Security Score for Non-Human Identities

A security score for non-human identities is a quantifiable metric used in cybersecurity to evaluate the risk level, security posture, and overall hygiene of machine-based credentials. These identities include service accounts, API keys, OAuth tokens, certificates, and secrets that applications, workloads, and devices use to communicate programmatically with other systems. The score provides security and risk management teams with a clear representation of how vulnerable these automated identities are to exploitation, allowing organizations to prioritize remediation efforts based on actual risk.

Understanding Non-Human Identities (NHIs) in Cybersecurity

In modern cloud computing and microservices architectures, non-human identities vastly outnumber human users. Whenever a cloud workload, automated deployment script, continuous integration pipeline, or third-party application needs to access a database or internal service, it utilizes a non-human identity to authenticate.

Because these machine identities operate entirely in the background and fundamentally cannot support traditional human-centric security controls—such as biometric verification or interactive multi-factor authentication (MFA)—they present a unique and expanding attack surface that requires specialized continuous monitoring and scoring.

Key Factors That Determine a Non-Human Identity Security Score

Calculating a robust security score requires continuously analyzing the lifecycle, configuration, and behavioral patterns of machine identities. Modern cybersecurity platforms evaluate several critical parameters to generate this score:

• The Principle of Least Privilege: The system evaluates whether the identity possesses only the exact permissions necessary to execute its function. Identities with excessively broad or administrative access are flagged as high risk, significantly lowering the score.

• Credential Age and Rotation: The score accounts for how long an API key, certificate, or secret has been active. Stale credentials that bypass organizational rotation policies are highly vulnerable to compromise.

• Usage and Dormancy: The system tracks the identity's activity levels. Orphaned or dormant service accounts belonging to decommissioned applications that remain active provide attackers with an unmonitored backdoor, severely penalizing the security score.

• Exposure and Storage: The score assesses where and how the identity's credentials are kept. Credentials securely stored and dynamically retrieved from an encrypted vault yield a high score, whereas secrets hardcoded in plaintext in source code or configuration files result in a critical score reduction.

• Behavioral Anomalies: The score dynamically adjusts based on runtime behavior. If a service account that normally accesses a specific database at scheduled intervals suddenly attempts to read sensitive files from an unusual geographic IP address, the score drops immediately to reflect the active threat.

Why Scoring Non-Human Identities is Critical for Risk Management

Threat actors have shifted their focus toward non-human identities because they often hold highly privileged access to critical infrastructure and data repositories. A single compromised API key or exposed OAuth token can allow an attacker to bypass the traditional network perimeter entirely, leading to catastrophic data breaches.

By assigning a dynamic security score to these automated identities, organizations transition from a reactive security posture to a proactive one. This scoring framework enables security operations centers (SOC) and identity and access management (IAM) teams to quickly identify over-privileged accounts, enforce automated secret rotation policies, and aggressively eliminate dormant credentials before they can be exploited in lateral movement campaigns or supply chain attacks.

Frequently Asked Questions (FAQs)

What is the difference between human and non-human identities?

Human identities belong to actual people, such as employees, contractors, or customers, who log in to systems interactively using usernames, passwords, and multi-factor authentication. Non-human identities belong to machines, applications, bots, or services that authenticate programmatically using API keys, tokens, or digital certificates without any human intervention.

How do you improve a non-human identity security score?

To improve the security score of machine identities, organizations should integrate automated secret management solutions, strictly enforce least-privilege access models, eliminate long-lived static credentials in favor of short-lived dynamic tokens, and actively audit and decommission any dormant or unused service accounts.

What are the biggest security risks associated with non-human identities?

The primary risks include the accidental leakage of hardcoded secrets in public source code repositories, the granting of overly permissive access rights, the inherent inability to use interactive multi-factor authentication, and the sheer, unmanaged volume of these automated accounts. Attackers actively exploit these vulnerabilities to move laterally and escalate privileges undetected within cloud environments.

