activity
20242026
collaborators

5 papers

cs.AI2026

GAVEL: Towards Rule-Based Safety Through Activation Monitoring

Shir Rozenfeld, Rahul Pankajakshan, Itay Zloczower +3

Large language models (LLMs) are increasingly paired with activation-based monitoring to detect and prevent harmful behaviors that may not be apparent at the surface-text level. Ho…

cs.CR2025

Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams

Gilad Gressel, Rahul Pankajakshan, Shir Rozenfeld +4

Romance-baiting scams have become a major source of financial and emotional harm worldwide. These operations are run by organized crime syndicates that traffic thousands of people…

cs.CR2025

ProxyPrints: From Database Breach to Spoof, A Plug-and-Play Defense for Biometric Systems

Yaniv Hacmon, Keren Gorelik, Gilad Gressel +1

Fingerprint recognition systems are widely deployed for authentication and forensic applications, but the security of stored fingerprint data remains a critical vulnerability. Whil…

cs.CL2025

ASRJam: Human-Friendly AI Speech Jamming to Prevent Automated Phone Scams

Freddie Grabovski, Gilad Gressel, Yisroel Mirsky

Large Language Models (LLMs), combined with Text-to-Speech (TTS) and Automatic Speech Recognition (ASR), are increasingly used to automate voice phishing (vishing) scams. These sys…

cs.CL2024

Are You Human? An Adversarial Benchmark to Expose LLMs

Gilad Gressel, Rahul Pankajakshan, Yisroel Mirsky

Large Language Models (LLMs) have demonstrated an alarming ability to impersonate humans in conversation, raising concerns about their potential misuse in scams and deception. Huma…