6 papers · 1 filter
Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal
David Noever, Forrest McKee
Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or enrollment costs. We investig…
Favicon Trojans: Executable Steganography Via Ico Alpha Channel Exploitation
David Noever, Forrest McKee
This paper presents a novel method of executable steganography using the alpha transparency layer of ICO image files to embed and deliver self-decompressing JavaScript payloads wit…
Infecting Generative AI With Viruses
David Noever, Forrest McKee
This study demonstrates a novel approach to testing the security boundaries of Vision-Large Language Model (VLM/ LLM) using the EICAR test file embedded within JPEG images. We succ…
Hallucinating AI Hijacking Attack: Large Language Models and Malicious Code Recommenders
David Noever, Forrest McKee
The research builds and evaluates the adversarial potential to introduce copied code or hallucinated AI recommendations for malicious code in popular code repositories. While found…
Safeguarding Voice Privacy: Harnessing Near-Ultrasonic Interference To Protect Against Unauthorized Audio Recording
Forrest McKee, David Noever
The widespread adoption of voice-activated systems has modified routine human-machine interaction but has also introduced new vulnerabilities. This paper investigates the susceptib…
Acoustic Cybersecurity: Exploiting Voice-Activated Systems
Forrest McKee, David Noever
In this study, we investigate the emerging threat of inaudible acoustic attacks targeting digital voice assistants, a critical concern given their projected prevalence to exceed th…