Securing AI agents: Key controls and best practices
Security experts warn AI agents with employee-level privileges outpace human access controls and advise layered enforcement, sandboxing, and approval gates.
CSO reports that enterprises granting AI agents credentials, tools, and network access face risks that human-focused identity controls cannot contain, including machine-speed action chaining and sub-agent spawning. Experts from Strike Graph, Veracode, Delinea, and XBOW recommend treating agents as privileged insiders with hard technical boundaries: egress proxies with allowlists, short-lived brokered tokens, separated read/write rights, and approval for high-risk actions. XBOW describes a layered architecture with a guardian model reviewing agent actions and per-agent audit files. OWASP guidance on excessive agency urges limiting agent functions, permissions, and autonomy with authorization enforced downstream.
- AI agents inherit privileged credentials and can chain allowed actions into unauthorized outcomes at machine speed.
- Experts recommend hard boundaries: egress proxies, domain allowlists, short-lived tokens, and separated read/write capabilities.
- XBOW uses a guardian model, egress proxy, sandboxes, and per-agent audit files to contain offensive-security agents.
- OWASP recommends limiting agent autonomy and enforcing authorization in downstream systems, not in the model.
From the original article
7 min read at csoonline.com
Enterprises increasingly give AI agents the credentials, tools, and network access of privileged employees, but security experts warn that existing security controls designed to govern human access are insufficient.
csoonline.com
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