9 papers
AttackonCTF: Defending Hardware Security Competition Benchmarks in the Age of LLMs
Mohamadreza Rostami, Nikhilesh Singh, Stephen Muttathil +5
Hardware security competitions such as HackTheSilicon serve as benchmarking platforms for evaluating vulnerability detection methods and for training humans and AI. However, our st…
NeST: Neuron Selective Tuning for LLM Safety
Sasha Behrouzi, Lichao Wu, Mohamadreza Rostami +1
Safety alignment is essential for the responsible deployment of Large Language Models (LLMs). Yet, existing approaches often rely on heavyweight fine-tuning that is costly to updat…
GoodVibe: Security-by-Vibe for LLM-Based Code Generation
Maximilian Thang, Lichao Wu, Sasha Behrouzi +4
Large language models (LLMs) are increasingly used for code generation in fast, informal development workflows, often referred to as vibe coding, where speed and convenience are pr…
NeuroStrike: Neuron-Level Attacks on Aligned LLMs
Lichao Wu, Sasha Behrouzi, Mohamadreza Rostami +3
Safety alignment is critical for the ethical deployment of large language models (LLMs), guiding them to avoid generating harmful or unethical content. Current alignment techniques…
AegisSat: Securing AI-Enabled SoC FPGA Satellite Platforms
Huimin Li, Vusal Novruzov, Nikhilesh Singh +3
The increasing adoption of System-on-Chip Field-Programmable Gate Arrays (SoC FPGAs) in AI-enabled satellite systems, valued for their reconfigurability and in-orbit update capabil…
Fuzzilicon: A Post-Silicon Microcode-Guided x86 CPU Fuzzer
Johannes Lenzen, Mohamadreza Rostami, Lichao Wu +1
Modern CPUs are black boxes, proprietary, and increasingly characterized by sophisticated microarchitectural flaws that evade traditional analysis. While some of these critical vul…