This Cybersecurity Awareness Month, Delinea is stepping up with a simple but urgent reminder: Machines are identities too.
From servers and APIs to cloud infrastructure and AI agents, non-human identities (NHIs) play a vital role in enabling business productivity—and cybercriminals know it. They also know that machine identities often aren’t given the same attention and care as human ones, making them juicy targets for an attack.
To raise awareness, we’re issuing a public service announcement and running a playful social campaign that brings machine identities to life while underscoring the serious need to secure them.
Why are machine identities at risk?
Many identity security solutions designed for humans don’t address the issues that can leave machine identities compromised. For example, machine identities don’t “log in” the same way that human accounts do, making them harder to verify and easier to exploit because they can’t be validated with multi-factor authentication (MFA).
Visibility of machine identities is another major challenge. They are often manually created and hidden in code. Plus, they can get cloned across environments, making it difficult for security teams to know how many machine identities exist, who owns them, or what they can access.
Without stronger controls, machine identities will remain a growing blind spot for cybercriminals to exploit
Poor governance and credential hygiene also compound the problem. Developers often create machine identities on the fly without consistent onboarding or offboarding processes, leaving no accountability or lifecycle management. Weak security practices such as shared API keys, tokens, and passwords are also common, making it difficult to rotate credentials or trace the source of identity-based threats. Without stronger controls, machine identities will remain a growing blind spot for cybercriminals to exploit.
AI amplifies machine identity woes
These challenges only intensify in the AI era. As AI agents and workloads take on more autonomous tasks, they inherit many of the same risks as traditional machine identities, but at a greater scale and speed. AI-driven processes often require broad access to sensitive data and APIs, making excessive permissions a critical concern.
Without clear governance, AI agents can proliferate rapidly, creating orphaned identities and expanding the attack surface faster than traditional security practices can keep pace.
Top 5 tips for protecting machine identities
While sparking conversation around this topic is an important first step, we want security teams to take action to keep their organizations secure. Here are five best practices every security team should follow to protect machine identities:
1. Discover and inventory everything:
Continuously identify all machine and AI identities, including accounts, secrets, and credentials, across cloud and on-premises environments. Achieving full visibility is the first step to reducing hidden risks.
2. Monitor posture and activity:
Audit and track machine identity usage. Monitoring for unusual behavior enables quick detection and remediation of threats before they escalate.
3. Secure and rotate credentials:
Eliminate static secrets by vaulting machine credentials and rotating them regularly. Dynamic or ephemeral credentials can help shrink the attack surface and prevent misuse.
4. Enforce least privilege and just-in-time access:
Apply zero standing privilege to machine identities, ensuring they only get the access they need, when they need it.
5. Automate lifecycle management:
Leverage automation to provision, deprovision, and govern machine identities. This reduces administrative overhead, prevents orphaned accounts, and ensures compliance with security policies.