Lateral movement is dangerous because a single foothold can turn into broad access across connected systems, including OT controllers and medical devices that are hard to patch or monitor. In manufacturing, that can interrupt production. In healthcare, it can affect patient care and sensitive data. The mix of legacy systems, trust relationships, and limited visibility gives attackers room to expand quietly.
Why Lateral Movement Becomes a Manufacturing and Healthcare Problem
lateral movement is not just a breach-stage tactic in these environments. It is the bridge between a single compromised credential and operational impact. In manufacturing, attackers can move from IT into OT-adjacent systems, engineering workstations, historians, or remote access paths that were never designed for hostile inspection. In healthcare, the same pattern can expose EHR platforms, imaging systems, medication workflows, and connected devices that must stay available even when they are under suspicion.
The risk is amplified by trust relationships, legacy protocols, and segments that were built for uptime rather than adversarial containment. NHIMG’s Ultimate Guide to NHIs — Why NHI Security Matters Now notes that 97% of NHIs carry excessive privileges, which makes the blast radius of a single foothold much larger than many teams expect. That matters because lateral movement often rides on service accounts, shared secrets, remote tools, and machine-to-machine trust that are rarely reviewed with the same rigor as human access.
Practical defenders should think in terms of containment boundaries, not just perimeter defense, because attackers rarely need to "break in" a second time once they can reuse trust already present inside the network. In practice, many security teams encounter the real cost only after production has stalled or patient-facing workflows have already been disrupted.
How Attackers Expand Quietly Across Connected Systems
Lateral movement succeeds when identity, network, and workload controls do not agree on what is normal. A stolen service account, API key, or remote admin token can be used to enumerate assets, harvest more credentials, and pivot through management planes that were assumed to be internal-only. On flat or weakly segmented networks, the attacker does not need sophisticated malware to move, only valid access and enough patience to blend into routine automation.
That is why zero trust and least privilege are more than policy language. NIST’s Zero Trust Architecture guidance emphasizes continuous verification rather than implicit trust based on network location. For organisations trying to understand the identity layer behind this risk, NHIMG’s Top 10 NHI Issues is useful because it frames the operational mistakes that let machine identities become pivot points.
- Limit east-west trust between business IT, OT, and clinical environments.
- Use unique, short-lived credentials instead of shared accounts and long-lived secrets.
- Monitor service account behaviour, not just user logins, because many pivots start there.
- Separate remote maintenance paths from normal internal traffic and review them continuously.
For deeper attack-path context, the MITRE ATT&CK Enterprise Matrix is helpful for mapping discovery, credential access, and lateral movement techniques to the controls that should detect them. These controls tend to break down in highly interconnected plants and hospital networks because legacy devices, vendor access, and uptime constraints prevent consistent segmentation and logging.
Why the Risk is Worse in Legacy, High-Availability Environments
Tighter containment often increases operational overhead, requiring organisations to balance resilience against maintenance complexity. That tradeoff is especially hard in manufacturing and healthcare, where downtime is expensive, devices may be difficult to patch, and some systems cannot support modern authentication or agent-based monitoring.
Best practice is evolving, but guidance increasingly points toward identity-driven segmentation, real-time policy checks, and strict control of non-human credentials. NHIMG’s Ultimate Guide to NHIs — Key Challenges and Risks is relevant here because it shows how excessive privilege, weak rotation, and poor visibility turn ordinary machine access into lateral movement fuel. Where the industry has not reached consensus yet is in exactly how far to push runtime authorization for every device class, especially when vendor tools still depend on static trust. Current guidance suggests using the strongest controls on the most critical links first.
Operationally, teams should prioritise high-value paths such as domain admin services, jump hosts, shared automation accounts, PACS and EHR integrations, and OT engineering workstations. The goal is not to eliminate movement entirely, but to make each step visible, time-bound, and hard to reuse. The pattern fails fastest where old systems, third-party support, and emergency access procedures all rely on the same long-lived secrets and broad internal trust.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST CSF 2.0, NIST Zero Trust (SP 800-207) and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Lateral movement often relies on overprivileged non-human credentials. |
| NIST CSF 2.0 | PR.AC-4 | Access permissions and segmentation are central to stopping internal pivots. |
| NIST Zero Trust (SP 800-207) | JIT authorization | Zero trust directly addresses implicit internal trust used for lateral movement. |
| CSA MAESTRO | IAM-04 | Autonomous workload and service identity controls help contain machine-to-machine spread. |
| NIST AI RMF | AI RMF is relevant where autonomous agents can amplify lateral movement paths. |
Enforce least privilege and restrict east-west access across manufacturing and care networks.
Related resources from NHI Mgmt Group
- Why do AI ETL libraries create such high lateral movement risk?
- Why do workflow automation platforms create such high lateral movement risk?
- Why does RDP create such a high lateral movement risk in enterprise environments?
- Why do exposed environment variables create such a high lateral movement risk in AWS?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 1, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org