Zero Networks targets AI agent security gaps with network-level ‘Least Agency’ controls
Summary
Zero Networks announced 'Least Agency Enforcement,' a security tool that protects AI agents by restricting them at the network level rather than just at the application level. The tool uses identity-based micro-segmentation (dividing networks into smaller zones based on who or what needs access) and multi-factor authentication (MFA, requiring multiple verification steps) to limit which systems an AI agent can communicate with, preventing damage if the agent is tricked, misconfigured, or compromised. This addresses a major gap: about 80% of enterprises have deployed internal AI agents, but roughly two-thirds lack security policies for them.
Solution / Mitigation
Zero Networks' Least Agency Enforcement uses three techniques: (1) identity-based microsegmentation to map and enforce which systems an agent identity should access, with everything outside that set denied by default; (2) automated policy generation; and (3) just-in-time multi-factor authentication (MFA) routing sensitive protocols (like RDP, SMB, or WinRM, which are remote access tools) through MFA prompts so a compromised agent cannot quietly move across the network. The capability is available immediately.
Classification
Affected Vendors
Original source: https://www.csoonline.com/article/4204394/zero-networks-targets-ai-agent-security-gaps-with-network-level-least-agency-controls.html
First tracked: August 3, 2026 at 02:01 PM
Classified by LLM (prompt v3) · confidence: 75%