About Secure AI Fabric

Secure AI Fabric publishes practitioner-level security frameworks for autonomous AI systems in enterprise production environments.

The publication focuses on the security architecture challenges that emerge as AI agents gain autonomy: identity propagation for non-human actors, protocol-level vulnerabilities in agent ecosystems, supply chain risks in plugin and skill marketplaces, trust management across multi-agent systems, and the maturity models organizations need to assess their readiness.

Topics we cover include:

- AI agent identity architecture and trust boundary design
- Protocol security for agent communication and orchestration (including MCP)
- Supply chain controls for agent plugins, skills, and tool ecosystems
- Threat modeling and controls mapping for LLM-powered systems
- Shadow agent detection and governance for unmanaged AI deployments
- Enterprise maturity models for AI agent security posture
- Predictive automation patterns and operational resilience for AI-driven platforms
- Hybrid-cloud architecture patterns for secure AI deployment

Secure AI Fabric is currently written by Nik Kale, who also publishes broader analysis on AI security, governance, and production architecture at nikkale.com. The publication is designed to grow into a multi-contributor platform as the field matures.

We welcome contributions from practitioners working on AI agent security, enterprise AI governance, and related architecture challenges. If you are interested in contributing, reach out via the Contact option.

For expert commentary or press inquiries on AI agent security, autonomous systems, or enterprise AI governance, contact us directly.