How to build a secure network zone for an AI agent with Tailscale
Give the agent its own workload identity, two precisely defined connection paths, explicit negative tests and an external kill switch.
Read Grants GuideDefense First's blog
Cybersecurity as practical access paths.
Current analysis of AI threats, Zero Trust architecture, Tailscale and access controls whose effectiveness can be demonstrated through tests and log data.
Latest Article
An agent’s secure network zone is a graph of allowed connections.
The reference architecture limits the AI agent to two necessary Tailscale paths, proves that direct database, ERP and administration paths are closed, and requires ordinary internet egress to be blocked separately.
Previous articles
Analysis of threats and the controls that contain them.
Before you give an AI agent access to your company’s systems
A practical guide brings agent identity, tools, network paths, approvals, logging and the kill switch together as 12 testable controls.
Read 12 security controlsOpenAI AI agent breached Hugging Face
The incident shows how an AI agent can chain a zero-day vulnerability, isolation bypass, privilege escalation, and lateral movement into a long operation.
Read the analysisBlog topics
Every technical development is connected to a practical control.
The blog goes beyond threat headlines. Each analysis explains what the finding means for architecture, deployment, testing and continuous ownership.
01 / Threats
AI and cyber attacks
How agent automation is changing the speed, economics and chaining of attack paths.
02 / Architecture
Tailscale and Zero Trust
How to reduce the public attack surface, broad network trust and lateral movement in practice.
03 / Verifiability
Controls, tests and logs
How an access path is tied to an approved need and its behaviour remains verifiable after the change.
