97 citations · 335 across the 14 of their papers we have counts for
5 papers · 1 filter
ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?
Zhun Wang, Nico Schiller, Hongwei Li +13
AI agents are rapidly gaining capabilities that could significantly reshape cybersecurity, making rigorous evaluation urgent. A critical capability is exploitation: turning a vulne…
Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre
Nicholas Carlini
Sabre is a defense to adversarial examples that was accepted at IEEE S&P 2024. We first reveal significant flaws in the evaluation that point to clear signs of gradient masking. We…
A LLM Assisted Exploitation of AI-Guardian
Nicholas Carlini
Large language models (LLMs) are now highly capable at a diverse range of tasks. This paper studies whether or not GPT-4, one such LLM, is capable of assisting researchers in the f…
A Partial Break of the Honeypots Defense to Catch Adversarial Attacks
Nicholas Carlini
A recent defense proposes to inject "honeypots" into neural networks in order to detect adversarial attacks. We break the baseline version of this defense by reducing the detection…
A critique of the DeepSec Platform for Security Analysis of Deep Learning Models
Nicholas Carlini
At IEEE S&P 2019, the paper "DeepSec: A Uniform Platform for Security Analysis of Deep Learning Model" aims to to "systematically evaluate the existing adversarial attack and defen…