Why machine identity sprawl is now a DevSecOps problem

TL;DR

Machine identity sprawl, the rapid growth of service accounts, API keys, and certificates, creates unmanaged access paths in DevSecOps. This exposes cloud infrastructure to breaches. The fix: short-lived credentials, automated rotation, scoped permissions, and centralized secrets management.

As your DevOps team spins up more service accounts to manage cloud resources, signs more image signatures to verify containers during CI/CD builds, and distributes more IoT authentication keys to secure device communication during edge deployments, machine identities quietly multiply. What begins as convenience in automating tasks like deployments, authentication, authorization, and encryption soon turns into unchecked growth.

Machine identities now outnumber human identities by a ratio of more than 80 to 1. For many organizations, this means a single engineer ends up managing dozens or even over 80 non-human identities (NHIs) across systems and environments. When loosely managed, these identities become entry points for attackers, exposing sensitive information and leaving security teams scrambling in the aftermath of data breaches.

This article breaks down how unmanaged NHIs expose your infrastructure to real threats and outlines the security practices DevSecOps teams should adopt to contain the risk before it spreads.

How machine identity sprawl becomes a security threat

Many teams struggle with proper security management, even with human identities like usernames, passwords, and multi-factor authentication (MFA) tokens, where volumes are much lower. With NHIs, the risk is only amplified. You’re often managing them manually, inconsistently, and often without enough discipline or visibility into how they are used across systems.

Let’s explore how this oversight gap turns machine identity sprawl into a growing security threat.

Common paths that turn unmanaged machine identities into active security threats.

No visibility into access patterns

When teams cannot trace which services or jobs are using a given machine identity, detecting a security breach becomes nearly impossible. If a GCP service account token is hardcoded into multiple CI/CD jobs, you lose the ability to pinpoint which job triggered suspicious activity. Without that visibility, you can’t quickly map the blast radius, identify affected systems, or trace the attacker’s path through your infrastructure.

Secrets copied across pipelines, repos, and containers

Using the same machine identities across multiple environments creates a hidden risk: exposure in one environment often means exposure everywhere. For example, reusing development credentials in a GitHub Actions workflow that deploys to production increases your system’s exposure and complicates incident response. Revoking compromised credentials takes longer because you would first need to trace where they are being used.

Unused credentials remain active

If an API key tied to a retired Kubernetes service account stays valid, it’s effectively a spare key left forgotten. Attackers can exploit these orphaned identities undetected, which contributes to privilege creep, expanding access beyond intended scopes.

Manual revocation and rotation

In most environments, revoking or rotating machine identities remains a manual task that engineers handle inconsistently. This often happens because secret rotation isn’t tied to deployment events or the identity lifecycle. For example, an IAM access key for an AWS automation script might stay active for months after the script is retired. Without automation, gaps emerge between issuance and invalidation, leaving infrastructure vulnerable to operational interruptions and prolonged exposure windows.

Secrets exposed in logs, crash reports, and third-party tools

GitGuardian’s 2024 State of Secrets Sprawl report found over 24 million secrets exposed in public repositories. Many of these exposures result from poor practices, such as hardcoding secrets, logging sensitive data, or failing to sanitize crash reports before sharing them. A debug log from a failed API deployment in Jenkins might include a live database password, meaning attackers wouldn’t even need to hack their way in. They could simply use the exposed credential.

These gaps add friction and weaken your security posture while they persist, each one widening the surface for known vulnerabilities such as phishing attacks, insider threats, or accidental data compromise. DevSecOps teams need to shift from reactive cleanup to proactive control before sprawl becomes a breach.

Why DevSecOps teams must act now

Attackers focus primarily on your production environment, where code is live and systems are actively running. Modern cloud-native applications depend on large numbers of NHIs to handle deployments, communication, and scaling, many of which are created or rotated while the application is running. This makes it critical for your DevSecOps team to manage these identities as part of runtime security, not just build-time setup.

Think about your CI/CD pipelines. Every deployment might involve using multiple secrets spread across jobs and environments. Or consider a Kubernetes cluster that spins up hundreds of pods daily, each requiring its own service account. These scenarios mostly happen in active, running systems, and traditional IAM methods aren’t designed to handle the scale or dynamic nature of machine identities. You can’t manually approve or track every identity being created and used at this pace.

