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Introduction:
The traditional cybersecurity image of a “privileged user”—a human system administrator in a hoodie—has become a dangerous liability. According to CyberArk’s latest Identity Security Threat Landscape research, 61% of organizations still define privileged users strictly as humans, despite the fact that 68% admit that up to half of their machine identities can access sensitive data. This disconnect creates a critical attack surface where non-human identities, from CI/CD pipelines to API keys, operate with elevated privileges outside the governance of standard Privileged Access Management (PAM) programs. As we move further into 2026, securing these machine identities is no longer optional; it is the defining challenge of identity security.
Learning Objectives:
- Understand the distinction between human and machine identities and why the latter requires a dedicated security strategy.
- Learn how to discover, inventory, and classify machine identities across hybrid cloud and on-premises environments.
- Implement technical controls for vaulting, rotating, and enforcing just-in-time access for secrets, tokens, and service accounts.
You Should Know:
- Redefining the Perimeter: Auditing Your Current “Invisible” Privilege
Before you can secure machine identities, you must first find them. The issue is that these identities are often scattered across CI/CD tools (Jenkins, GitLab), cloud provider IAM roles (AWS, Azure), and application configuration files. Attackers exploit these because they are rarely rotated and often have permissions far exceeding their functional requirements.
Step‑by‑step guide: Discovery and Inventory
This process involves using a combination of native cloud tools and open-source utilities to build a comprehensive map.
- Linux/macOS (Local Discovery): Use `find` and `grep` to locate potential hard-coded secrets in configuration files.
Find files containing common secret patterns (cases insensitive) grep -r -i -E "(password|secret|key|token)" /etc /opt /home --include=.{conf,json,yaml,env} 2>/dev/null - Windows (PowerShell): Scan for environment variables or stored credentials.
List all environment variables looking for credential patterns Get-ChildItem Env: | Where-Object { $_.Name -match "KEY|TOKEN|SECRET|PASSWORD" } Check for stored credentials in Windows Credential Manager cmdkey /list -
Cloud (Azure CLI): Identify service principals and their permissions.
List all service principals and their associated roles az ad sp list --all --query "[].{displayName:displayName, appId:appId}" -o table For a deeper dive, list role assignments for a specific service principal az role assignment list --assignee <appId> --all
2. Vaulting Machine Credentials: From Hardcoded to Dynamic
Once discovered, the first line of defense is moving secrets from flat files and environment variables into a secure vault. CyberArk Conjur, HashiCorp Vault, or even cloud-native solutions like AWS Secrets Manager are designed for this. This process eliminates long-lived credentials stored in plaintext.
Step‑by‑step guide: Implementing a Secrets Vault (Conceptual with CLI)
The goal is to retrieve a database password at runtime rather than storing it in the application’s code.
- Store the Secret: Using the vault’s CLI, add the secret.
Example using HashiCorp Vault CLI vault kv put secret/myapp/config db_password="SuperSecurePassword123!"
- Configure Authentication: The application (machine identity) must authenticate to the vault. This is often done via an AppRole, Kubernetes service account, or AWS IAM role.
Retrieve a temporary token using an AppRole RoleID and SecretID vault write auth/approle/login role_id="<role-id>" secret_id="<secret-id>"
- Retrieve at Runtime: Modify the application startup script to fetch the secret.
!/bin/bash Fetch the password from Vault and export it as an environment variable for the app export DB_PASSWORD=$(vault kv get -field=db_password kv/myapp/config) Start the application java -jar myapp.jar
3. Forcing Rotation: Automating the Machine Identity Lifecycle
The average service account remains unchanged for years, giving attackers a persistent window of opportunity. Modern PAM for machines requires automated, frequent rotation without downtime.
Step‑by‑step guide: Automating Password Rotation for a Service Account
This example outlines a process using PowerShell to rotate a Windows Service account password, assuming the application supports pulling the new password from a vault.
- Generate a New Password: Use PowerShell to create a cryptographically secure password.
