#featured

Evaluating LLM Generated Detection Rules in Cybersecurity

2025-09-20 Anna Bertiger, Bobby Filar, Aryan Luthra, Stefano Meschiari, Aiden Mitchell, Sam Scholten, Vivek Sharath Conference on Applied Machine Learning in Information Security (CAMLIS) 2025

#LLMs #Evaluation #Cybersecurity #Featured

An open-source evaluation framework and three benchmark metrics for measuring LLM-generated cybersecurity detection rules.

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The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

2018-02-20 Brundage, Avin, Clark, Toner, Eckersley, Garfinkel, Dafoe, Scharre, Zeitzoff, Filar, et al. arXiv preprint

#AI Safety #Featured

Foundational report co-authored with researchers from FHI, OpenAI, CSER, EFF, and CNAS on the misuse risks of advanced AI.

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Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning

2018-01-26 Hyrum S. Anderson, Anant Kharkar, Bobby Filar, David Evans, Phil Roth arXiv preprint

#Reinforcement Learning #Adversarial ML #Featured

An RL agent that learns to make non-breaking modifications to malicious PE binaries to evade static ML-based malware classifiers.

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Ask Me Anything: A Conversational Interface to Augment Information Security Workers

2017-07-12 Bobby Filar, Richard Seymour, Matthew Park Thirteenth Symposium on Usable Privacy and Security (SOUPS 2017)

#NLU #Human-AI Interaction #Featured

An early natural-language interface for security analysts — a precursor to today's agent-based SOC tooling.

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