Best AI Chat Apps on GitHub

// How we scan

Before a repository gets a post here we clone it and run the same checks on every one. The scanner is a script in this site's own repository, its findings are written out with file and line, and a person reads every hit before writing the verdict in the post. The last full run was on Oct 28, 2026.

Pinned commit

A fresh clone of the default branch. The commit and date are on every report, so the findings are about one snapshot, not the repository in general.

Secrets

Credential patterns with a known shape: cloud access keys, API tokens for OpenAI, Anthropic, Slack, GitHub, Google and Stripe, chat webhooks, private key blocks.

Suspicious code

Code that decodes a string and then executes it, pipes a download straight into a shell, opens a raw socket to a shell, reaches a known exfiltration service, mines cryptocurrency, or looks packed.

Install-time code

npm lifecycle scripts, setup.py command classes, Cargo build scripts, and installer shell scripts: whether they use sudo, edit your shell profile, or fetch and run remote code.

Committed binaries

Executables and compiled objects identified by their bytes, not their file extension, so a renamed binary still shows up.

CI workflows

GitHub Actions that run on pull_request_target and check out the pull request head (a classic way to leak secrets), write-all permissions, and third-party actions pinned to a tag instead of a commit.

Network hosts

Every host the source code talks to, so an unexpected one stands out.

Known vulnerabilities

Every pinned dependency in the repository's lockfiles looked up in OSV.dev, counted by severity. Includes development dependencies, which is why the counts are not zero for a large web app.

Project hygiene

A security policy, automated dependency updates, CodeQL, a licence, contributing guidelines.

OpenSSF Scorecard

The Open Source Security Foundation's independent score, where the project has one.