How to Reclaim Control Over Secrets by Correlating Credentials to Non-Human Identities (NHIs) for Safe and Automated Remediation

Read full article here: https://www.token.security/blog/reclaiming-control-over-secrets-correlating-credentials-to-nhis-for-safe-and-automated-remediation/?utm_source=nhimg

In the age of cloud-native automation and enterprise AI, the explosion of Non-Human Identities (NHIs), such as service accounts, workload identities, ephemeral compute roles, and automation agents — has transformed how organizations operate. Yet, the secrets that power these NHIs remain fragile, scattered, and dangerously disconnected from the identities they serve.

Token Security is addressing one of the hardest and least visible problems in identity security: correlating secrets back to NHIs with high precision, enabling enterprises to remediate exposure confidently and automate security at scale.

The Hidden Risk: Secrets Without Identity Context

In most infrastructures, credentials live without clear ownership or purpose. These credentials, API keys, SSH tokens, passwords, JWTs, enable access but rarely maintain traceability.

When a secret is discovered, security teams often can’t answer:

• Who or what does it belong to?
• What systems depend on it?
• Can it be safely revoked or rotated?

Secrets scanners detect potential credentials but lack the context to understand if a secret is valid, active, or mission-critical.
This creates an environment where keys exist without locks, and secrets remain unmanaged liabilities rather than verifiable identity proofs.

Why NHI Environments Complicate the Problem

In dynamic, multi-cloud, and AI-driven systems, NHIs multiply rapidly:

• Identities are created programmatically and expire unpredictably
• Different teams use fragmented IAM systems with limited visibility
• Credential lifecycles are poorly documented or entirely unmanaged
• There’s no unified trust plane tying secrets to their originating identity

Even when secrets are securely stored in vaults, they lack contextual metadata, ownership, creation history, or intended purpose — leaving security teams with no reliable way to assess risk or enforce governance.

Token Security’s Approach: Building a Secrets-to-NHI Correlation Layer

Token Security is pioneering a correlation layer that maps secrets to the NHIs they authenticate, safely, automatically, and without requiring access to plaintext secret values.

Core Design Principles

• No plaintext secret access: Correlation occurs through metadata, environment tags, and context rather than secret content.
• Machine learning classification: A supervised ML model associates incomplete or unstructured metadata to known identities.
• Multi-source visibility: Data correlation spans vault entries, scan findings, logs, policies, and runtime environments.
• Precision with explainability: Every match includes a confidence score and reasoning trail for auditability.

Data Inputs and Features

• Naming conventions and tag alignment
• IAM ownership and role mappings
• Workload usage and deployment history
• Environment-specific references and runtime metadata
• Temporal correlation between credential creation and identity registration

This process allows Token Security to identify which identity a secret authenticates, understand its downstream impact, and support safe remediation without operational disruption.

Why Traditional Rules Fail — and LLMs Help

Static, rule-based systems relying on tags and naming conventions often fail under real-world complexity. Metadata is incomplete, inconsistent, or missing entirely.

Token Security overcomes this by integrating an LLM-powered classification model trained on diverse vault and environment data.
The model recognizes latent, fuzzy relationships between secrets and identities, even when naming doesn’t match, providing a high-accuracy, environment-agnostic solution for modern infrastructures.

What Correlation Enables

By bridging the gap between secrets and NHIs, organizations can shift from reactive secrets management to proactive, identity-aware governance:

• Safe rotation: Confidently automate or schedule credential rotations without breaking dependencies.
• Intelligent leak triage: Classify found secrets based on associated identity and business impact.
• Vault hygiene: Detect orphaned or unused secrets and safely remove them.
• Identity-linked visibility: Strengthen Zero Trust enforcement by grounding every credential in an authenticated access path.

This evolution transforms secrets management from passive key storage to active, identity-aware security intelligence, a critical advancement for enterprises embracing automation, AI, and large-scale DevOps environments.