Securing Non-Human Identities Using ThreatNG

Non-human identities, such as API keys, service accounts, OAuth tokens, and digital certificates, form the invisible backbone of modern cloud computing and automated software supply chains. Because these machine identities operate continuously and often possess highly privileged access to sensitive data, they have become a primary target for cybercriminals. Securing them requires an organization to achieve complete visibility over where these credentials operate and where they might be leaking onto the public internet.

ThreatNG serves as an advanced, agentless External Attack Surface Management (EASM) and Digital Risk Protection (DRP) platform. By autonomously discovering exposed infrastructure, deeply assessing API endpoints, calculating specific security ratings, and investigating public code repositories, ThreatNG provides the intelligence required to secure non-human identities before they can be exploited.

Agentless External Discovery of Machine Identity Perimeters

Before an organization can secure its non-human identities, it must discover every external endpoint, cloud bucket, and application programming interface (API) where these identities are used. Forgotten digital assets often house dormant or unsecured machine credentials.

• Connectorless Reconnaissance: ThreatNG maps the global internet to discover an organization's complete digital footprint without requiring internal network access, software agents, or API keys. It identifies the exact external web applications and cloud instances that rely on automated machine-to-machine communication.

• Patented Recursive Discovery: ThreatNG utilizes a self-expanding discovery engine to uncover hidden subdomains, shadow IT, and undocumented staging environments. By identifying a forgotten developer portal, ThreatNG ensures the security team can secure it before attackers extract the service account credentials embedded within it.

Deep External Assessment and the Non-Human Identity Security Rating

Once the external perimeter is mapped, ThreatNG conducts rigorous, unauthenticated external assessments. A defining feature of this process is ThreatNG’s proprietary Non-Human Identity Security Rating, which quantifies the specific risks associated with exposed machine credentials and the infrastructure that houses them.

• Evaluating API and Credential Security: ThreatNG assesses external-facing APIs, web services, and cloud gateways to evaluate their authentication mechanisms, rate-limiting controls, and encryption standards. It translates these findings into an objective Non-Human Identity Security Rating (graded A through F).

• Detailed Assessment Example (Exposed API Tokens): An organization deploys a new customer support portal that relies on an external API to fetch user data. ThreatNG’s discovery engine maps this new endpoint, and the external assessment module probes it. The assessment discovers that the API does not enforce strict rate limiting and, critically, passes static, long-lived authentication tokens in plain text within the URL query string rather than in a secure HTTP header. ThreatNG immediately downgrades the asset's Non-Human Identity Security Rating to a critical failing grade. It flags the exact misconfiguration, allowing the engineering team to rewrite the API to use secure, short-lived tokens in the authorization header before an external attacker can intercept the URL and steal the machine identity.

Deep-Dive Investigation Modules for Credential Leakage

The most severe risk to non-human identities is human error. Developers frequently hardcode secrets into scripts or configuration files, accidentally exposing them to the public. ThreatNG deploys highly specialized investigation modules to actively hunt for these leaked machine identities across the open and deep web.

• Detailed Investigation Example (Sensitive Code Exposure): Developers working on a cloud integration project temporarily hardcode a highly privileged Amazon Web Services (AWS) Identity and Access Management (IAM) access key into a configuration script to bypass local testing errors. An engineer accidentally commits this script to a public GitHub repository. ThreatNG’s Sensitive Code Exposure module, which continuously interrogates public repositories and developer forums, detects this commit instantly. The module captures the repository URL, the commit timestamp, and the exposed plaintext AWS key. ThreatNG generates an immediate critical alert, providing the precise forensic evidence the security team needs to revoke the AWS key and generate a new one, neutralizing a catastrophic cloud breach before automated scraping bots can harvest the credentials.

Continuous Monitoring and Intelligence Repositories

Because developers deploy code multiple times a day and cloud infrastructure scales dynamically, securing non-human identities requires continuous, automated vigilance.

