Service accounts have quietly become the most common type of non-human account in enterprise infrastructure. Every CI/CD pipeline, microservice, and SaaS integration needs one, and in many organizations they now outnumber human users by an order of magnitude.
Yet while companies pour resources into securing employee accounts with MFA, zero-trust, and regular access reviews, service accounts still get created with static credentials, granted sweeping permissions, and then left unmanaged.
This creates a growing population of non-human identities that operate outside traditional IAM controls, the perfect blind spot for attackers. To secure modern automation, enterprises need to understand how these identities escape visibility and what strategies can bring them under governance.
The Service Account Explosion: How We Got Here
The rise of cloud and DevOps created an identity crisis. Every new microservice and automation script needs an ID to talk to databases and other services. This created an identity “explosion,” with non-human accounts multiplying faster than traditional security models could handle.
The old way of doing things, with HR-style onboarding, managers approving access, and regular reviews, was built for people. Service accounts don’t have a manager to sign off on a request. Developers, under pressure to move fast, often create these identities on the fly, provision them automatically, and replicate them across multiple environments without a centralized system to track them. It’s a Wild West of identities, and frankly, we’re all a bit lost.
The Blind Spots: Where Visibility Breaks Down
Imagine trying to manage all your company’s physical assets, laptops, phones, servers, without a central inventory. Now, imagine they’re scattered across different cities, with each city using a totally different tracking system. That’s the reality of managing service accounts.
- Multicloud mayhem: The real challenge isn’t just managing credentials, it’s that each cloud defines and trusts identities differently. AWS uses IAM roles and STS tokens, Azure relies on service principals and managed identities, and GCP uses service accounts that can authenticate with either legacy JSON keys or modern federated tokens. Each operates within its own trust domain (AWS STS, Azure AD, GCP IAM) with no shared root of trust, making cross-cloud identity verification and consistent least-privilege enforcement nearly impossible without a unifying workload identity layer.
- Developer tool sprawl: It gets worse. Your development teams use their own tools, GitHub Actions, Jenkins, GitLab, each with its own siloed credential store. Credentials get created on the fly to unblock a developer’s workflow, often without the security team even knowing they exist.
- SaaS and legacy labyrinth: And we’re not even done yet. Every SaaS tool you use, from Salesforce to Stripe, has its own unique way of handling API keys and integrations. These identities live completely outside your corporate network, managed through a vendor’s portal. This fragmentation makes comprehensive, centralized management nearly impossible without specialized tooling.
The Over-Privilege Problem: Why Service Accounts Get Too Much Access
Have you ever given a friend a spare key to your house, and then a year later, they still have it even though they’ve moved away? That’s what’s happening with service accounts, but on a massive scale.
In the fast-paced world of DevOps, speed is everything. Developers are under constant pressure to deploy new features. When a service account needs access to a resource, the quickest solution is often to give it broad, even administrative, permissions. This “path of least resistance” ensures nothing breaks, but it creates a massive security risk.
This over-permissioning becomes a cultural problem. A developer gives a new service account admin access for a prototype, that same access goes into production, and six months later, another developer copies that same overly permissive policy as a “template” for a new service. It’s a compounding effect that spreads excessive privileges throughout your infrastructure, turning every single service account into a potential escalation path for an attacker.
The result is a huge gap between what a service account can do and what it actually needs to do. Without automated analysis, you have no way to know if a service account’s permissions are frozen in time, far beyond their original purpose.
Attack Vectors: How Compromised Service Accounts Enable Lateral Movement
Once an attacker compromises a single service account, they’ve found a perfect backdoor into your system. Why? Because these accounts are a goldmine of vulnerabilities.
- Credential exposure is everywhere: Service account credentials are often left lying around in plain sight. They might be hardcoded in application code and checked into version control, baked directly into container images, or stored as long-lived tokens in CI/CD pipelines. This makes it incredibly easy for an attacker to get their hands on a key to your infrastructure.
