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Teleport released three new features for its Beams runtime to track what AI agents do, detect unexpected behavior, and score risk levels. The webinar covers how to audit agent sessions, write policies that catch workarounds, and triage activity at scale using MITRE ATT&CK mapping.
- Session Summaries compress multi-hour agent logs into 30-second summaries with operations, security actions, and risk levels
- Agentic Classifiers catch agents attempting policy workarounds through LLM proxy-level audit across Claude, OpenAI, and other models
- Risk Scoring tied to MITRE ATT&CK framework lets small teams triage agent activity without manual review of every session
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.