Machine identities are used by numerous organizations to help with access management, automation, and streamlining processes. When we think of identities in the identity and access management (IAM) context, we typically think of human identities. These are identities assigned to real users such as employees, administrators, contractors, and customers. However, there also exists another category of identities: machine and non-human identities.
Machine identities are identities that are given to non-human entities like servers, containers, and IoT devices. They serve several purposes but their main one is to provide secure interaction between systems, servers, devices, applications, and workloads as the identities are used to authenticate connections.
Physical and virtual servers are a key part of IT systems. Each of them has a unique identity to validate connections, manage permissions, and govern access to data.
Containers bundle applications with everything they need to ensure that the apps run the same way regardless of the environment. Each container has a unique identity to enable secure interactions within an application.
Smart devices like sensors, security cameras, and domestic appliances use distinct identities for secure communication. With more and more IoT devices being used in our daily lives, proper management of these identities is essential in maintaining security and preventing unauthorized access to them.
Non-human identities are a broader category. In addition to machine identities, it also includes things like APIs, bots, and Robotic Process Automation (RPA) tools. While machine identities are often associated with software workloads (e.g., cloud instances, containers, IoT devices), non-human identities generally refer to any non-human entity that must be authenticated and authorized within IT systems.
APIs allow different software systems to communicate with each other. Each API must have a unique identity to exchange data securely.
Bots are capable of performing and automating repetitive tasks, like answering customer questions or checking system performance. A secure bot has a unique identity with strong access controls.
Although RPA tools also automate, like bots, their focus is more on automating structured business processes like data entry and invoice processing. Each RPA instance possesses an identity that specifies what data it can read and modify.
Machine and non-human identities mainly enable the following functions in an organization:
• Automation: Both types of identities help to automate heavy/complex workloads, improving the efficiency of operations through less human intervention. Good identity controls, however, are required to help prevent abuse.
• Data processing and integration: Non-human identities streamline data handling, ensuring that integrations between different systems are seamless. Machine identities, for example, can help secure data exchanges between cloud-based services and safeguard confidential business information.
• Secure communication: Trusted system-to-system communication relies mainly on authenticated machine identities. Authentication of devices with digital certificates protects against misuse and ensures data integrity.
Machine and non-human identity management differs from regular user account management. Although automation makes identity management easier, organizations still face a range of challenges due to the fast growth of digital identities, security breaches, and strict compliance regulations. This section outlines common problems in machine identity management.
Companies now have more machine identities than ever before. 81% of security leaders believe that machine identity security is critical for protecting the future of AI, emphasizing the role that these identities have in modern technological infrastructures [1]. Statista also projects that the number of IoT devices worldwide will go from 15.9 billion in 2023 to over 32.1 billion by 2030, almost doubling in less than a decade [2].
This rapid growth leads to what experts call an "identity sprawl," where businesses have more identities than they can efficiently keep track of and monitor. Identity sprawl makes it difficult for IT staff to maintain a comprehensive view of all existing identities, their permissions, and their use. Uncontrolled identity sprawl can lead to unauthorized entry or data leaks.
If not handled correctly, machine identities can result in great security risks. For example, an intruder can get direct access to sensitive data or critical systems through a compromised identity. Studies reveal that on average, organizations manage 20 times more non-human identities than human ones, with over 20% of these non-human identities being insufficiently secured [3].
An example of a machine identity breach is the 2020 SolarWinds cyberattack, which caused multiple organizations (including US federal agencies) to be affected and compromised. Attackers were able to gain access to SolarWinds' software build system and inserted malicious code into their Orion network management software updates. When customers installed these updates, the embedded malware provided attackers with unauthorized access to their systems. This supply chain attack exploited trusted machine identities, allowing the malware to operate undetected for months. [4]
The Zero Trust framework, which assumes that no entity should be trusted by default and that continuous validation is required, is one example of a measure that could have been implemented to strengthen their security.
Regulatory standards like GDPR, PCI DSS, and HIPAA issue strict guidelines on handling identities and data. Adherence to these requirements can become challenging while managing non-human identities because each identity must closely follow these requirements. Organizations could face financial and reputational losses if they fail to comply. For example, not regularly updating or securely managing identities might violate the requirements set by these standards.
Having compliant machine identity management is important, especially in ensuring that fines aren’t being incurred.
To effectively manage non-human and machine identities, three primary challenges must be addressed:
• Increasingly rapid growth of identities: Organizations need automated management systems to handle and control the increasing number of identities.
• Security threats: Strong security models, such as Zero Trust, can help in reducing the risk of identity-related breaches.
• Complexity of compliance: Ongoing monitoring and efficient IAM practices enable firms to comply with strict regulations.
Addressing these challenges through clear policies, automated tools, and solid security measures enables companies to securely manage their identities.
