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17/08/2026 4:42 pm
TL;DR: Enterprises are suffering repeated breaches because human compromise is only the entry point, while attackers then use machine credentials, tokens, certificates, and secrets to reach mission-critical systems, according to Akeyless. The real governance failure is that IAM, PAM, and Vault models still assume a human-paced control loop, even though machine access now drives the blast radius.
NHIMG editorial — based on content published by Akeyless: Why enterprises must act now to secure mission-critical systems
By the numbers:
- Lack of credential rotation is cited as the top cause of NHI-related attacks by 45% of organisations, followed by inadequate monitoring and logging and over-privileged accounts at 37% each.
Questions worth separating out
Q: What breaks when machine credentials are not rotated?
A: When machine credentials are not rotated, stale access accumulates and the organisation loses confidence that the secret still reflects the intended scope.
Q: Why do machine identities complicate traditional PAM programmes?
A: Machine identities complicate traditional PAM because they need access patterns that are automated, frequent, and often cross-cloud.
Q: How do security teams know if machine identity governance is working?
A: Look for fewer standing accounts, faster onboarding of automation workflows, auditable role approvals, and visible retention of access records after logout.
Practitioner guidance
- Map every machine credential to an owner and runtime dependency Build a current inventory of service accounts, API keys, certificates, and tokens, then tie each one to an owning team, application, and environment.
- Reduce standing machine privilege before attackers can reuse it Replace long-lived secrets with short-lived credentials where possible, and set revocation rules that match workload duration rather than human review cycles.
- Break the code-to-runtime secret path Scan repositories, configuration stores, CI/CD pipelines, and container images for embedded secrets, then remove hardcoded credentials and replace them with governed runtime issuance.
What's in the full article
Akeyless's full article covers the operational detail this post intentionally leaves for the source:
- The vendor's specific key-splitting and zero-knowledge architecture for machine secrets
- Implementation claims around auto-rotation and ephemeral credential handling across deployment environments
- The interoperability details for DevOps, CI/CD, observability, and virtualization toolchains
- The platform integration model for managing multiple existing secrets managers
👉 Read Akeyless's analysis of machine credential exposure in mission-critical systems →
Machine credential exposure in multi-cloud: what IAM teams are missing?
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17/08/2026 4:47 pm
Machine identity governance is now the control plane for breach containment. The article is right that human compromise is not the real business problem. The breach outcome depends on whether attackers can pivot into machine credentials that outlive the initial intrusion. That makes service accounts, tokens, certificates, and workload secrets the decisive layer for blast-radius control.
A few things that frame the scale:
- 1 in 4 organisations are already investing in dedicated NHI security capabilities, with an additional 60% planning to do so within the next twelve months, according to The State of Non-Human Identity Security.
- Only 1.5 out of 10 organisations are highly confident in their ability to secure NHIs, compared with nearly 1 in 4 for securing human identities.
A question worth separating out:
Q: Who is accountable when a machine credential is abused?
A: Accountability should sit with the team that owns the workload, the identity lifecycle, and the connected business process, not with security alone. In regulated environments, that usually means engineering, platform, and IAM teams share responsibility for discovery, rotation, and offboarding while compliance verifies that the process is repeatable.
👉 Read our full editorial: Machine credential exposure is undermining enterprise security models