• Tracking Configuration Drift: If an administrator accidentally alters a cloud policy, making a previously secure directory containing digital certificates accessible to the public internet, ThreatNG detects this configuration drift in real time. It pushes an immediate alert to secure the directory before the certificates are compromised.

• Curated Intelligence (DarCache): ThreatNG cross-references all discovered machine identity exposures against DarCache, its operational intelligence data store. If ThreatNG discovers a leaked service account password on a dark web forum, it correlates this data against known threat actor profiles to determine if the leak is part of an active, targeted campaign.

• Exploit Chain Modeling (DarChain): ThreatNG uses its DarChain engine to visually map how an attacker could combine a leaked API key with an unpatched external vulnerability to pivot laterally and execute a massive data exfiltration attack.

Standardized Reporting for Identity Governance

• Audit-Ready Deliverables: ThreatNG consolidates its continuous telemetry into structured Executive and Technical reports. These reports highlight the organization's Non-Human Identity Security Rating, providing verifiable proof to leadership and compliance auditors that machine credentials are mathematically evaluated and actively protected.

• Correlation Evidence Questionnaires (CEQs): ThreatNG verifies the ownership of every discovered asset and leaked credential against global registries, ensuring that security teams spend time only revoking keys and tokens that actually belong to their organization.

Cooperation with Complementary Solutions

ThreatNG's robust API architecture functions as an automated external intelligence engine, cooperating seamlessly with enterprise defense platforms to secure non-human identities at machine speed.

• Cooperation with Secrets Management Complementary Solutions: When ThreatNG’s investigation modules discover an exposed API key or database token in a public code repository, they feed this verified intelligence directly to Secrets Management complementary solutions. These systems cooperate to immediately identify which application owns the compromised secret, disable that application, and dynamically inject a newly generated secure key into the production environment.

• Cooperation with SOAR Complementary Solutions: If ThreatNG detects a leaked service account credential on a dark web marketplace, its zero-latency API sends an immediate signal to Security Orchestration, Automation, and Response complementary solutions. The SOAR platform executes an automated playbook that instantly revokes the compromised service account within the cloud environment and blocks any external network traffic attempting to use it.

• Cooperation with Cloud Security Posture Management (CSPM) Complementary Solutions: ThreatNG continuously feeds its dynamically updated inventory of external APIs and shadow cloud infrastructure into CSPM complementary solutions. This cooperation ensures that the CSPM actively evaluates the internal configurations of the exact cloud assets that ThreatNG has verified are exposed to the public internet, providing a unified defense for machine identities from the outside in.

• Cooperation with Identity and Access Management (IAM) Complementary Solutions: ThreatNG shares its external assessment data regarding weak authentication gateways with IAM complementary solutions. If ThreatNG identifies an exposed portal that lacks strict authentication for machine access, the IAM platform cooperates by enforcing adaptive, risk-based access policies that block programmatic logins originating from untrusted geographic IP addresses.

Frequently Asked Questions (FAQs)

What makes up a Non-Human Identity Security Rating?

ThreatNG calculates this rating by evaluating the external posture of the infrastructure housing machine credentials. It factors in the presence of exposed API keys, the use of insecure authentication protocols, the absence of rate-limiting controls on automated endpoints, and the historical frequency of sensitive code leaks in public repositories.

How does ThreatNG find exposed API keys and secrets?

ThreatNG utilizes a specialized Sensitive Code Exposure investigation module that continuously scans and interrogates public code repositories, developer forums, and paste sites. It searches for specific file extensions, variable names, and string patterns associated with hardcoded passwords, cloud infrastructure tokens, and cryptographic keys.

Why is external discovery important for securing service accounts?

Service accounts are only as secure as the infrastructure they inhabit. If an organization has a forgotten, unmanaged staging server (shadow IT) that uses highly privileged service accounts to connect to the main database, attackers will target that vulnerable server. External discovery finds these hidden servers, allowing the organization to decommission them and eliminate the backdoor before the service accounts are compromised.