Like in many other areas, machine and non-human identities are impacted by the new technologies and trends that arise. Given how rapidly these trends grow and evolve, it’s important for companies to have a solid understanding of them such that they are able to effectively prepare for any challenges that may come with it. The key trends include artificial intelligence (AI), the Zero Trust framework, as well as unified access management.
AI has grown exponentially in recent years, becoming a large presence in virtually any industry. In the case of identity management, AI is able to identify unusual behavior in real time. This real-time aspect is particularly beneficial as it means that threats can be detected sooner than what was possible before. Another example of AI’s power is its ability to automatically identify expired certificates.
All in all, AI reduces downtime and helps organizations improve their overall system security. This encourages many organizations to now use AI-based IAM solutions to manage and monitor machine identities.
The Zero Trust framework is an approach that has seen a rise. Though the concept has existed for over a decade, it has gained popularity in recent years as the world saw an increase in things such as cyber threats, cloud adoption, and identity-based attacks.
As mentioned earlier, the Zero Trust framework relies on the assumption that no identity should be trusted and that verification is always required. The framework functions on 3 main pillars: constant verification and authentication, the principle of least privilege access, and operating under the assumption that a breach has occurred/will occur (continuous monitoring and logging of activities).
In the case of machine/non-human identities, applying the Zero Trust framework would mean that each access request has to be examined, authenticated, and verified every single time—even if it has already been authenticated before. This increases the barriers that attackers must overcome to use compromised identities.
Different kinds of identities used to be managed and monitored using different systems and tools, as there was no better alternative. One could say that it got the job done, but it was undeniable that doing it this way caused for there to be more complexity and increased security risks. Then came unified access management (UAM), a solution that unified the monitoring and management of all identities—including machine and non-human identities—into one platform.
With UAM, organizations can control and take actions for all their identities more easily. Whether it be to apply the best practices or to automate tasks like provisioning and access reviews, it can all be done more efficiently with a centralized identity management system.
As these trends grow and new ones emerge, the need for IAM solutions has also seen an increase. Market estimates suggest that the IAM market will be valued at around $42 billion in 2031 [5]. Given the costs associated with security breaches and failures, it’s no surprise that many organizations are investing a great deal into IAM technologies such as machine identity management and AI integrations to make their environments more secure.
Three broad trends are transforming machine and non-human IAM in today's environment:
• AI-powered IAM solutions can offer faster threat identification and simpler management of tasks, and the capabilities that these AI-based solutions possess will only continue to grow.
• The Zero Trust framework offers an approach to greatly reduce security threats through applying principles like continuous verification and least privilege access.
• Unified access management ensures simpler, centralized control over identities.
Organizations that embrace and stay on top of trends will be able to manage their identities more efficiently and effectively, regardless of the changing environment.
Machine and non-human identity management can be complicated, but it can be made simpler by following clear best practices. This section will explore actionable items that organizations can undertake to help ensure that their identities are secured. This includes having strong authentication, automatic lifecycle management, least privilege access, and constant monitoring. Implementing these best practices will help organizations reduce security risks and operate their business in a more secure manner.
Having strong authentication methods and practices is crucial in securing identities and preventing unauthorized access, and there are a few ways this can be done. One such way is by using multi-factor authentication (MFA). MFA is when multiple forms of authentication is required to authenticate an identity. This can be done in many ways. Some commonly seen methods include via SMS (codes being sent to provided phone numbers) or through authenticator apps (codes being sent to apps such as Microsoft Authenticator or DUO).
Another practice organizations should do is regularly updating and rotating their credentials. Though it’s not a perfect solution, credential rotation helps lessen the risk of identities being compromised over time. Automating this process with IAM tools helps ensure this practice is consistently completed.
Finally, organizations should avoid using poor or outdated encryption methods. Adopting the latest encryption norms ensures machine identities remain secure against the newest threats.
As discussed previously, automation provides many benefits and organizations should certainly leverage it. Tasks involved in the lifecycle management of identities range from provisioning new identities and revoking active credentials to deleting expired or unused identities. In this case, automating the lifecycle management of machine and non-human identities reduces the likelihood of human errors while also saving time.
For example, automated identity management software can easily detect and disable orphaned identities, reducing the risks associated with unused identities. Organizations that use automation would also have an easier time properly managing a large number of identities.
Protocols such as System for Cross-domain Identity Management (SCIM) help standardize identity management processes. Adopting SCIM-based tools can help make operations more efficient, especially in systems where many machine and non-human identities must be managed.
The least privilege principle is about only giving identities the access they absolutely need. Following this principle greatly reduces the risk of unauthorized access or misuse.
