What Is Secrets Management? A Complete Guide for Cloud and AI Environments

Key Takeaways

• KPMG's latest reporting puts non-human identities at 80 to 1 compared with human users, and almost every one authenticates with a secret that has to be stored, rotated, and revoked.
• Stolen credentials remain the most common way attackers get in, according to the Verizon Data Breach Investigations Report, which is why secret leakage sits near the top of the OWASP Non-Human Identity Top 10.
• Secrets management is not just a vault. It is the full credential lifecycle: issuing, scoping, distributing, rotating, monitoring, and retiring every API key, token, and service account key.
• The 2025 Salesloft Drift breach exposed data across more than 700 organizations through stolen OAuth tokens, showing that a single leaked secret can become a supply-chain incident.

Quick Answer: What Is Secrets Management?

Secrets management is the practice of securely issuing, storing, distributing, rotating, and retiring the credentials that machine identities use to authenticate to systems and to each other.

In plain terms, it covers four things:

• Keeping secrets out of code, config files, and chat logs, and in a controlled store instead.
• Giving each secret the narrowest scope and the shortest life that still lets the workload do its job.
• Rotating and revoking secrets on a schedule, and immediately when something looks wrong.
• Knowing who owns every secret, what it can reach, and whether it is still in use.

Secrets Management at a Glance

The fastest way to understand the discipline is to map each common failure to what it means and how to address it.

You run dozens of services that talk to AWS, GitHub Actions, Snowflake, and a growing set of AI tools. Each one authenticates with a secret: an API key, a database password, a service account key, or an OAuth token. Those secrets now outnumber your people by about 80 to 1, according to KPMG's 2026 cybersecurity reporting, and most of them were created in a hurry and never reviewed. That gap is where breaches start.

What Does Secrets Management Actually Cover?

A secret is any credential that proves a machine identity is who it claims to be. That includes API keys, database passwords, OAuth client secrets, signing keys, TLS private keys, and service account keys in cloud platforms. Secrets management is the set of controls that governs those credentials from creation to retirement.

The discipline is broader than a password vault. A vault solves storage. It does not, by itself, tell you that a key has not been used in 90 days, that a token is scoped far wider than the workload needs, or that the same credential is shared across five pipelines. Those are governance questions, and they are where most programs fall short.

The OWASP Secrets Management Cheat Sheet is blunt about the core failure mode: long-lived secrets are the problem. Yet most enterprises still have thousands of API keys sitting in Git history, CI jobs, and serverless environment variables. Rotation is theoretical, revocation is manual, and attribution is a guess.

Why Has Secrets Management Become Harder in Cloud and AI Environments?

The population changed. A decade ago, a security team could inventory its service accounts in a spreadsheet. Today every workload gets its own identity, every SaaS tool issues OAuth apps, and every AI agent that calls a tool needs a credential to do it. KPMG's 2026 cybersecurity reporting puts the ratio of non-human to human identities at 80 to 1, with nearly 99 percent of identities being non-human.

AI tooling accelerated the trend inside 18 months. An agent that reads a ticketing system and writes to a database holds credentials and acts on its own. The usual shortcut is to hand it a broad, long-lived key because nobody has designed a proper identity for it yet. That is the same mistake the industry made with service accounts, compressed into a much shorter window.

Scale breaks the old manual habits. You cannot review thousands of credentials by hand, and you cannot rely on the engineer who created a key in 2023 to remember it exists after they have left. Machine identity credentials need governance that runs continuously, not a quarterly audit.

How Do Leaked Secrets Turn Into Breaches?

Stolen credentials are the most common initial access vector year after year in the Verizon Data Breach Investigations Report. A secret is a bearer token: whoever holds it can use it, and the log line looks identical whether the caller is your pipeline or an attacker who copied the key.

The 2025 Salesloft Drift incident is the clearest recent example. According to Google Threat Intelligence Group, attackers stole OAuth tokens tied to the Drift integration and used them to query Salesforce data across more than 700 organizations, then combed the stolen records for further secrets like AWS keys and Snowflake tokens. One set of leaked credentials became a supply-chain breach affecting hundreds of companies.

This pattern maps directly to the OWASP Non-Human Identity Top 10, where secret leakage and long-lived secrets both rank among the leading risks. The financial impact is consistent too: the IBM Cost of a Data Breach Report has repeatedly tied identity-related breaches to higher remediation cost and longer dwell time than other vectors.

What Does Good Secrets Management Look Like?

Keep Secrets Out of Code

The first control is to remove secrets from places they were never meant to live: source code, container images, config maps, and CI logs. Store them in a managed secret store, inject them at runtime, and scan repositories and images so a committed key is caught before it reaches production.

