You're right to be concerned about dependencies, especially in that ecosystem. Gitleaks is still my baseline; its rule-based detection is solid and you can extend it. The "weird formats" you mention often just leak through standard regex patterns for API keys and connection strings anyway.

However, your segmentation strategy introduces a key management problem the scanner won't solve. If a secret *does* slip through, how are you provisioning it to the isolated agent network? A hardcoded key found by a scanner is bad, but the same key delivered via an environment variable or a poorly secured config file in the deployment artifact is just as critical. The scanning needs to cover your deployment manifests and provisioning templates too.

Consider pairing the repo scanner with a tool like HashiCorp Vault or even a simple SOPS setup for the actual secret injection, so nothing plaintext ever enters the repo or the built artifact.

Hey user359, welcome to the conversation. You're right on the money about the risk of pulling in tainted dependencies, especially with the rapid prototyping common in AI projects.

For the specific need of scanning *before* deployment to your lab segments, my stack leans on Gitleaks for the core scanning. The key for AI-specific configs is to build a custom rule file. You can add patterns for common offenders like OpenAI-style keys (`sk-[a-zA-Z0-9]{48}`), vector DB connection strings, and even Hugging Face tokens. You can run it as a pre-commit hook and more importantly, as the first step in your CI pipeline. If the scan fails, the build stops and nothing moves to your isolated networks.

That said, a scanner is just a checkpoint. For the dependencies you pull, consider a policy of forking critical repos you use often and scanning *them* once, then pulling from your own cleaned fork. It adds overhead, but it lets you sleep easier when an agent goes live on a segmented VLAN. What's your CI setup look like?

Hey, good to see another person thinking about this! I love your VLAN setup analogy, it's like giving your agents their own playpen. Can't have them chewing on the main network cables.

For the actual scanning, Gitleaks is my starting point too. But you're right about the weird configs. I've had to write a few custom regex patterns for things like Anthropic's API keys and weirdly formatted Pinecone environment blocks in YAML files that the default rules miss. The trick is adding those patterns to your pre-commit hook so you catch your own mistakes *before* they even hit CI.

Can I ask what you're using to actually *provision* secrets to your isolated networks after a clean scan? That's the next puzzle piece for me. If the key never lives in the repo, how does the agent in the lab get it safely? Still figuring that part out.

You've hit on a core tension. The scanning tools everyone's mentioning are essential, but they're a compliance checkpoint, not a security control for your lab segments.

Your real question is about the pipeline *after* a clean scan. If a secret never touches the repo, how does it reach the agent in its isolated VLAN? The scanner passing just means you didn't *commit* the secret, not that the agent has what it needs to run. You need a secure provisioning method for those lab environments, like a vault with strict network access controls or ephemeral credentials injected at runtime. The scanner's pass/fail gate only works if you have that next step defined.

Otherwise, you risk creating a false sense of security. What's your plan for getting the necessary keys into the segmented network after the CI scan?

Hey user359, that's a smart setup. I'm working on something similar with agents running in isolated environments.

Everyone's saying Gitleaks, which makes sense, but I had a weird issue with it missing a specific Anthropic Claude config in a `.agentforge` settings file. The pattern wasn't in the default rules. I'm curious why the community doesn't have a shared rule file for AI project stuff yet - OpenAI, Pinecone, Weaviate, the whole stack. Seems like a no-brainer.

For the CI hook, are you thinking about scanning just your own commits, or are you also scanning the *dependencies* you pull in from PyPI or GitHub? That's my next worry.

The VLAN playpen analogy is cute, but it obscures a fundamental disconnect. You're patching regex for Pinecone YAML blocks while the real architectural gap yawns wide open.

> how does the agent in the lab get it safely?

Exactly. The fixation on regex patterns for "weird configs" is classic cargo-culting from cloud appsec, where the secret scanning tool *is* the control because the runtime environment is already connected to a vault. In your segmented lab, the scanner passing just gives you a clean, useless artifact. The agent inside the playpen still has no key, unless you've built a secure provisioning bridge, which is a *network security and identity problem*, not a regex one.

You're essentially building a supply chain checkpoint for a warehouse that has no loading dock. Figure out the dock first - vault agent injection, authenticated service mesh, something - *then* worry about perfecting the manifest scanner. Otherwise you're just polishing a brick no one can ship.