India’s digital economy is scaling at an unprecedented pace. From government systems to global enterprises, automation, cloud-native development, and AI-powered operations now define how business gets done. But as organizations race ahead, a new blind spot has emerged at the heart of enterprise cybersecurity, non-human identities (NHIs).
According to Gartner, NHIs outnumber human identities by a staggering 45:1. Yet most security frameworks continue to focus primarily on protecting people, through passwords, multi-factor authentication, and user access monitoring, while overlooking the exponentially larger machine population driving digital transformation.
This gap was exposed dramatically when researchers discovered 12,000 live API keys and passwords in the Common Crawl dataset, a massive public web archive used to train large language models (LLMs). These credentials didn’t just signal careless coding practices; they revealed a deeper vulnerability: machines now hold the keys to enterprise networks, and traditional security systems aren’t built to protect them.
Understanding Non-Human Identities
NHIs include every digital entity that requires authentication to access systems, data, or services without human involvement. These range from API keys, service accounts, and OAuth tokens to TLS certificates and managed identities in cloud environments. In enterprises adopting DevOps and Infrastructure as Code (IaC), CI/CD pipelines alone can generate hundreds of machine credentials daily.
In India, where sectors such as BFSI, telecom, manufacturing, and government services are rapidly embracing automation, this machine identity sprawl is accelerating. Each API integration, microservice, or robotic process adds a new non-human identity, often with elevated privileges and no clear expiry.
The Security Crisis Beneath the Surface
Machine identities present a perfect storm of visibility gaps and privilege risks. Unlike human users, NHIs operate continuously, often across multi-cloud and hybrid setups. Many developers, under pressure to deliver quickly, embed API keys directly into source code or configuration files. These “hard-coded secrets” often end up in public repositories or AI training datasets, an increasingly common breach vector.
Equally worrying is the issue of excessive privileges. A backup service or automation bot may be granted broad administrative rights for convenience. If compromised, attackers can move laterally through systems, often undetected, since traditional monitoring tools are tuned for human behavioral anomalies, not machine activity.
Adding to the risk is poor lifecycle management. Temporary service accounts created for test environments or pilot projects often persist long after the initiative ends, still holding valid credentials and unnecessary access permissions.
The Next Wave: AI, Automation, and IoT
India’s rapid adoption of AI and intelligent automation is creating new categories of NHIs. Enterprise-grade AI agents now make autonomous decisions, generate content, and trigger workflows using dynamic credentials. These agents need adaptive, context-aware access controls, not static role-based models.
Automation platforms and container orchestration tools are another hotspot. RPA bots and CI/CD pipelines bridge multiple systems, demanding extensive permissions. In IoT-heavy sectors such as manufacturing and utilities, thousands of connected devices, sensors, actuators, and gateways, authenticate continuously with central servers. Each represents a potential attack vector.
Why Traditional Security Isn’t Enough
Human-centric identity frameworks can’t cope with the scale or complexity of NHIs. Organizations need a fresh approach built on four pillars:
- Dynamic Privilege Management: Move from static role-based access to just-in-time (JIT) privilege allocation. Grant only the permissions needed for a specific task and revoke them once complete.
- Behavioral Analytics for Machines: Establish baselines for normal machine behavior, such as API call frequency, data access patterns, and resource usage, and flag anomalies automatically.
- Zero Trust for NHIs: Apply “never trust, always verify” principles to machine identities. Every machine-to-machine transaction should be continuously authenticated and authorized.
- Secrets Management at Scale: Replace manual password vaults with automated systems that rotate credentials, enforce policies, and integrate directly with CI/CD pipelines.
Building Governance for a Machine-Driven Future
To tackle the NHI explosion, enterprises must establish identity governance frameworks for machines, covering discovery, provisioning, monitoring, and decommissioning. Automation is essential here: modern tools can map machine-to-machine relationships across cloud and on-premises systems, highlighting unused or risky credentials.
Integration with DevSecOps is equally critical. Security checks must shift left, embedded into the development pipeline itself. Static code analyzers can detect hard-coded secrets, while deployment scripts can validate credential configurations automatically.
The Way Forward
As India’s enterprises deepen their digital operations and embrace AI-driven automation, machine identities have become the invisible backbone of business. Ignoring them is no longer an option. The recent exposure of thousands of live credentials underscores an urgent truth: organizations can no longer rely on frameworks built for a human-centric world.
In a digital ecosystem where machines outnumber humans by more than 100 to 1, protecting non-human identities isn’t just an operational necessity, it’s a strategic imperative. The ideal time to act was yesterday; the second-best time is now.
The article has been written by Srilekha Veena Sankaran, Senior Enterprise Analyst, ManageEngine
Srilekha Veena Sankaran is a senior enterprise analyst at ManageEngine, the enterprise IT management division of Zoho Corporation. She leads marketing and user education initiatives for ManageEngine’s identity security solutions and specializes in helping customers secure access to mission-critical assets.
