DevSecOps guides for AI workloads

TL;DR:

• This hub indexes tested defensive guides for AI agents, MCP servers, and AI coding tools.
• The highest-value controls are secret scanning, immediate credential rotation, and least-privilege token scoping.
• Start with the emergency secret-leak remediation guide if you have an active exposure.
• For ongoing hardening, work through least privilege for AI agents and the AI agent hardening checklist.

What does DevSecOps for AI workloads actually cover?

DevSecOps for AI workloads is the discipline of building security controls into how AI agents, MCP servers, and coding assistants are designed, deployed, and run. AI workloads expand the attack surface in three specific ways. Agents act autonomously, so a single over-scoped token can be abused at machine speed. AI coding tools read and write source repositories, which is exactly where leaked secrets tend to live. MCP servers broker tool access, so a weak permission boundary there exposes every connected tool. The guides below treat each of those risks as a separate, testable problem.

Our editorial approach is hands-on. Where a guide claims a tool works, we run it first and note the date and method. Numeric findings in these guides are framed as illustrative examples for orientation, not as audited benchmarks of your environment.

Which guide should I read first?

Read the guide that matches your current risk, not the one that looks easiest. If a credential is already public, rotation is an emergency and everything else waits. If you are building or reviewing an agent, permission scoping is the highest-leverage preventive control. The table below maps topics to difficulty and the situation each guide is for.

Guide	Topic	Difficulty	Read it when
Committed a secret to GitHub, now what	Emergency secret remediation	Intermediate	A key, token, or password is in a public or shared repo
Least privilege for AI agents	Scoped tokens and permission boundaries	Intermediate	Designing or reviewing an autonomous agent
AI agent hardening checklist	End-to-end agent hardening	Beginner	You want a single pass/fail audit list
OWASP LLM Top 10 explained	Threat model reference	Beginner	Mapping risks to a recognised framework
Security tooling directory	Scanners and guards	Beginner	Choosing a secret scanner or guard tool

How do these guides relate to the OWASP framework?

Every guide here maps back to a named risk in the OWASP LLM Top 10 and the wider OWASP GenAI security project. Secret leakage and over-scoped agents are not abstract worries; they are documented categories with established mitigations. Using a shared vocabulary means a finding in one guide can be cross-referenced against the framework, which makes audits faster and reporting clearer for stakeholders who already know OWASP.

For the tooling that underpins the scanning guides, the security tooling directory lists the open-source scanners we test with, including gitleaks and TruffleHog.

What are the core defensive controls, in order?

The controls follow a deliberate priority order: rotate, scope, scan, verify. Getting this order wrong is the most common mistake we see. Teams reach for a history rewrite before rotating, which leaves the live credential valid the entire time the rewrite runs.

1. Rotate exposed credentials first. A leaked secret is compromised the moment it is public; removing it from history does not un-leak it. See the secret remediation guide.
2. Scope every token to least privilege. An agent should hold the narrowest permission set that still lets it do its job, with short lifetimes. See least privilege for AI agents.
3. Scan continuously for new leaks. Run a secret scanner in pre-commit and in CI so the next leak is caught before it merges.
4. Verify the fix. Confirm rotation, history purge, and scope changes actually took effect across all clones, forks, and caches.

How do we test these guides?

We run each remediation on a disposable repository or sandbox account before publishing, and we date every test note. Methodology in brief: we create a controlled exposure, attempt the documented fix with current tool versions, and record whether the leak survives in clones, the provider cache, or pull-request history. We never publish a step we have not executed. For destructive operations such as history rewrites, we follow the official GitHub guidance on removing sensitive data from a repository and cross-check against NSA and CISA hardening guidance where it applies.

Where do I go next?

Pair this hub with the lateral references that match your task. For a single audit pass, use the AI agent hardening checklist. For tool selection, see the security tooling directory. For framework alignment, read the OWASP LLM Top 10 breakdown. Every guide in this index links back here, so you can always return to choose the next control to harden.