The OWASP Agentic Skills Top 10 maps the 10 risks of the AI-agent skill ecosystem - malicious skills, supply chain compromise, over-privileged manifests, metadata attacks, weak isolation, update drift, scanning gaps, governance failures and cross-platform reuse - with real 2026 evidence.
PowerShell, WMI, scheduled tasks, certutil: signed by the OS vendor, whitelisted by AV, trusted by EDR. Living-off-the-land attacks drop no malware, so detection cannot hinge on unknown binaries. The shift from artifact blacklists to execution-baseline analytics that actually catches native-tool chains.
How attackers hijack AI applications with nothing but text: direct vs indirect injection, real incidents from Bing to EchoLeak, why no complete fix exists, and the layered architecture that actually contains it.
RAG pipelines trust whatever lands in the vector database. Learn how corpus poisoning, retriever manipulation, and injected documents hijack AI answers — and the defenses that actually work in 2026.
Five years ago, application security meant securing APIs, patching web frameworks, and hunting for SQL injection in input fields. Today, we’re handing over SSH keys, database credentials, and deployment pipelines to AI agents that make their own decisions about what code to run. Post-Quantum Cryptography for Cyber Professionals Red Teaming LLM Applications: A Practical Playbook […]
Your IAM system answers 'who has access' — AI agents ask 'what will this identity do next.' The authority gap, three real attack scenarios, and a four-layer framework to close it.
How AI models get stolen through extraction and distillation attacks. Explore techniques, defenses, and real-world ML security case studies.
How AI agents transform enterprise SOC operations — autonomous triage, incident response, threat hunting, and compliance automation.
A deep dive into securing AI agent supply chains — MCP server vetting, dependency integrity, sandboxing, and trust anchors for AI infrastructure.
Master the three-layer model for AI agent identity: cryptographic identity, capability permissions, and runtime least privilege for autonomous AI systems.
Zero Trust for AI systems requires rethinking identity, data flows, and access control. Learn the five pillars of AI Zero Trust — identity verification, input validation, least privilege, monitoring, and encryption — with practical architecture patterns and implementation roadmap.
Post-quantum cryptography is no longer a research-only topic. With NIST's first PQC standards finalized and organizations facing long-term risks such as harvest-now, decrypt-later, cyber teams need to understand how PQC affects PKI, TLS, code signing, firmware trust, crypto agility, and migration planning. This guide explains what PQC is, where QKD fits, how hybrid deployments work, and what defenders should prioritize first.