Zscaler unveiled a zero trust platform to secure autonomous AI agents’ data access, communications and device activity. It adds an AI Broker for agent-to-agent and data calls, endpoint AI threat detection, an AI Access Graph for mapping identities and data flows, and expanded AI Protect controls. This aims to give each AI agent its own identity, permissions and real-time monitoring.

• Zscaler launched a zero trust platform giving each AI agent its own identity, permissions, and real-time monitoring, built on four pieces: an AI Broker, Endpoint AI Security, an AI Access Graph, and expanded AI Protect controls.
• Dell'Oro Group forecasts the AI systems security market will grow from near zero to $8 billion by 2030, with nearly 60 vendors already competing.
• Analysts warn agents shouldn't inherit trust just because a user launched them—without unique identities and scoped permissions, compromised or misconfigured agents could move laterally and escalate privileges in seconds.

The UK’s AI Safety Institute tested Claude Mythos and found its ability to uncover security flaws scales directly with the number of tokens spent. This creates a simple economic model: defenders must outspend attackers on AI-driven reviews to stay secure. It also boosts the value of open source libraries, since multiple users can share the cost of token-based audits.

• UK AI Safety Institute confirmed vulnerability discovery scales directly with tokens spent using Claude Mythos Preview
• Security becomes a spending race: defenders must outspend attackers on token-driven audits to stay ahead
• Open source libraries gain outsized value since audit costs get shared across all downstream users
• Falling token costs and improving AI efficiency make shared/communal security audits progressively cheaper