The New Identity Crisis
Cybersecurity used to be about people. Securing digital identities meant managing employee access, verifying user credentials, and assigning roles. But today, that human-centric approach no longer suffices.
With the explosive growth of cloud services, DevOps pipelines, and especially artificial intelligence, we are seeing an identity paradigm shift. Enterprises now manage thousands even millions of Non-Human Identities (NHIs): service accounts, containers, scripts, bots, and AI agents. In some organizations, NHIs outnumber human users by 50 to 1.
Identity is the new security perimeter. Across modern digital ecosystems, machines have overtaken humans as the dominant identity type. Yet most identity frameworks still prioritize people, creating a dangerous blind spot.
Understanding NHIs: The Rise of Machine Identities
Non-Human Identities (NHIs) refer to any digital identity used by systems, software, or hardware, rather than people, to interact with services and data. These identities operate silently, scale rapidly, and often remain unnoticed.
Common examples include:
- Service Accounts: Applications connecting to databases or internal APIs.
- API Keys and Tokens: Used for authenticating system-to-system communication.
- RPA Bots: Software robots executing repetitive business tasks.
- AI Agents and Copilots: Autonomous or semi-autonomous processes making decisions or taking actions.
Unlike human users, NHIs lack formal onboarding and offboarding processes. Once created, they often persist indefinitely, even when no longer in use, becoming “shadow identities” with unknown access and unknown owners.
AI’s Role in Expanding the Identity Surface
Artificial Intelligence is not just consuming data; it is reshaping the identity landscape.
AI introduces both volume and volatility into identity ecosystems. Unlike traditional human users, AI-generated entities are dynamic, fast-scaling, and often operate beyond formal visibility. Consider:
- Generative AI agents that autonomously draft reports, trigger transactions, or modify digital assets.
- Automated scripts in CI/CD pipelines that deploy infrastructure or run system tests within seconds.
- RPA workflows interacting with critical systems, from financial tools to HR platforms to customer databases.
Each of these non-human actors requires access credentials and needs them in real time. The issue arises when these identities are created outside structured IAM processes. They may be spun up automatically, use temporary containers, or be embedded within code, making them difficult to track or govern.
This leads to credential sprawl, inconsistent permissioning, and limited visibility. These entities not only expand the identity surface but also redefine it. As AI-driven processes multiply, they quietly widen the attack surface, often without triggering any alarms until a breach occurs.
Key Identity Security Challenges
The rise of NHIs calls for a new approach to identity security, one that treats machine identities as first-class citizens and addresses risks that traditional IAM models cannot handle.
- Shadow Identities
Untracked or forgotten NHIs—such as service accounts created for test environments—can remain active for years. Without governance, they become ideal backdoors for attackers. - Overprivileged Access
NHIs often receive blanket permissions, such as admin-level access, because least-privilege policies are difficult to enforce for machines. If compromised, these entities offer attackers wide-ranging capabilities. - Lifecycle Blind Spots
NHIs are not subject to HR-managed onboarding and offboarding. There is often no assigned owner, expiration policy, or deactivation plan. - Credential Hygiene Risks
Tokens and credentials are frequently hardcoded in code repositories or configuration files. These secrets are rarely rotated, leading to long-lived credentials with high-risk exposure. - Automation Blindness
AI and RPA agents can execute high-impact actions without oversight. If their logic is corrupted, they can unintentionally or maliciously create disruptions.
Rethinking Identity Security for the AI Age
Securing NHIs requires a new mindset. Identity must become the foundation of security, not merely a function of user management.
Key shifts include:
- Identity-First Security
Prioritize identity over perimeter-based models. Enforce authentication and authorization consistently across humans, devices, and NHIs. - Real-Time Identity Inventory
Map all digital actors in your system, both human and machine. Maintain up-to-date metadata on their roles, ownership, and access history. - Behavioral Analytics
Monitor NHIs for anomalies in access behavior. For example, if a bot that usually accesses payroll systems suddenly attempts to access R&D data, that is a clear red flag. - Enforced Least Privilege
Assign only the access necessary for each NHI to function. Use role-based access control (RBAC) and fine-grained permissions whenever possible. - Automated Credential Rotation
Secrets should never be static. Use tools that rotate keys and tokens regularly and revoke them when no longer needed.