- No MFA, no problem (for the attacker): Unlike human accounts that are protected by multi-factor authentication and get locked after failed login attempts, service accounts use static tokens that never expire. There’s no extra verification step, so a stolen credential works no matter where, when, or how it’s used.
- The ultimate privilege escalation: With a single compromised credential, an attacker can move freely across your network. An over-permissioned IAM role can grant them administrative access. A Kubernetes ServiceAccount with too many privileges gives them unrestricted access to your entire cluster. These accounts become persistent backdoors that outlive their original purpose, allowing attackers to establish long-term footholds that are nearly impossible to detect.
Detection Gaps: Why Breaches Go Unnoticed
Think about how your security team watches for threats. They’re looking for an employee logging in at 3 a.m. from an unusual location, or someone trying to access files they shouldn’t. They’re looking for human patterns.
But service accounts don’t act like humans. A single service account might make thousands of API calls per hour, authenticate from multiple IP addresses at once, and work around the clock. This behavior would trigger an immediate red flag for a human user, but it’s completely normal for a microservice.
Because of this, traditional security tools like SIEM and UEBA systems are practically useless for monitoring service accounts. They generate a constant stream of “noise” from legitimate automation, leading to alert fatigue. Security teams get so used to seeing these alerts that they start to ignore them, and that’s when a real attack can slip through undetected.
The problem is compounded by a lack of context. Shared credentials make it nearly impossible to pinpoint which specific service is doing what. By the time an analyst investigates a suspicious API call, the ephemeral resource that made it might have already disappeared. Without a clear understanding of what “normal” looks like for these non-human identities, every anomaly detection system either drowns in false positives or misses a genuine compromise entirely.
Modern Governance Strategies: Bringing Service Accounts Under Control
Securing these non-human identities requires a completely new approach. You can’t just apply old security rules to a problem that’s unique to the cloud. The key is to embrace automation, and for that, you need three core strategies:
1. Automated Discovery and Risk Scoring
You can’t secure what you can’t see. The first step is to get a complete, up-to-date inventory of all your service accounts, no matter where they live. This means continuously scanning your AWS, Azure, GCP, Kubernetes clusters, CI/CD systems, and SaaS integrations. Once you have that inventory, you need to prioritize the biggest risks. An unused account with administrative privileges is a much higher priority than a microservice with read-only access.
2. Workload Identity and Just-in-Time Access
Instead of distributing static, long-lived credentials, you can verify a service’s identity and give it temporary access only when it’s needed. For example, a CI/CD job can get temporary cloud credentials that automatically expire as soon as the deployment is done. This eliminates persistent backdoors and drastically shrinks the blast radius if an identity is ever compromised.
3. Policy-Based Control and Monitoring
The goal is to enforce the principle of least privilege automatically. With policy-based access control, you can define exactly what resources a workload can access based on its verified identity. This can be managed centrally, so your security teams can define a policy once and enforce it consistently across all your environments.
Additionally, you need a monitoring system designed for service accounts. Instead of triggering alerts on every API call, a modern system learns what “normal” looks like for each workload and flags only genuine anomalies. This eliminates alert fatigue and allows your team to focus on real threats.
Moving Beyond Service Account Security Theater
Right now, most companies are performing security “theater” when it comes to service accounts. We put on a good show of protecting human identities while the largest and most privileged user population, our non-human identities, operates with minimal oversight. These accounts, with their excessive permissions and static credentials, are a perfect environment for attackers.
The only way to move forward is to stop treating service accounts like a side problem. The solution isn’t more manual work; it’s to embrace automation, temporary access, and a security approach that’s built for the dynamic, automated nature of the cloud.
This means you need comprehensive visibility, automated governance, and security tools made specifically for these non-human identities. A modern workload IAM platform like Aembit helps organizations move beyond static service account credentials.
By verifying workload identity and brokering short-lived, identity-bound access, Aembit enables secretless authentication and centralizes policy enforcement for consistent, auditable control across environments.