To secure your pipelines and infrastructure, identity and access controls must adapt to these dynamic environments. For example, every new service account should be logged and automatically assigned least-privilege permissions as it’s created. Frameworks such as SOC2, ISO 27001, and HIPAA mandate this level of control and visibility as part of modern compliance requirements.

Therefore, your DevSecOps team must enforce proactive security measures, apply security patches to actively used identities when needed, and ensure each identity is properly configured before it interacts with production systems. To do this effectively, they need to adopt industry-standard best practices that promote better machine identity hygiene.

Best practices for maintaining cyber hygiene in the age of NHIs

Here are some of the best practices your team must follow for maintaining good cyber hygiene, especially as NHIs continue to grow across your workflows.

• Use short-lived secrets instead of static credentials: Avoid long-lived secrets that persist beyond their intended use. For example, allow your CI/CD pipeline to request a short-lived API key for deployments, which automatically expires after the job completes.
• Rotate secrets after deployments, not just on a fixed schedule: For sensitive environments, rotate secrets shortly after deployment events. This reduces the risk of leaked credentials from earlier stages persisting into production.
• Scope each identity to its environment and task: Ensure every NHI is restricted to only the environments and resources it needs. Avoid broad access policies, even in development and staging environments.
• Maintain activity logs and visibility for every identity: Track which service uses each identity, when, and where. This provides the visibility needed to detect issues and respond effectively.
• Implement monitoring and anomaly detection: Monitor identity usage for unusual patterns, and configure alerts to flag potential breaches early.

Security hygiene practices every DevSecOps team should adopt to control machine identity sprawl.

Following these best practices will help reduce your attack surface and contain risks before they escalate. Of course, implementing this manually across pipelines and environments would be a challenging task. This is where dedicated secrets management platforms, like Doppler, help enforce these controls automatically.

How Doppler helps DevSecOps teams manage machine identities and access controls

Doppler enables DevSecOps teams to manage NHIs centrally, giving them the ability to apply security controls consistently across environments without slowing deployments or pipeline releases.

With Doppler's secrets management solution, DevSecOps teams can:

• Centralize and scope secrets in a secure, single source of truth, storing them by environment (development, staging, production). They can also group them into custom configs, such as prod_k8s_config or prod_cloud_config, so staging API keys never appear in production jobs.

Doppler dashboard showing secrets grouped by environment and config.

• Automate secret rotation and enforce TTLs for credentials by triggering rotation after deployments, on a schedule, or on demand. Once the job completes, they can also expire credentials used in ephemeral jobs like CI/CD builds or Kubernetes workloads.
• Issue short-lived dynamic secrets that expire after use, supporting use cases like generating temporary service account tokens for container builds or creating a 15‑minute database password for a migration job.
• Stream secrets directly into workflows by syncing with cloud-native tools like AWS, GCP, Kubernetes, serverless functions, and CI/CD platforms like GitHub Actions or CircleCI. This allows secrets to be injected into jobs without ever being stored in a repository.
• Maintain full audit trails for every access event to support compliance requirements like SOC 2, ISO 27001, and HIPAA, while applying least‑privilege policies so identities are always scoped to their intended tasks.

Doppler activity log showing recent access events and secret usage.

These capabilities help DevSecOps teams embed security into their workflows while keeping secrets usage organized and auditable. As part of a broader DevSecOps culture, pairing Doppler with regular security awareness training ensures that teams not only use secrets correctly but also understand the risks involved in mishandling them. When teams understand these risks, the next step is action.

Keep machine identity sprawl from becoming a security liability

In this age of automation and cloud-native innovation, the volume of machine identities will only continue to soar. That part is inevitable. What you can control is how securely they’re managed and used. But don’t rely on manual processes; adopt a secrets management tool that automates the work for you.

Doppler helps with this by providing your DevSecOps teams with centralized secret storage, automated secret rotation and expiration, audit logs, and smooth integration with tools your workloads rely on.

Try using Doppler today to get ahead of the sprawl.

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