several others, I help develop and maintain Volatility, an open-source (GPL-licensed) memory forensics framework. Volatility can do a lot of really cool things with memory images, from listing processes and threads, to viewing open network connections, to reconstructing executable files out of memory. I have also written some small extensions that allow it to interpret the memory of live virtual machines under Xen, using the XenAccess library.