Default to Short-Lived Credentials

Every workload identity should get ephemeral credentials, scoped to a task and expiring in minutes. OIDC federation, cloud workload identity, and Kubernetes service account tokens bound to pods all support this. The goal is simple: a leaked token should be worthless within the hour. This aligns with NIST SP 800-207, which treats trust as something evaluated per request rather than granted once.

Govern the Full Credential Lifecycle

Credential lifecycle management is the part most teams skip. Every secret should carry an owner, a purpose, and an expected lifetime at creation. Intent-based cybersecurity applies the same discipline to secrets: each credential should exist only for the purpose it serves. Rotation should run on a schedule and fire automatically when a credential is exposed. When the workload behind a secret is decommissioned, the secret should be retired with it, without a human having to remember.

Right-Size API Key Permissions

API key management is not only about storing keys safely. Most keys are over-scoped because they were provisioned to unblock a deploy. Scope each key to the specific actions the workload performs, monitor real usage, and revoke access that has gone unused. A key that can read an entire data warehouse when it only needs one table is a standing liability.

Where Do Service Account Keys Fit In?

Service account keys are among the riskiest secrets in any cloud estate. A single service account running a nightly job can carry more standing privilege than any person on the team, and its key is often a long-lived credential stored in a pipeline. When that key leaks, the attacker inherits everything the account can do.

The OWASP NHI guidance calls out improper offboarding and long-lived secrets as distinct risks for exactly this reason. Service account keys outlive the projects that created them, accumulate permissions, and rarely get rotated. Treating them as first-class identities, with owners and review dates, is what separates a governed estate from a sprawling one.

How Token Security Approaches Secrets Management

The Challenge

A vault stores secrets well. It does not tell you which of those secrets are over-scoped, which have not been used in months, which are duplicated across pipelines, or which belong to a workload that no longer exists. Most programs end up with strong storage and weak governance, which leaves the riskiest credentials invisible.

The Approach

Token Security is built for machine identities rather than retrofitted from human IAM. The platform runs continuous discovery of every non-human identity and its secrets across cloud, SaaS, CI/CD, identity providers, secret vaults, Kubernetes, and AI tooling, then correlates each secret to its owner, its permissions, and its runtime behavior. The model follows three steps:

• Discover: a live inventory of every secret and the identity it authenticates, including credentials that never appeared in the vault.
• Understand: entitlement mapping, blast-radius analysis, and behavioral baselines, so over-scoped and unused secrets stand out.
• Enforce: automated remediation and lifecycle governance that rotates, scopes down, or retires credentials based on real usage.

The Outcome

Secrets are governed as identities, not just stored as strings. The credentials behind the 80-to-1 majority get the same owner, scope, and review discipline that human access has had for years.

How Security Teams Put This Into Practice

Getting Discovery and Reducing Operational Load

Discovery is the prerequisite for every other control. You cannot rotate, scope, or retire a secret you do not know exists. The team at GEHA described the shift directly after adopting continuous discovery for its secrets and API keys.

"We've been using Token Security for the past few months, and it has significantly streamlined how we manage and secure our secrets, API keys, and other NHIs. The platform's visibility and discovery capabilities have helped us detect new and hidden risks while reducing operational overhead. With simple integration and quick time to value, Token Security has been a game-changer for our security operations!"
— Eric Ullmann, Director Information Security at GEHA

The point that maps back to secret management is hidden risk. Most leaked or over-scoped credentials are not on anyone's radar until discovery surfaces them, and surfacing them without adding operational load is what makes the control usable day to day.

Turning Findings Into Action Without Alert Fatigue

Finding risky secrets is only useful if the signal is clean enough to act on. Security teams drown when a tool reports thousands of low-value findings. Lemonade described this signal-to-noise problem specifically.

"Token Security has enhanced our security by providing us accurate and relevant visibility into machine identity risks, something I have yet to see from other vendors. It's the first service I've seen that delivers on the widely-made claim of finding machine identity risk. It provides us with the right amount of detail to mitigate issues without burdening us with tens of rows of useless alerts."
— Jonathan Jaffe, CISO at Lemonade

For secrets management, the lesson is that prioritization matters as much as detection. A program that flags every credential equally is noise. One that ranks by blast radius and real usage is a control that teams will actually run.

Why Non-Human Identities Require a New Security Model

Secrets management is no longer a storage problem. It is an identity problem. Every API key, token, and service account key is the credential behind a machine identity, and those identities now make up the overwhelming majority of an environment. Securing them means governing the full lifecycle of their secrets: issuing narrowly, rotating reliably, monitoring continuously, and retiring on time.

The organizations that get this right stop treating secrets as static strings in a vault and start treating them as living credentials attached to identities that have owners, purposes, and expiry. That shift, applied to the 80-to-1 majority, is what closes the gap attackers keep walking through.