Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
ArXivCSExplorer
☆☆Bookmarks🏆RSSHow to UseFAQ
Home/Authors/Michael J. Bommarito

Michael J. Bommarito

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

Crypto×3AI×3Software Eng.×2ML×1

Research Timeline

2026
Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

The paper introduces Symbolicate-Enrich-Sample, a low-cost pipeline that drastically reduces the search space of a whole operating system by prioritizing vulnerable functions, turning millions of potential targets into a manageable shortlist of candidates.

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

The paper introduces Symbolicate-Enrich-Sample, a pipeline that efficiently filters millions of functions in a Windows OS to create a highly prioritized, manageable shortlist of potential vulnerabilities.

MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments

MimeLens is a novel, position-agnostic BERT-style encoder that accurately detects file types from arbitrary binary fragments, outperforming existing methods like Magika, especially on non-standard inputs.

Highlighted terms show continued research focus across papers

Papers

cs.CRcs.AIcs.LGRecentJun 2, 2026

MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments

Michael J. Bommarito

MimeLens is a novel, position-agnostic BERT-style encoder that accurately detects file types from arbitrary binary fragments, outperforming existing methods like Magika, especially on non-standard inp…

View →
cs.CRcs.AIcs.SERecentMay 31, 2026

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

Michael J. Bommarito

The paper introduces Symbolicate-Enrich-Sample, a low-cost pipeline that drastically reduces the search space of a whole operating system by prioritizing vulnerable functions, turning millions of pote…

View →
cs.CRcs.AIcs.SERecentMay 31, 2026

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

Michael J. Bommarito

The paper introduces Symbolicate-Enrich-Sample, a pipeline that efficiently filters millions of functions in a Windows OS to create a highly prioritized, manageable shortlist of potential vulnerabilit…

View →