GitHub security

Authorize once, and Mooth maps the risks across your whole code-hosting and CI/CD environment: explained, prioritized, and fixable in one click.

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Give your whole dev environment its own AI security officer.

You can't fully see your own GitHub

You're shipping fast, and when you lean heavily on AI-assisted coding, code, secrets, config, dependencies, and permissions pile up every day. The risk isn't in just one repo — it's scattered across every corner of your dev environment:

  • A secret committed in a hurry and never removed, still sitting in some repo's history
  • Dozens or hundreds of repos, with no one able to say who can change what, who the outside collaborators are, or whether branches are protected
  • One poisoned package among the many you installed
  • A CI/CD pipeline wired to deploy credentials, where the pipeline's own config is the risk
  • Permissions you set up for Claude Code or Cursor, without ever thinking the config itself could be exploited
  • News of secret leaks and supply-chain poisoning that leaves you uneasy, with no idea where to start

Off-the-shelf scanners either watch only a single repo's code and bury you in hundreds of alerts, or have no "whole organization" view and miss the new risks of the AI era. The worst part: you can't tell which findings will actually bite, let alone where the real weak point in your whole dev environment is.

That's exactly what Mooth solves.

Four steps to see your whole dev environment

1

Authorize GitHub

Read-only access, one minute, revocable any time. Organization or personal repos both work.
2

Mooth runs a full checkup

Covers org and member permissions, each repo's code and secrets, dependency supply chain, CI/CD pipelines, and dozens of risk types — no configuration needed.
3

Get a report you can actually read

The truly dangerous findings on top, each explaining how it can be exploited, the real impact, and how to fix it.
4

Open a fix PR in one click

For anything auto-fixable, Mooth generates the fix PR — you click once to resolve it.

From authorization to report usually takes only a few minutes. Try it free once and see what's actually in your dev environment.

What Mooth focuses on

Not just scanning a single repo's code, but mapping your whole code-hosting and CI/CD environment together:

Risk layerTypical issueSeen in the wild
Org & permissionsOver-broad member permissions, unmanaged outside collaborators, missing branch protection, 2FA offAccount compromise leading to stolen code and credentials
Secret & credential leaksPlaintext keys and hardcoded fallbacks in code, config, historyToyota key leak
Supply-chain poisoningHijacked dependencies, unpinned GitHub Actionstj-actions, the Shai-Hulud npm worm
CI/CD pipelinesInjectable pipeline config, third-party Action risk, exposed deploy credentialsBuild-chain poisoning incidents
AI agent & MCP configAgents allowing dangerous commands, untrusted MCP connectionsAmazon Q plugin injected with a wipe command
Code & dependency flawsExploitable code defects, dependencies with known vulnerabilities

AI agent and MCP config risk is where Mooth is especially strong and where traditional tools are usually blind: a .claude or .cursor config that auto-approves delete, install, or network commands effectively removes the human-confirmation gate from your AI.

What a report looks like

Directly exploitable · Critical — long-lived credentials leaked in code and config

Real impact: usable plaintext keys found in .env.example and .claude config. Anyone with a copy of the repo can reuse them to call third-party services or access your data.

Reference incident: Toyota left a key committed to GitHub for nearly five years, exposing data for about 296,000 customers.

How to fix: rotate the exposed keys, replace .env.example:6 with a placeholder, and remove the hardcoded fallback at razor-local.js:11.

(Mooth can generate the fix PR for you.)

Every finding answers just three things: how it can be exploited, how bad the real impact is, and how to fix it. No jargon, no analysis dump — read it and act.

Why Mooth is different from other scanners

It looks at the whole environment, not just one repo. Risk often hides in org config, member permissions, and CI/CD pipelines, not just in code. Mooth looks from the org layer down to the code layer and tells you where your whole dev environment should be shored up first.

It reports only real problems, already prioritized. Mooth doesn't pile up alerts. Every finding is marked "directly exploitable" or "indirectly exploitable" — what an attacker can hit right now versus what needs a precondition. You immediately know what to fix first.

Every finding comes with a real incident. Not a dry "high severity." Mooth tells you this class of problem actually happened and what it cost — for example secret leaks at Toyota and supply-chain poisoning at tj-actions. You actually understand why it matters.

It catches AI-era risks others miss. Traditional tools still watch the classic playbook. Mooth understands the new risks of AI development and surfaces those dangerous auto-approved configs — risks most tools simply can't see.

It also tells you what not to worry about. Mooth doesn't manufacture anxiety. It will say outright that something looks like a problem but doesn't need escalation in your context, saving you time on irrelevant items.

It doesn't just find problems, it fixes them. Seeing the risk is only half the job. Mooth generates the fix PR, turning "found" into "resolved."

Is your code safe

We know authorizing GitHub takes trust. So:

  • Least-privilege, read-only — Mooth only reads what it needs to analyze, and never changes your code unless you click to generate a PR.
  • Your source code is not retained — analysis runs and leaves; nothing enters any model training.
  • Revocable any time — one click removes access, effective immediately.

See your GitHub now

No configuration, no docs to read. Authorize once and within minutes you get a security report you can read and act on — free the first time. Authorization takes a minute, read-only, revocable any time.