Cybersecurity
Cyber
Agentic threat modeling, identity security, and the evolving attack surface of autonomous AI systems.
Explore by Category
- Red Team AI-assisted offensive techniques, authorized emulation, and attack surface research.
- Blue Team Detection engineering, autonomous defenders, guardrails, and IR workflows.
- Agent Architecture Design patterns, memory systems, and orchestration for reliable autonomous agents.
Agentic Cyber Library New
A curated intelligence toolkit of agent frameworks, LLM security testing tools, and authorized offensive copilots — annotated for practitioners building or securing agentic AI systems.
Browse the library →Latest Cyber Articles
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The Agentic Frontier: An Industry Analysis of Auto-GPT-for-Security and the Evolving SOC
An industry analysis of how agentic AI frameworks like Auto-GPT-for-Security are restructuring the modern SOC — from autonomous triage and the collapse of the Tier 1 analyst role to the rise of Agent Orchestrators and AI Security Posture Management.
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Defensive Agent Safety: Best Practices for Engineers Who Worry Their Agents Could Be Turned Against Them
Practical safety patterns for engineers building defensive AI agents — covering adversarial robustness, prompt injection containment, least-privilege design, and how to keep your defender from becoming the attacker's best asset.
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Connecting an LLM to Nuclei: A Practitioner's Architecture Guide
A hands-on walkthrough of the architecture for connecting a large language model to the Nuclei vulnerability scanner — with safe configuration patterns, pseudocode, and scope-control guidance.
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Agentic Threat Modeling: Securing the AI Attack Surface
How autonomous AI agents expand the threat surface and what security teams need to model, monitor, and mitigate before the next CVE targets an agent runtime.