Applied GAI in Security

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Brandon Dixon

Brandon Dixon

Brandon is a cybersecurity expert currently leading Security Copilot at Microsoft. He is known for creating PassiveTotal, Blockade.io, NinjaJobs, PDF X-Ray, and other opensource tools

Last Week in GAI Security Research - 10/14/24

Last Week in GAI Security Research - 10/14/24

Highlights from Last Week * 🪱 Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems * ⚠️ AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents * 🪝 APOLLO: A GPT-based tool to detect phishing emails and generate explanations that warn users * 🎶 Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning * 🐞 RealVul: Can

Last Week in GAI Security Research - 10/07/24

Last Week in GAI Security Research - 10/07/24

Highlights from Last Week * 🫥 The Perfect Blend: Redefining RLHF with Mixture of Judges * 🔏 Confidential Prompting: Protecting User Prompts from Cloud LLM Providers * 🦺 Overriding Safety protections of Open-source Models * 🤖 Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents * 🧠 Undesirable Memorization in Large Language Models: A Survey * 🚧 The

Last Week in GAI Security Research - 09/30/24

Last Week in GAI Security Research - 09/30/24

Highlights from Last Week * 💂‍♂ MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks * 📚 Unit Test Generation for Vulnerability Exploitation in Java Third-Party Libraries * 🔗 LLMs are One-Shot URL Classifiers and Explainers * 🛻 Enhancing LLM-based Autonomous Driving Agents to Mitigate Perception Attacks * ⛔ Holistic Automated Red Teaming for Large Language

Last Week in GAI Security Research - 09/23/24

Last Week in GAI Security Research - 09/23/24

Highlights from Last Week * 🧮 Jailbreaking Large Language Models with Symbolic Mathematics * ❇ AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing * 📨 Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach * 🧑‍💻 Hacking, The Lazy Way: LLM Augmented Pentesting * 📝 CoCA: Regaining Safety-awareness of Multimodal Large Language Models

Last Week in GAI Security Research - 09/16/24

Last Week in GAI Security Research - 09/16/24

Highlights from Last Week * 🍯 LLM Honeypot: Leveraging Large Language Models as Advanced Interactive Honeypot Systems * 🔎 Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches * ⛑️ LLM-Enhanced Software Patch Localization * 🔒 A First Look At Efficient And Secure On-Device LLM Inference Against KV Leakage * 📒 Using Large Language Models for Template Detection

Last Week in GAI Security Research - 09/09/24

Last Week in GAI Security Research - 09/09/24

Highlights from Last Week * 🐚 RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command Explainer * 🤖 SafeEmbodAI: a Safety Framework for Mobile Robots in Embodied AI Systems * 📰 LLM Detectors Still Fall Short of Real World: Case of LLM-Generated Short News-Like Posts * 🎭 The Dark Side of Human Feedback: Poisoning Large Language Models via

Last Week in GAI Security Research - 09/02/24

Last Week in GAI Security Research - 09/02/24

Highlights from Last Week * 🤺 Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks * 🥀 Detecting AI Flaws: Target-Driven Attacks on Internal Faults in Language Models * 📧 Investigating the Effectiveness of Bayesian Spam Filters in Detecting LLM-modified Spam Mails * 🚪BackdoorLLM: A Comprehensive Benchmark for