NHI Sprawl
Non-Human Identity (NHI) Sprawl, also known as secrets sprawl or credential sprawl, is the cybersecurity risk associated with the uncontrolled proliferation of machine-based authentication credentials across an organization’s infrastructure. This systemic issue is driven by the exponential growth of non-human identities (NHIs)—such as service accounts, API keys, tokens, certificates, and machine identities—which now often outnumber human users by vast margins in cloud and hybrid environments.
Causes and Characteristics of NHI Sprawl
NHI sprawl is a common and often unavoidable byproduct of modern, automated IT operations, particularly in DevOps and microservices architectures.
Automation and Decentralization: Cloud-native architectures generate credentials for microservices, containers, and serverless functions. Continuous Integration/Continuous Deployment (CI/CD) pipelines spin up temporary, short-lived, or ephemeral credentials for deployment and testing that are often not properly cleaned up or deactivated.
Lack of Governance: NHIs frequently fall outside the established governance lifecycle used for human accounts. This results in credentials lacking clear ownership, no expiration date, and no proper monitoring.
Zombie Identities: NHIs often remain active and privileged long after their intended purpose is fulfilled, creating unmonitored backdoors into critical systems.
Fragmented Storage: Secrets become scattered across code repositories, configuration files, developer workstations, and third-party integrations instead of being stored and managed centrally in a secure vault.
Security Risks of NHI Sprawl
NHI sprawl significantly increases an organization's attack surface and is a leading cause of credential-based breaches.
Initial Access via Leakage: Attackers actively target this sprawl by scanning public platforms (like GitHub, S3 buckets, and developer forums) for exposed secrets. A single hardcoded API key or token, a frequent sign of sprawl, can grant direct, programmatic access to cloud environments, APIs, or databases.
Over-Privilege and Lateral Movement: For convenience, developers often assign overly broad or excessive permissions to NHIs, violating the Principle of Least Privilege (PoLP). If a low-level, exposed credential is then compromised, the attacker can use its excessive permissions to escalate privileges and move laterally within the network, leading to significant data exfiltration.
Compliance Failure: The lack of a unified inventory and inconsistent policy enforcement across these scattered credentials makes it challenging to comply with regulatory frameworks such as HIPAA, SOC 2, and the EU Cyber Resilience Act.
Mitigation Strategies
Mitigating NHI sprawl requires a structured approach centered on visibility and automation:
Discovery and Inventory: Continuously identifying and inventorying all NHIs across the entire cloud and hybrid environment is the foundational first step.
Secrets Vault Adoption: Centralizing all secrets management using a dedicated secret vault, ensuring applications fetch credentials at runtime instead of relying on hardcoding.
Automated Lifecycle Management: Implementing automated processes for secret rotation and prompt decommissioning of unused or zombie NHIs.
Zero Trust and PoLP: Rigorously applying the Principle of Least Privilege and adopting a Zero Trust approach to ensure NHIs only have the permissions necessary, precisely when they need them.
ThreatNG is highly effective at combating NHI Sprawl because its core function is to perform purely external unauthenticated discovery to identify and track the fragmented, leaked, and forgotten machine credentials that constitute this sprawl across the external attack surface.
ThreatNG's Role in Combating NHI Sprawl
External Discovery and Continuous Monitoring
ThreatNG’s External Discovery is ideally suited to finding the symptoms of NHI sprawl, as leaked secrets are often found in publicly exposed locations. It Continuously Monitors the external attack surface , ensuring that the rapid creation and accidental exposure of new machine credentials inherent to DevOps (the root cause of sprawl) are immediately detected and flagged for remediation.
External Assessment and Examples
The platform calculates specific security ratings that are directly impacted by the discovery of credential sprawl:
Non-Human Identity (NHI) Exposure Security Rating: This dedicated metric is the primary measure of NHI sprawl risk. It quantifies the organization's vulnerability to threats originating from high-privilege machine identities (leaked keys, service accounts).
Example: If ThreatNG discovers multiple hardcoded secrets for different services (e.g., an AWS Access Key ID and a Stripe API Key) scattered across various public repositories (via Sensitive Code Exposure) , this directly indicates severe NHI sprawl and significantly degrades the NHI Exposure Security Rating.
Data Leak Susceptibility: Since NHI credentials often grant access to data, their exposure contributes to this rating.
Example: The rating is derived from uncovering external risks across Compromised Credentials and Cloud Exposure (exposed open cloud buckets). Finding an exposed open cloud bucket that a leaked NHI credential could further exploit exacerbates the data leak risk.
Cyber Risk Exposure: This rating includes Sensitive Code Discovery and Exposure (code secret exposure), which is the technical indicator of credential sprawl.
Investigation Modules and Examples
The following investigation modules are essential for mapping the extent of NHI sprawl:
Sensitive Code Exposure: This module directly hunts for scattered secrets across public code, which is the most visible manifestation of sprawl. The Code Repository Exposure submodule finds numerous high-value secrets:
Access Credentials: Including tokens for cloud and third-party services like AWS Access Key ID, Google Cloud API Key, Stripe API key, and Slack Token. Example: ThreatNG finds a hardcoded Heroku API Key in a public development file, identifying an unmanaged credential for a PaaS service.
Security Credentials: Including PGP private key block and RSA Private Key.
Mobile Application Discovery: This module identifies machine credentials hardcoded into mobile applications.
Example: ThreatNG discovers a Twitter Secret Key and a PayPal Braintree Access Token embedded within an organization's mobile app, showing sprawl across different application contexts.
Cloud and SaaS Exposure: This module tracks where NHIs are being used, identifying Unsanctioned Cloud Services and Open Exposed Cloud Buckets. NHI sprawl often occurs when services are spun up outside of central IT oversight.
NHI Email Exposure: This feature groups and tracks exposed role-based email addresses (like system, svc, devops, jenkins ) that are typically associated with NHI service accounts. An attacker uses these addresses as a target for credential stuffing to compromise the corresponding machine identity.
Intelligence Repositories and Reporting
ThreatNG uses intelligence to quantify the danger of the NHI sprawl:
Compromised Credentials (DarCache Rupture): This repository is critical for validating sprawl risk. If a hardcoded credential discovered by ThreatNG is also found in a dark web dump, it confirms the credential has been compromised and escalates the risk of that specific identity.
Context Engine™: The engine delivers Legal-Grade Attribution , converting the chaos of credential sprawl into irrefutable evidence. This certainty helps security leaders justify investments to enforce centralized secrets management and eliminate sprawl.
Complementary Solutions
ThreatNG's external findings on NHI sprawl provide the necessary evidence for internal control enforcement:
Secrets Management Solutions: When ThreatNG discovers a hardcoded credential (e.g., a Twilio API Key or Google Cloud Platform OAuth), this external alert can be automatically sent to the organization's Secrets Management platform. The platform can then use this alert to revoke the exposed key and enforce retrieval of the new credential from the secure vault, thereby forcing centralized management and mitigating sprawl.
Cloud Identity and Access Management (IAM) Systems: The discovery of numerous exposed cloud keys (e.g., multiple AWS Access Key IDs) is shared with the IAM system. The IAM system can then use this data to run an internal audit, identifying which exposed keys are over-privileged or orphaned (no longer tied to an active resource), and automatically enforce the Principle of Least Privilege and key rotation for the NHIs.
Code Repository Platforms: ThreatNG’s detailed report on exposed credentials in a public repository can be shared with the code platform (e.g., GitHub or GitLab). The platform can then use the data to automatically block future commits containing similar secret patterns, preventing the coming proliferation of hardcoded secrets.
