STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving

Large Language Models LLMs have demonstrated potential in code generation, yet they struggle with the multi-step, stateful reasoning required for offensive cybersecurity operations. Existing research often relies on static benchmarks that fail to capture the dynamic nature of real-world...

DeepXplain: XAI-Guided Autonomous Defense against Multi-Stage APT Campaigns

Advanced Persistent Threats APTs are stealthy, multi-stage attacks that require adaptive and timely defense. While deep reinforcement learning DRL enables autonomous cyber defense, its decisions are often opaque and difficult to trust in operational environments. This paper presents DeepXplain, a...

Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents

Autonomous offensive agents often fail to transfer beyond the networks on which they are trained. We isolate a minimal but fundamental shift -- unseen host/subnet IP reassignment in an otherwise fixed enterprise scenario -- and evaluate attacker generalization in the NetSecGame environment. Agent...

SoK: The Pitfalls of Deep Reinforcement Learning for Cybersecurity

Deep Reinforcement Learning DRL has achieved remarkable success in domains requiring sequential decision-making, motivating its application to cybersecurity problems. However, transitioning DRL from laboratory simulations to bespoke cyber environments can introduce numerous issues. This is furthe...

Collaborative research by Microsoft and NVIDIA on real-time immunity

AI-Powered Threats Demand AI-Powered Defense While AI supports growth and innovation, it is also reshaping how organizations address faster, more adaptive security risks. AI-driven security threats, including “vibe-hacking”, are evolving faster than traditional defenses can adapt. Attackers can n...

Chinese Hackers Use Anthropic's AI to Launch Automated Cyber Espionage Campaign

State-sponsored threat actors from China used artificial intelligence AI technology developed by Anthropic to orchestrate automated cyber attacks as part of a "highly sophisticated espionage campaign" in mid-September 2025. "The attackers used AI's 'agentic' capabilities to an unprecedented degre...

Large Language Models Are Autonomous Cyber Defenders

Fast and effective incident response is essential to prevent adversarial cyberattacks. Autonomous Cyber Defense ACD aims to automate incident response through Artificial Intelligence AI agents that plan and execute actions. Most ACD approaches focus on single-agent scenarios and leverage...