Add-Type -AssemblyName System.Web $newPassword = [System.Web.Security.Membership]::GeneratePassword(16, 3)
2. Update the Active Directory Account:
Set-ADAccountPassword -Identity "svc_webapp" -NewPassword (ConvertTo-SecureString $newPassword -AsPlainText -Force) -Reset
3. Store in Vault and Update Service: Push the new password to the vault and trigger a service restart to read the updated credential.
Assuming a hypothetical CLI tool 'cyberark-cli' cyberark-cli account update -a svc_webapp -p $newPassword Restart-Service -Name "WebAppService"
4. Just-in-Time (JIT) for Pipelines: Zero Standing Privileges
The principle of Zero Standing Privileges (ZSP) applies equally to machines. A CI/CD pipeline (like Jenkins or GitHub Actions) should not have permanent, broad permissions to production. Instead, it should request ephemeral credentials just for the duration of a deployment.
Step‑by‑step guide: Configuring JIT for a CI/CD Job
Using a cloud provider’s CLI, you can assume a role with elevated privileges only when needed.
- GitHub Actions Workflow Example: Request short-lived credentials from AWS before deploying.
</li> <li>name: Configure AWS credentials uses: aws-actions/configure-aws-credentials@v2 with: role-to-assume: arn:aws:iam::123456789012:role/DeployRole aws-region: us-east-1 role-duration-seconds: 900 15 minutes</p></li> <li><p>name: Deploy to Production run: aws s3 sync ./build s3://my-production-bucket
5. Securing API Keys and OAuth Tokens
In SaaS environments, machine identities often manifest as API keys or OAuth apps with delegated permissions. Treating these with the same rigor as user passwords is critical, especially concerning scope creep.
Step‑by‑step guide: Auditing Slack or GitHub OAuth Apps
Most organizations have dozens of integrations with broad scopes.
- GitHub (CLI): List all authorized OAuth apps for an organization and identify their permissions.
Using GitHub CLI gh api /orgs/{org}/installations --paginate For a user, list authorized credentials gh api /user/codespaces/secrets - Mitigation: Review the OAuth scopes. If an integration requests `repo` (full control of code) but only needs to read issues, reinstall it with the minimal scope.
6. Continuous Monitoring: Detecting Anomalous Machine Behavior
Even with vaulting and rotation, a compromised machine identity can be used legitimately. Monitoring for behavioral anomalies—such as a CI job running at 3:00 AM or an API key accessing data from a new geographic location—is the final layer of defense.
Step‑by‑step guide: Setting Up a Simple Anomaly Alert (SIEM Query Concept)
This query assumes logs from cloud providers (like AWS CloudTrail) are ingested into a SIEM.
Example Splunk query for anomalous service account activity index=cloudtrail user=svc_ci_cd_deploy | eval hour=strftime(_time, "%H") | where hour < 6 OR hour > 20 Alert if activity happens outside 6 AM - 8 PM | stats count by sourceIPAddress, eventName, _time | where sourceIPAddress NOT IN ["KNOWN_BUILD_AGENT_IP_RANGE"]
What Undercode Say:
- The Perimeter Has Shifted: The “insider threat” is no longer just a disgruntled employee; it is a misconfigured CI/CD pipeline with a hardcoded AWS key. Security architecture must pivot from protecting “who you are” to protecting “what you are,” treating every API call as an identity that requires verification.
- Convergence is Key: The data shows a critical gap between organizational policy (61% see humans only) and reality (68% have sensitive machine access). This gap exists because PAM and IGA teams often operate separately from cloud and DevOps teams. Closing this gap requires a converged strategy where secrets management, cloud hardening, and traditional PAM report to the same zero-trust framework.
Prediction:
By 2027, we will see the first major data breach attributed not to a stolen human password, but to an expired but still-valid OAuth refresh token for a decommissioned SaaS integration. This will force regulatory bodies to update compliance frameworks (like SOC2 or GDPR) to explicitly mandate governance for non-human identities, treating machine credentials with the same legal and auditing weight as human privileged access. The rise of AI-agents performing actions autonomously will further accelerate this trend, making machine identity the primary identity type on the network.
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Reported By: Deveshmudgal Cyberark – Hackers Feeds
Extra Hub: Undercode MoN
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