Identity and Access Management (IAM): From Human-centric to Machine-inclusive Security
Initially, Identity and Access Management (IAM) served as a straightforward IT function designed solely to ensure that human users gained appropriate access to systems. Its primary goal was to authenticate and authorize individuals based on their roles and responsibilities. However, the landscape has dramatically shifted. Today, digital identity has emerged as the predominant attack surface, with at least 80% of modern security breaches involving compromised or stolen identities—often exploited by cyber adversaries due to poor management practices.
This troubling reality shifts much of the responsibility for risk mitigation onto the security teams tasked with defending organizations. At the heart of this effort is the Chief Information Security Officer (CISO), responsible for orchestrating security strategies. Yet, a critical blind spot exists: non-human identities—those belonging to machines, systems, applications, and automated workloads. This oversight is no minor detail. In fact, machine identities are estimated to outnumber human identities by a factor of at least 45 to 1, with some estimates reaching a ratio of 100 to 1 within organizations.
As companies strive to deliver more software and features at an unprecedented pace, the population of machine identities—such as service accounts, APIs, and automated processes—continues to grow rapidly. The adoption of Large Language Models (LLMs) and quickly deployed AI-powered coding assistants and productivity tools further accelerates this trend, leading to an explosion in non-human identities. If security leaders fail to develop IAM strategies that account for these machine identities, they leave a massive and vulnerable attack surface exposed, one that adversaries are actively targeting.
Limitations of Traditional IAM: An Incomplete Governance Model
The conventional IAM paradigm has long been centered around human identities—onboarding employees, assigning role-based access, monitoring policy violations, and deprovisioning accounts when necessary. This human-centric approach has advanced significantly, incorporating robust governance frameworks, compliance mandates, multifactor authentication (MFA), and Zero Trust principles. Leading identity management solutions from providers like Okta, OneLogin, and Auth0 have kept pace with these innovations.
In contrast, non-human identities operate under fundamentally different assumptions and mechanisms:
- They often lack passwords, relying instead on API keys, tokens, and cryptographic identifiers for authentication.
- They typically do not follow traditional identity lifecycle processes; service accounts and machine identities may persist indefinitely, even after their original purpose has lapsed.
- They usually lack a clearly assigned owner, making security oversight challenging and often neglected.
Furthermore, NHI are frequently misused or abused. The fragmentation and unchecked proliferation of secret credentials—such as API keys and access tokens—have become a significant security risk. These secrets are often hardcoded into source code, embedded within configuration files, or exposed through log files. Secrets with long lifespans, ungoverned or lacking automated rotation policies, are prime targets for hackers. Many legacy systems do not enforce expiry or rotation, resulting in outdated keys remaining active for years, especially in cloud environments. Additionally, NHIs are often over-permissioned due to hurried development cycles, with developers granting excessive privileges just to expedite deployment. The absence of clear governance and systematic oversight results in many machines having more access than necessary, creating vulnerabilities that malicious actors eagerly exploit.
In sum, without a comprehensive IAM strategy that includes machine identities, organizations are only addressing part of the security challenge. Effective protection must encompass all identities—human and machine—to truly secure access and mitigate risks.
The Business Case for Security Leaders to Own Machine Identity Governance
Given that IAM now falls under the security function’s jurisdiction, it is imperative that Chief Information Security Officers (CISOs) and their teams take ownership of managing machine identities. Here’s why:
Machine Identities Represent a Major Attack Vector
Digital identities constitute one of the most expansive and least monitored attack surfaces in modern enterprises. Cybercriminals increasingly target exposed API keys, compromised service accounts, or misconfigured automated identities to gain unauthorized access. Several high-profile breaches have underscored this threat:
- The U.S. Department of the Treasury was compromised through a stolen API key, enabling attackers to access desktops and non-classified documents.
- Toyota publicly disclosed a vulnerable server access key that allowed unauthorized data access for five years, exposing sensitive customer information.
- The New York Times revealed a GitHub token that resulted in the online exposure of 5,600 code repositories.
