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

Lorenzo Cavallaro

3 indexed papers

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

Publications per year

3
26

Top categories

Crypto×3AI×1ML×1Software Eng.×1

Frequent co-authors

Alfredo Pesoli2×
Michele Armillotta1×
Nicolò Romandini1×
Rebecca Montanari1×
Herman Errico1×
Xinran Zheng1×

Research Timeline

2026
Veritas: A Semantically Grounded Agentic Framework for Memory Corruption Vulnerability Detection in Binaries

Veritas is a semantically grounded framework that detects memory corruption vulnerabilities in stripped binaries by combining static analysis, LLM-based reasoning, and runtime validation, achieving high recall and zero false positives on a curated benchmark.

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput

The paper argues that the near-term impact of LLM-assisted vulnerability discovery is not simply an increase in zero-day volume, but a critical bottleneck in defender remediation throughput, shifting the focus to validation and patching capacity.

Antaeus: Hunting Repository-Level Logic Vulnerabilities via Context-Grounded LLM Reasoning

Antaeus is a framework that uses repository-level code context to detect logic vulnerabilities using LLM reasoning, reducing calls, cost, and triage effort.

Highlighted terms show continued research focus across papers

Papers

cs.CREmpiricalRecentJul 1, 2026

Antaeus: Hunting Repository-Level Logic Vulnerabilities via Context-Grounded LLM Reasoning

Michele Armillotta, Nicolò Romandini, Rebecca Montanari, Lorenzo Cavallaro

Antaeus is a framework that uses repository-level code context to detect logic vulnerabilities using LLM reasoning, reducing calls, cost, and triage effort.

View →
cs.CRcs.AIcs.LGRecent
May 23, 2026

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput

Alfredo Pesoli, Herman Errico, Lorenzo Cavallaro

The paper argues that the near-term impact of LLM-assisted vulnerability discovery is not simply an increase in zero-day volume, but a critical bottleneck in defender remediation throughput, shifting…

View →
cs.SEcs.CRRecentMay 14, 2026

Veritas: A Semantically Grounded Agentic Framework for Memory Corruption Vulnerability Detection in Binaries

Xinran Zheng, Alfredo Pesoli, Marco Valleri, Suman Jana +1 more

Veritas is a semantically grounded framework that detects memory corruption vulnerabilities in stripped binaries by combining static analysis, LLM-based reasoning, and runtime validation, achieving hi…

View →