collaborators

13 papers

cs.SE2026

SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers

Kaihua Qin, Dawn Song, Arthur Gervais

Smart contract decompilation aims to recover high-level source code from bytecode, but evaluating decompilers remains difficult because existing studies use narrow datasets, incons…

cs.CR2026

Measuring Safety Alignment Effects in Autonomous Security Agents

Isaac David, Arthur Gervais

Do stock safety-aligned language models and their uncensored or abliterated derivatives behave differently when run as autonomous security agents? Single-turn refusal benchmarks ca…

cs.SE2026

Benchmarking Mythos-Linked Bug Rediscovery

Isaac David, Arthur Gervais

Anthropic's April 2026 Mythos materials combine benchmark claims with concrete bug-finding stories across OpenBSD, FreeBSD, Linux, FFmpeg, and browsers. This paper reports a contro…

cs.CR2026

Ablating Safety: Mechanisms for Removing Alignment in Language Models for Security Applications

Isaac David, Arthur Gervais

Safety-aligned language models often refuse cybersecurity requests whose wording resembles misuse, even when the task is authorized and defensive. This makes security evaluation am…

cs.SE2026

CrackMeBench: Binary Reverse Engineering for Agents

Isaac David, Arthur Gervais

Benchmarks for coding agents increasingly measure source-level software repair, and cybersecurity benchmarks increasingly measure broad capture-the-flag performance. Classical bina…

cs.CR2026

Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches

Isaac David, Arthur Gervais

Security updates create a short but important window in which defenders and attackers can compare vulnerable and patched software. Yet in many operational settings, the most access…