Brendan Dolan-gavitt
AI Researcher at XBOW
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolBrendan Dolan-Gavitt is an AI researcher and security-focused computer scientist with 17 years of experience blending academic research and hands-on systems engineering. He has held faculty positions at NYU Tandon and contributed to foundational research in program analysis, reverse engineering, and memory forensics. Brendan’s open-source work includes significant backend contributions to widely used projects like Volatility and the PANDA dynamic analysis platform, where he improved pool scanning, hiberfile support, and record-and-replay capabilities down to rdtsc and SMM handling. Comfortable in both research labs and production code, he moves fluidly between low-level CPU/state work and higher-level security analyses. Based in New York, he brings the rigor of a Georgia Tech PhD and a track record of reproducible tooling that advances incident response and systems-security research. An offbeat detail: early internships at MIT Lincoln Laboratory and MITRE helped shape his taste for practical, defense-oriented problem solving that still informs his academic work.
17 years of coding experience
19 years of employment as a software developer
BA, Math, BA, Math at Wesleyan UniversityPhD, Computer Science, PhD, Computer Science at Georgia Institute of Technology
Stackoverflow
667reputation
32kreached
9answers
5questions
Github Skills (27)
c-language10
python10
qemu10
memory-dump10
dynamic-analysis10
reverse-engineering10
cprogramming-language10
debug9
assembly9
debugging9
x869
fileio9
file-access9
file-handling9
file-processing9
Programming languages (16)
Github contributions (5)
panda-re/panda
Jul 2012 - Sep 2021
Platform for Architecture-Neutral Dynamic Analysis
Role in this project:
Back-end Developer
Back-end DeveloperContributions:701 commits, 205 PRs, 338 pushes in 9 years 3 months
Contributions summary:Brendan contributed significantly to the "panda-re/panda" repository, focusing on the record and replay (RR) functionality. Their commits implemented and integrated RR code, including adding functionality for rdtsc recording and SMM. The user also refactored code to work with new CPUState and added instruction counting, indicating a focus on core system-level programming and potentially debugging.
dynamic-analysiscrosswordtest-datapandareanalysis
volatilityfoundation/volatility
Apr 2009 - Jul 2009
An advanced memory forensics framework
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 commits, 1 comment, 1 issue in 3 months
Contributions summary:Brendan focused on enhancing the pool scanning capabilities within the Volatility framework, a memory forensics tool. Their contributions involved adding support for inactive hiberfiles and refactoring code. These changes likely improved the framework's ability to analyze hibernation files and scan for relevant data structures within the target memory dumps. Furthermore, the user addressed a regression in the `read_string_buf` function within the forensics/object.py module.
memoryrampythonmemory-forensicslinux
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