How do IAM and PAM teams reduce lateral movement through machine identities?

Why This Matters for Security Teams

Machine identities often become the shortest path from a low-risk workload to a high-value system because they are reused, over-permissioned, and left in place long after the original task ends. That is exactly where lateral movement accelerates: one credential, token, or certificate opens multiple services, so compromise spreads faster than human-centric controls can detect it. NHI Management Group’s Ultimate Guide to NHIs notes that 97% of NHIs carry excessive privileges, which makes privilege containment a practical necessity rather than a hygiene exercise.

For IAM and PAM teams, the core mistake is treating machine identities like durable user accounts. Current guidance from the NIST Cybersecurity Framework 2.0 pushes organisations toward stronger identity governance, but machine-to-machine access needs tighter runtime control than classic RBAC alone can provide. The reality is that a service account, API key, or workload token can be copied, chained, and reused across environments in ways a human session usually cannot. In practice, many security teams discover that their lateral movement problem was already established by standing machine access before any alert ever fired.

How It Works in Practice

Reducing lateral movement starts with identifying every machine identity that can cross trust boundaries, then narrowing each one to a single purpose, system set, and time window. IAM and PAM teams should map workload identities to the exact resources they need, remove broad group memberships, and replace persistent secrets with ephemeral credentials issued just in time. That means the identity proves what it is at runtime, while the policy engine decides what it may do in that specific context.

Useful controls usually combine four layers:

• Workload identity binding, so the machine is authenticated as a specific service, job, or agent rather than as a shared secret holder.
• Short-lived credentials, so a stolen token expires before it can be reused widely.
• Policy evaluation at request time, so access depends on purpose, environment, and target sensitivity instead of a static allow list.
• Session logging that ties each privilege use to a named machine identity and a task outcome.

This is where PAM becomes more than a vault. For machine identities, PAM should broker access rather than merely store credentials. A compromise pattern seen in incidents such as JetBrains GitHub plugin token exposure and the BeyondTrust API key breach shows why long-lived secrets and broad reuse create blast radius that standard password rotation does not solve. Better practice is to issue task-specific credentials, limit them to the minimum reachable scope, and revoke them automatically when the job completes.

Teams that operationalise this well usually combine PAM telemetry with cloud IAM, secrets managers, and workload orchestration. That gives investigators a clean chain from identity issuance to privilege use to revocation. These controls tend to break down in hybrid environments where legacy services still require shared secrets, because those systems cannot consume ephemeral identity and runtime policy cleanly.

Common Variations and Edge Cases

Tighter machine-identity control often increases operational overhead, requiring organisations to balance blast-radius reduction against deployment friction and service fragility. That tradeoff is real, especially when older applications cannot rotate credentials without downtime or when multiple teams share one service account.

Current guidance suggests treating shared machine accounts as a temporary exception, not a steady state. Where there is no universal standard yet, organisations should document compensating controls: scoped network reachability, separate credentials per environment, stronger session recording, and faster revocation SLAs. High-frequency build systems and ephemeral compute fleets also need different handling than always-on services, because token issuance must match orchestration speed or teams will reintroduce static secrets for convenience.

NHIMG research shows the scale of the problem: 88.5% of organisations say their non-human IAM practices lag behind or merely match their human IAM efforts, and that maturity gap is one reason lateral movement persists. The 2024 Non-Human Identity Security Report is a useful benchmark for prioritising this work. In practice, the hardest cases are CI/CD pipelines, third-party integrations, and multi-cloud workloads where identity lifecycles are short, access paths are numerous, and no single control plane sees the full picture.

Related resources from NHI Mgmt Group

• How can IAM teams reduce risk from supplier access and machine identities together?
• How do IAM and NHI teams reduce lateral movement after a leaked token?
• How should teams secure non-human identities across cloud and SaaS?
• How should security teams decide whether JIT access is safe for non-human identities?