A Red Teaming Framework for Evaluating Robustness of AI-Enabled Security Orchestration, Automation, and Response Systems

AI-enabled Security Orchestration, Automation, and Response SOAR systems increasingly employ autonomous agents for cyber defense, yet their resilience to adaptive adversaries is underexplored. We introduce an autonomous red teaming framework that integrates large language models LLMs with...

Beyond RAG for Cyber Threat Intelligence: A Systematic Evaluation of Graph-Based and Agentic Retrieval

Cyber threat intelligence CTI analysts must answer complex questions over large collections of narrative security reports. Retrieval-augmented generation RAG systems help language models access external knowledge, but traditional vector retrieval often struggles with queries that require reasonin...

AI in Cybersecurity Education -- Scalable Agentic CTF Design Principles and Educational Outcomes

Large language models are rapidly changing how learners acquire and demonstrate cybersecurity skills. However, when human--AI collaboration is allowed, educators still lack validated competition designs and evaluation practices that remain fair and evidence-based. This paper presents a...

Security Analysis of Agentic AI Communication Protocols: A Comparative Evaluation

Multi-agent systems MAS powered by artificial intelligence AI are increasingly foundational to complex, distributed workflows. Yet, the security of their underlying communication protocols remains critically under-examined. This paper presents the first empirical, comparative security analysis of...

Enhancing Automotive Security with a Hybrid Approach Towards Universal Intrusion Detection System

Security measures are essential in the automotive industry to detect intrusions in-vehicle networks. However, developing a one-size-fits-all Intrusion Detection System IDS is challenging because each vehicle has unique data profiles. This is due to the complex and dynamic nature of the data...

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks

This paper presents a novel approach to intrusion detection by integrating traditional signature-based methods with the contextual understanding capabilities of the GPT-2 Large Language Model LLM. As cyber threats become increasingly sophisticated, particularly in distributed, heterogeneous, and...

Privacy-Aware, Public-Aligned: Embedding Risk Detection and Public Values into Scalable Clinical Text De-Identification for Trusted Research Environments

Clinical free-text data offers immense potential to improve population health research such as richer phenotyping, symptom tracking, and contextual understanding of patient care. However, these data present significant privacy risks due to the presence of directly or indirectly identifying...

Building the Best SOC Takes Strategic Thinking

So your security team is ready to scale up its security operations center, or SOC, to better meet the security needs of your organization. That’s great news. But there are some very important strategic questions that need to be answered if you want to build the most effective SOC you can and avoi...

A Matter of Perspective: Agent-Based and Agentless Approaches to Cloud Security, Part 2

In our previous blog on this topic, we discussed some of the considerations when choosing between agent-based and agentless cloud security approaches. The following table provides a summary of these considerations. Aspect | Agent-based | Agentless ---|---|--- Deployment | - Deployed on every asse...

Mystery Company Offers $250,000 Bounty for VM Escape Vulnerabilities

An unnamed company will start an eight-week, invite-only bug bounty program in September that offers a $250,000 payout for virtual-machine escape vulnerabilities tied to an unreleased product. Bugcrowd announced the program today, and said the high-priced bounty is the largest advertised bounty o...