Modern Tools and Techniques
Leading organizations are investing in modern identity platforms that go beyond managing human users:
- AI-Driven IAM Platforms (e.g., SailPoint, Saviynt)
These systems use machine learning to detect excessive access rights, dormant identities, and suspicious usage patterns. - Secrets Management Tools (e.g., HashiCorp Vault, AWS Secrets Manager)
Automate secure storage, retrieval, and rotation of credentials. - Just-in-Time (JIT) Access
Grant temporary access rights that expire after a specific task or time period, minimizing exposure. - Zero Trust Architectures
Validate each access attempt dynamically based on identity, behavior, location, and device, not just login credentials. - Container-Aware IAM
Tools like Kubernetes RBAC and Open Policy Agent (OPA) enable granular permissions in containerized environments.
Real-World Lessons from Breaches
Security failures involving NHIs are no longer theoretical. Consider:
- SolarWinds Breach: Attackers used compromised credentials from machine accounts to inject malware into trusted software, impacting thousands of organizations
(source: SpyCloud ). - GitHub Token Leaks: Developers accidentally exposed API tokens, allowing attackers to hijack cloud services (source: CSO Online).
- RPA Misconfigurations: In some banks, bots executed financial transactions without proper audit logs or access controls, leading to compliance violations
(source: How Robotic Process Automation (RPA) Creates Security Risks).
These cases emphasize the need for rigorous NHI governance and proactive detection methods.
AI’s New Identity Threats
As AI systems become more autonomous and embedded in decision-making, they do not just consume identities—they can generate, manipulate, or misuse them. This introduces a novel risk class.
New Threat Vectors:
- Synthetic Identities
Generative AI models can fabricate plausible identities by combining real and fake data to create “ghost” users that bypass verification mechanisms. - Identity Inference
AI algorithms trained on sensitive datasets may unintentionally expose personal or corporate identity data through inference or model leakage. - IAM Prompt Injection
As IAM copilots become more common, attackers can exploit their natural language interfaces using prompt injection or manipulation, tricking them into granting or modifying access controls. - Autonomous Exploitation Loops
Advanced AI agents can scan environments, find weakly protected NHIs, and autonomously escalate privileges or pivot across systems faster than manual attackers can respond.
“AI is no longer just consuming identities – it is beginning to manipulate them. Modern security systems must detect not only access abuse but also access deception.” – Dineshkumar Gandhi, Technical Project Manager at SISAR
CISO Action Plan: Identity-First Security
CISOs and security leaders must drive the transformation toward identity-centric security with practical, leadership-level steps:
- Unify Identity Management by bringing human and non-human identities under a single governance model.
- Use Automated Discovery to continuously scan for new NHIs and classify them based on risk and function.
- Perform Ownership Mapping by assigning responsibility for every NHI, including lifecycle management and access reviews.
- Implement Access Timeboxing to limit the duration of access rights and reduce standing privileges
- Harden CI/CD Pipelines by embedding secrets scanning and policy checks.
- Provide Security Training to engineering and DevOps teams on credential hygiene, NHI risks, and least-privilege principles.
These actions reduce exposure and support a resilient identity posture that evolves alongside AI and automation.
Autonomous Identity Governance
As enterprises shift toward AI-driven operations, identity systems must become autonomous, adaptive, and intelligent.
Key innovations include:
- Policy-as-Code
Security policies embedded in application and infrastructure code enable automated enforcement at runtime. - Self-Healing IAM
Systems that detect misconfigurations and automatically fix or quarantine risky identities. - Context-Aware Access
Use real-time data—such as behavior, device type, and time of day—to make smarter access decisions. - IAM Copilots
AI assistants that help security teams manage identities, recommend policies, detect anomalies, and conduct audits faster.
These capabilities ensure that identity security scales with the complexity of cloud-native and AI-first environments.
Securing the Invisible Workforce
Non-Human Identities (NHIs) now power critical systems, from automation to AI. Yet many remain unmanaged, creating blind spots across the enterprise.
Legacy identity models fall short in this new landscape. Securing today’s digital environment means treating NHIs as first-class identities—tracked, governed, and protected with the same rigor as human users.
With AI expanding the identity surface, adaptive and automated identity security is no longer optional—it’s essential. Organizations that modernize now will reduce risk, improve resilience, and lead confidently into an AI-driven future.
Shaping the Future of Identity Security with SISAR
The identity game has changed—and we’re building what’s next. At SISAR, we’re partnering with visionary teams to explore smarter ways to secure both human and non-human identities in an AI-first world. From strategy to experimentation, we’re in it with you.
Empower your enterprise to secure every identity and step into tomorrow with confidence.