Least privilege access can be enforced by organizations using role-based access control (RBAC). RBAC assigns identities to roles with strictly defined permissions, customizing the access that each role has specific to the requirements of its typical tasks. This ensures that only the necessary level of access is given to each identity. Nothing less, nothing more.
However, this doesn’t mean that RBAC is the one-and-done solution. Regular access reviews still need to be conducted by organizations to ensure that each identity continues to only have the access that is needed. Over time, some identities may need more or less access as business needs and objectives change. Frequently reviewing permissions helps ensure that all identities have the appropriate access.
Continuous monitoring allows for rapid identification of identity-related risks. For instance, by closely monitoring identity activities, organizations are able to detect and recognize malicious activity or security vulnerabilities before anything more severe can occur.
Security Information and Event Management (SIEM) systems help companies monitor real-time identity events. These solutions keep track of activities in real-time, alerting teams if any potential risks are detected. On top of this, there is User and Entity Behavior Analytics (UEBA), an approach that combines analytics, machine learning, and AI to detect any behavior that may be out of the norm. With this combination, UEBA systems are able to detect unknown threats, reduce false positives, and respond to insider threats more effectively and efficiently than traditional approaches. Its ability to detect anomalous behavior—such as logging in from an unfamiliar location—adds an extra layer of security that regular monitoring typically can’t provide.
In short, frequent audits confirm identities meet security and compliance standards. It helps identify if any identities aren’t configured correctly, reducing risks and ensuring compliance stays on track.
Organizations can greatly reduce risk and improve efficiency by implementing the following best practices:
• Strong authentication: Using MFA and regular credential rotations.
• Automated lifecycle management: Automatic provisioning, updating, and de-provisioning of identities.
• Least privilege access: Granting identities only necessary permissions.
• Continuous monitoring: Implementing SIEM and UEBA solutions and regular audits.
As more organizations rely on machine identities to secure digital interactions, proper management of them is key in preventing incidents such as security breaches. This illustrates the risks of poor identity management and the benefits of adopting modern, automated solutions.
Equifax, a prominent credit reporting agency, needed to safeguard its massive consumer data against cyberattacks. This involved the management of machine identities, including digital certificates for secure communications and network monitoring.
Equifax experienced a large data breach as a result of various security failures. An element of this breach was an expired digital certificate on a network traffic monitoring device. This failure made the device inactive for 19 months, allowing the attackers to gather sensitive information without detection the whole time.
After the breach, Equifax implemented several steps to tighten security:
• Renewed expired certificates: The expired certificate was renewed. This enabled the network monitoring device to work properly again.
• Installed automated certificate management: To prevent such incidents in the future, Equifax adopted automated methods of monitoring and renewing digital certificates.
• Improved network monitoring: Improvements were made to the overall network monitoring process to detect and respond to suspicious activity promptly.
• Data exposure: The breach exposed the personal information of around 148 million people.
• Financial penalties: Equifax incurred significant financial losses, including a settlement of at least $575 million with the Federal Trade Commission.
• Loss of reputation: The breach caused a loss of customer trust and emphasized the sheer importance of proper machine identity management.
Source: Equifax breach
• Machine and non-human identities are everywhere – Companies use machine identities for servers, IoT devices, APIs, and bots, and these need to be protected just like human identities.
• Managing machine identities is getting harder – With the rapid increase in IoT devices and cloud services, companies struggle with "identity sprawl", where they have more identities than they can track or control.
• Poor identity management can lead to major security breaches – The Equifax breach and SolarWinds attack happened partly because of weak machine identity security, showing why effective identity management is necessary.
• New security approaches like AI and Zero Trust can help – AI-powered IAM tools can detect unusual identity activity in real time, and Zero Trust security makes sure every machine and user is verified continuously.
• Better identity management improves security and efficiency – Companies using automated IAM solutions have seen fewer security risks, smoother operations, and easier compliance with regulations like GDPR and HIPAA.
• Strong authentication and continuous monitoring are key – Using multi-factor authentication (MFA), least privilege access, and security monitoring tools helps prevent cyberattacks and ensures machine identities aren’t misused.
References
1. CyberArk, "New CyberArk Research: Rapid Growth of Machine Identities, AI Adoption and Cloud Native Innovations Leave Organizations More Vulnerable to Attacks," StockTitan.net.
2. Statista, "Number of Internet of Things (IoT) connections worldwide from 2022 to 2023, with forecasts from 2024 to 2033," Statista.com.
3. AppViewX, "Half of Enterprises Surveyed Have Experienced a Security Breach Due to Unmanaged Non-Human Identities," AppViewX.com.
4. Wikipedia, "2020 United States Federal Government Data Breach," Wikipedia.org.
5. KBV Research, "The Identity and Access Management Market is Predict to reach USD 42.9 Billion by 2031, at a CAGR of 12.2%," KBVResearch.com.
