We have seen examples of how critical machine identities are to an organization—especially in manufacturing and energy sectors that heavily rely on machine identity-based communications.
While designing a roadmap to secure and mature critical infrastructure, manufacturing, energy, and utility firms must consider the following key challenges:
Develop an understanding of the ever-evolving regulatory environment – Staying aligned with shifting regulatory requirements is essential for building a resilient identity security strategy. Different sectors have unique compliance obligations. A strong starting point is the NIST guidelines (SP 1800-10, Protecting Information and System Integrity in Industrial Control System Environments: Cybersecurity for the Manufacturing Sector), which provide a foundational understanding of regulatory expectations.
Know your infrastructure – Every machine is a component of the identity fabric, and it’s vital to maintain an up-to-date inventory of machines and their identities. This requires regular audits and reviews to identify changes, orphaned or unused accounts, and service accounts that may pose risk. Equally important is understanding integrations with legacy systems—many of which weren’t built with security in mind. A common challenge in industries like steel manufacturing is protecting legacy infrastructure while enabling modern identity integrations.
Define ownership – Unclear ownership of machine identities creates governance gaps. This becomes especially risky when third-party access is involved, as these can become weak points during security incidents.
Define clear policies and procedures – Just like human identities, machine identities require well-defined lifecycle policies—from creation through governance to decommissioning. Without clear procedures, these identities often fall through the cracks.
Implement principles of least privilege – Machine identities must be governed using the same security principles as human identities. Granting only the necessary access limits potential exposure during a breach. Additionally, creating segmentation and breakpoints in the network limits the potential scope of data loss.
Standardization and centralization – Centralizing machine identity management and adopting standardized processes leads to greater efficiency. It also supports early detection of anomalies, reduces the attack surface, and minimizes operational errors.
Audit manual interventions prior to release – Manual tasks like certificate issuance, renewal, and revocation still dominate machine identity processes. Applying privileged access controls and auditing these activities before deployment reduces risk and safeguards sensitive credentials.
Define the maturity journey for machine identities – Maturity can be measured by the level of automation and how changes are synchronized across systems. Paper-based or fragmented methods are error-prone and inefficient. Implementing automated lifecycle management supports governance while ensuring certificate accuracy and operational continuity.
Identity Orchestration for Mature Machine Identity Management
Each of these challenges can be addressed through siloed efforts—but that often results in inefficiencies, redundancies, and higher risk. A more effective approach is a holistic, tool-based strategy that automates workflows, enforces governance, and integrates security frameworks like Zero Trust.
Platforms built for identity orchestration help connect and manage machine identities across diverse systems. With centralized visibility, organizations can enforce consistent policies, respond faster to changes, and streamline identity governance across legacy and modern infrastructure.
As the number of technologies supporting IAM use cases grows—alongside the rapid proliferation of machine identities—organizations face complex integrations across SSO, IGA, PAM, CIAM, and CIEM platforms. When these systems operate in silos, integration becomes costly, error-prone, and difficult to maintain. Identity orchestration addresses these challenges by offering a consolidated, technology-agnostic approach that delivers actionable insights, reduces complexity, and enhances visibility into identity-related risks.
By applying the right framework, tools, and governance model, organizations—particularly in high-risk sectors like manufacturing and energy—can implement scalable, secure, and resilient machine identity strategies. Success requires more than just technology; it demands alignment across people, processes, and systems to deliver a unified, modern identity program that meets both operational and regulatory demands.
Written by Rahul Purohit
