Machines form the foundation of our digital world — with every interaction relying on workloads, containers, applications and physical devices, including mobile and IoT. And much like humans, these machine’s need identities in order to authenticate and gain access privileges. In nearly all cases, however, machine identities are verified with a single factor, using ‘secret zero,’ a master token or key that, if exposed, enables the attacker to impersonate the compromised workload and access associated secrets.
To avoid data theft, downtime and other damages, we need to completely rethink machine identity management in a way that will better secure IT operations, including cybersecurity, cloud and identity and access management (IAM) infrastructures. Case in point: Gartner predicts that IAM infrastructure is now a critical attack point that needs to be protected.
The problem is that machine identity management is highly complex — a topic covered in great detail in our previous blog, “The Machine Identity Crisis: How It’s Spun out of Control and What Can Be Done.” It’s a great place to start if you need a primer on machine identity management, a new and critical area for cyber and identity-security professionals.
In this new blog post, we’ll make sense of the complexity and create more order by looking at every step of the machine identity lifecycle. In each step or phase, there are potential risks that cyber and identity-security professionals need to address. We’ll break it down for you, explaining the tasks and risks at each stage.
The machine identity lifecycle & risks to address
To minimize complexity and risk, it’s vital to secure and manage the full lifecycle of machine identities. To do this at machine speed and scale, large organizations need a consolidated solution that automates the processes throughout the machine identity lifecycle. At the same time, security teams and developers need complete visibility of all machine identities in their environment.
7 Steps of the machine identity lifecycle
At a high level, machine identity management involves authentication and authorization, but there’s a full lifecycle to manage, centered around three primary tasks: provisioning, renewing and revoking identities. But even those three tasks are overly simplistic. Here we’ve highlighted 7 steps of the lifecycle along with related security risks to give you a full picture of machine identity management:
- Identity creation (aka key generation): This involves generating unique identifiers, such as certificates, credentials or API tokens for each machine.
Risks: Weak, easily guessable credentials or keys can be a risk, but this issue is less common of with machines compared to humans. The primary risks are insecure storage of credentials and key sharing, which links together many machines, making them indistinguishable from each other. If your identity creation methods are not built on strong foundations, bad actors will find a way to compromise at this stage of the lifecycle. One concern is that a bad actor could create a rogue workload but have it issued with a unique identifier that has been created by one or more of your systems. In this scenario, the workload could go unnoticed since it’s using ‘legitimate credentials.’ There are similar risks with duplicate identities, orphaned credentials and other complicating factors.
- Identity provisioning: After key generation, identities need to be securely provisioned to the machines. This may involve deploying the identities to machines directly or by using a centralized identity management system to distribute and install the identities on the machines. Ideally, identities are distributed through a secure standards-based provisioning process using encrypted channels to establish digital trust with the provisioned machines.
Risks: Insecure distribution methods or unauthorized access to the identity files during provisioning can expose the identities to interception, tampering or theft and can impede response times when dealing with vendor solution vulnerabilities. This is further complicated by today’s infrastructure-as-code paradigm, which requires key provisioning. But typically, in this scenario, keys are kept in repositories — a highly insecure way to keep secrets, leaving them vulnerable to compromise.
- Secure storage of credentials and secrets: Throughout the machine identity lifecycle, machine identities and associated cryptographic keys, credentials or access tokens must be securely stored and managed. Proper key management practices, such as key generation, encryption, secure storage mechanisms and access controls, ensure the confidentiality and integrity of the machine identities.
Risks: All key generation and storage mechanisms, even key vaults, such as AWS Key Management Service (KMS), and HashiCorp Vault, are vulnerable to unauthorized access, data leakage or theft. If ‘secret zero’ is exposed, machine identities are vulnerable.
- Expiration and renewal: In some cases, machine identities should have a specific validity period, after which they need to be renewed. This involves managing the expiration dates and ensuring that machine identities are reissued in time to avoid outages.
Risks: Expired certificates, for example, can lead to disruptions in machine operations and machine-to-machine communications. Outages can negatively impact consumer confidence, revenue and productivity. To avoid outages, a common (but risky) practice is to create a very long validity period with an expiration date far beyond what’s needed. This only increases the opportunity for compromise.
- Rotation and revocation: It’s important to regularly replace (i.e. rotate) or revoke long-lived or compromised machine identities. Rotation involves generating new cryptographic keys, certificates, or credentials and replacing the existing ones used by machines or systems within an organization’s infrastructure. If a machine is compromised, no longer needed or no longer authorized to access certain resources, machine identities may need to be revoked before their expiration date.
Risks: Expired or compromised machine identities are a security risk that can result in unauthorized access or misuse if you allow the identities to remain active.
- Monitoring and auditing: Continuous monitoring and auditing involves tracking the usage of machine identities, monitoring their validity and access patterns and generating audit logs for compliance and security analysis purposes.
Risks: Full visibility of all machine identities in today’s complex IT environments is challenging but essential to detect any anomalies, suspicious activities or unauthorized use.
- Remediation and incident response: In the event of a security incident, you may need to revoke identities, replace keys, run forensics and implement measures to prevent future incidents.
Risks: Lack of visibility into the usage and behavior of machine identities can hinder incident response efforts and compromise the overall security posture.
Minimizing risk across the machine identity lifecycle
Now more than ever, machines are the dominant force of digital business, and the numbers of machines are going to only multiply as generative AI takes hold. So the question is how can you reduce the attack surface in every way possible? Look for our next machine identity blog (coming soon) to get recommendations for mitigating risk throughout the identity lifecycle.
