AI agents: Take Control of Non-Human Identities
“We’ve got hundreds of service accounts and AI agents running in the background. We didn’t create most of them. We don’t know who owns them. How are we supposed to secure them?” That complaint — heard in boardrooms, IT war rooms, and cloud-cost reviews — captures a modern dilemma: enterprises race to automate, yet remain alarmingly blind to the identities that power automation.
Behind every large organization sit thousands of non-human identities: service accounts, API keys, tokens, containers, and increasingly autonomous AI agents. These actors access systems, move data, and execute tasks without vacations, audit trails, or obvious owners to call when incidents occur. The result is an expanding, poorly cataloged attack surface that traditional identity and access management (IAM) systems were never built to secure.
Why non-human identities are a risk
The growth of non-human identities is a story of provenance and compounding complexity. Early automation relied on service accounts tied to scripts and cron jobs. Cloud adoption multiplied credentials: each microservice, serverless function, and pipeline often demands unique access. DevOps velocity, third-party integrations, shadow IT, and now AI agents that can autonomously create or extend identities only accelerate the problem. Analysts warned that non-human identities will outnumber human accounts in many enterprises, making governance and visibility urgent priorities.
When identities are unmanaged, attackers gain a low-friction path to compromise. A leaked CI/CD token can redeploy malicious binaries; an overprivileged cloud role can expose entire data stores. Recent incident reports highlight supply-chain and automation-driven breaches where adversaries exploited exposed tokens and service accounts to move laterally. Beyond security, regulations increasingly require demonstrable governance over access and data flows — a near-impossible task when identities are opaque.
Key challenges to address
– Inventory gaps: Many IT teams lack a complete catalog of non-human identities. Credentials lurk in code, config files, container images, or forgotten cloud projects.
– Credential sprawl: Long-lived API keys and service accounts often accumulate unnecessary permissions over time.
– Ownership ambiguity: Identities are created by transient projects or tooling; identifying the business owner is difficult.
– Detection noise: Security tools produce false positives, making it hard to prioritize genuine risks.
– Organizational friction: Developers and operators value uptime and speed, which can push convenience over strict identity hygiene.
Practical controls for AI agents and other non-human identities
None of the mitigation strategies are new; the key is consistent, organization-wide application to every automated actor — including AI agents.
1. Inventory and visibility
Discover and catalog every non-human identity across cloud accounts, on-prem systems, CI/CD pipelines, and third-party services. Combine agented and agentless discovery with log analysis and configuration management databases (CMDBs). Treat inventory as a living dataset, automatically updated by pipelines and deployment tooling.
2. Least privilege and role hygiene
Design roles around specific tasks with narrow permissions. Avoid undifferentiated “owner” or “admin” roles for machines. Use role-based and attribute-based access control, and require just-in-time elevation for higher-risk operations.
3. Short-lived credentials and ephemeral identities
Move from long-lived keys to short-lived tokens and workload identity federation. Use platform-native token services and instance metadata where available to avoid hard-coded secrets. Ephemeral identities reduce the window for abuse.
4. Secrets management and code hygiene
Centralize secrets in vaults, remove hard-coded credentials from repositories, and scan infrastructure-as-code and container images for embedded secrets within CI pipelines. Automate credential rotation and make rotation events auditable.
5. Ownership and lifecycle governance
Assign a clear owner and business justification to every non-human identity. Bake deprovisioning into project closure and deployment pipelines so identities are revoked when no longer needed.
6. Monitoring and behavioral analytics
Log every action by non-human identities and correlate activity with baselines. Alert on anomalies such as access outside normal windows, unusual data movement, or cross-account usage. Behavioral detection helps catch compromised agents faster.
7. Policy and standardization
Codify naming conventions, minimum controls for machine identities, mandatory expiration dates, and procurement requirements. Embed these standards into developer templates, onboarding, and vendor contracts.
Organizational realities and trade-offs
Tooling improvements — managed identities, workload identity federation, automated rotation — are important but insufficient on their own. Organizations must change incentives so developers and operators treat identity hygiene with the same discipline as code testing. Expect trade-offs: short-lived tokens can complicate workflows and increase deployment latency; automated remediation can disrupt services if ownership and inventory are incomplete; confidentiality concerns may limit how much context is shared about certain automated actors.
Cross-functional action and measurable goals
Addressing non-human identity risk is inherently cross-functional. Security teams should partner with development, DevOps, cloud, procurement, and legal to bake identity controls into templates and vendor requirements. Executives must fund remediation and prioritize time for cleanup. Regulators can accelerate good practice by requiring demonstrable governance for sensitive sectors.
Start small and measure. Pick a critical application or cloud account, inventory its non-human identities, and apply short-lived credentials and clearer ownership. Track mean time to detect and mean time to remediate incidents involving AI agents and other machine identities. Use those metrics to justify broader rollout.
Conclusion: secure the identities that animate automation
AI agents and other machine identities are only as safe as the controls and disciplines you apply. If organizations don’t catalog, constrain, and govern these non-human actors, attackers will continue to exploit them as easy pathways to sensitive systems. Securing every automated actor is a long-term program, but the cost of inaction can be immediate and severe. How much exposure will you accept while waiting to act?
