CISO AI Security Hub
A curated entry point for CISOs, security leaders, AppSec teams, and SOC managers preparing for AI agents, LLM adoption, faster vulnerability discovery, and the operational risk of machine-speed attacks.
Executive playbook
The near-term goal is not to block every model. It is to make safe adoption easier than shadow adoption: approved tools, scoped access, secure sandboxes, logging, human review, data rules, and clear ownership for AI-assisted security decisions.
Search topics
CISO reading path
Zero Trust in the age of AI agents means every human, model, agent, device, API, repository, and workflow must prove identity, need, context, and authority before action. Network location is no longer the trust boundary.
NIST's February 2026 work on AI agent identity and authorization is a timely signal that the real enterprise risk is no longer model output alone, but what agents are allowed to do, prove, and audit once they start acting.
Claude Opus 4.7 is built for stronger coding and agentic workflows. Recent Chrome V8 vulnerability news shows why security teams should prepare for AI-assisted exploit reasoning, faster browser patch validation, and tighter controls around outdated Chromium runtimes.
A practical GitHub security checklist for teams: branch protection, rulesets, secret scanning, push protection, Dependabot, CodeQL, GitHub Actions hardening, least-privilege access, OIDC, and SECURITY.md.
Trivy is excellent at finding known vulnerabilities, misconfigurations, secrets, and SBOM risk. OpenAI-style agentic security workflows can help teams turn that scanner output into prioritized, reviewable remediation without treating AI as the source of truth.
Anthropic's Claude Mythos Preview and Project Glasswing are a warning shot for enterprise security teams: AI-driven vulnerability discovery is moving toward machine speed, and companies need secure sandboxes, patch pipelines, and executive governance before attackers copy the playbook.
Field guides
How security command centers can use AI for triage, visualization, and communication without losing operator trust.
How different model families help with code review, secure design feedback, and remediation support.
Choosing models for timelines, containment support, communication, and lessons learned.
A practical comparison of leading model families for triage, alert summarization, and analyst copilots.