Regulatory Compliance and Risk Management
Regulatory frameworks such as PCI DSS, GDPR, ISO 27001, and standards from the National Institute of Standards and Technology (NIST) mandate strict controls around access privileges and minimum necessary permissions. Historically, these requirements focus primarily on human identities. However, as regulators recognize that non-human identities pose equally significant—or even greater—risks, organizations will be held accountable for securing all types of identities. This includes applying least privilege principles consistently, monitoring the entire lifecycle of machine identities, and auditing credentials, tokens, and service accounts with the same rigor currently reserved for user accounts.
Waiting until after a major breach to comply with evolving standards is too late. Proactive security management is essential to stay ahead of regulatory expectations and emerging threats.
Incorporating Non-Human Identities into Zero Trust Architectures
Zero Trust security models emphasize continuous verification, least privilege access, and segmentation. While these principles are well understood for human identities, applying them to machine identities requires deliberate effort:
- Continuous Validation: Machine identities should undergo ongoing authentication and authorization checks, rather than one-time provisioning.
- Least Privilege Enforcement: Automated identities must operate with minimal permissions, and permissions should be reviewed regularly.
- Segmentation and Isolation: Machine identities should be confined to specific workloads and services, limiting their access scope.
Failing to treat non-human identities as rigorously as human ones undermines Zero Trust initiatives. Managing machine identities foundationally strengthens security posture by reducing the opportunity for lateral movement or privilege escalation within the environment.
Building a Holistic and Modern IAM Strategy
Developing an effective, modern IAM strategy begins with comprehensive discovery and mapping of all organizational identities—including machines. This entails understanding where secrets are stored, how they originated, their permissions, and their interconnections within the ecosystem. Deploying robust secrets management platforms—serving as single sources of truth—ensures all credentials are encrypted, tracked, and monitored consistently.
Special attention must be paid to the lifecycle management of machine identities. Unlike humans, whose access patterns are predictable, machines often require automated processes for creating, rotating, and deactivating credentials. Security teams should deploy systems capable of tracking the creation date, creator, renewal schedule, and decommissioning timeline of each secret or account.
Extending IAM Controls to Non-Human Identities
To fully integrate machine identities within the IAM framework, organizations should follow these next steps:
Discover All Machine Identities
Organizations must first identify all existing machine identities—service accounts, API keys, tokens, and other automated credentials—regardless of where they are stored. Documentation should include their creation details, storage locations, and current usage status. Without full visibility, it’s impossible to implement effective controls or enforce security policies.
Centralize Secrets and Credential Management
Fragmented secret management across multiple tools leads to duplication and inconsistent security. On average, enterprises manage six or more secret stores, complicating oversight. Centralizing secrets management simplifies tracking, enforces policy consistency, and reduces risks associated with conflicting or outdated credentials. Additionally, automated checks can ensure secrets are rotated simultaneously across all systems, maintaining integrity during security incidents.
Enforce Rotation Policies and Minimum Privilege Principles
Granting the right permissions is a complex yet critical task. Many machine identities often have excessive privileges, including capabilities to modify or delete important data or resources. Implementing policies for regular permission audits, least privilege enforcement, and automated credential rotations ensures that secrets maintain their security posture over time. Continuous monitoring helps detect and revoke unnecessary privileges, mitigating potential abuse.
Secure Non-Human Identities via Zero Trust
Currently, most machine identities rely on long-lived credentials—API keys and tokens that often last for years. In an ideal environment, automatic identity federation and short-lived tokens—like those enabled by frameworks such as SPIFFE and SPIRE—would be employed to guarantee that identities are ephemeral and tightly controlled. While reworking existing infrastructure can be challenging, migrating secrets into centralized secure stores offers a path toward Zero Trust adherence in the near term. Mapping these identities is a prerequisite to enforce proper authentication and restriction policies effectively.
Towards a Unified IAM for Human and Machine Identities
In a digital landscape where identity is the chief new security perimeter, security leaders must adopt a holistic view that encompasses both human and non-human entities. Integrating machine identity security into a comprehensive IAM strategy not only mitigates risks but also enables organizational agility and innovation. Proper management of automated identities simplifies compliance, reduces attack vectors, and provides a competitive edge in the rapidly evolving digital economy.
While the path forward involves complex challenges, each step reinforces an organization’s security framework. Ultimately, proactive and integrated identity management is no longer just a technical necessity but a strategic imperative—driving resilience and trust across the enterprise environment.
*Dwayne McDaniel is a Developer & Cybersecurity Advocate at GitGuardian
