CLI that spots fake GitHub stars, risky dependencies and licence traps

In plain words

StarGuard is a command-line tool that analyzes GitHub repositories to detect artificially inflated star counts and identify supply-chain risks. It examines star timestamps to find suspicious spikes, then evaluates the accounts behind those spikes—checking user age, follower counts, contribution history, and profile details—to calculate a Fake Star Index ranging from organic to synthetic. Designed for developers, hiring teams, and organizations making dependency decisions, it helps distinguish genuine project quality from manipulated metrics in a single command.

written from the facts on this page · September 2026

From the sources

CLI that detects fake-star campaigns, dependency hijacks, licence red-flags and other signs of repository risk. Inspired by the “4.5 million fake stars” study, StarGuard helps CTOs, security teams and investors perform fast, automated open-source due-diligence. - m-ahmed-elbeskeri/Starguard

CLI tool to detect fake-star campaigns, dependency hijacks, licence red flags, and other signals of open-source risk. Inspired by the 4.5 million fake stars study , StarGuard helps automate open-source due diligence in seconds. flowchart TD GH[GitHub API] --> Collectors Collectors -->|Star, forks, issues| Analyzers MF[Manifest files] --> Parser Analyzers --> ScoreCombiner Parser --> ScoreCombiner ScoreCombiner -->|Report / Badge / API| Output Loading 🧪 Quick Start Requirements Python ≥ 3.9 GitHub Personal Access Token (for high-rate limits) Run export GITHUB_TOKEN=ghp_xxxxxxxxx # Full scan with star plot python -m starguard.cli pytorch/pytorch --format markdown --plot stars.png #…from github.com

In the maker’s words, at launch

When I came across a study that traced 4.5 million fake GitHub stars, it confirmed a suspicion I’d had for a while: stars are noisy. The issue is they’re visible, they’re persuasive, and they still shape hiring decisions, VC term sheets, and dependency choices—but they say very little about actual quality. I wrote…

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  For the past month, we've been monitoring GitHub's public event stream to catch spam comments and fake stars. Today, the spammers are back. Go check out the damage! You can see the spam comments and which users are posting the spam in real time. Also, here's a post we wrote about how we set it up: https://www.trytrench.com/blog/preventing-spam-and-fake-star...

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  Hey friends! We have built an app for getting insights about your favorite GitHub community using large language models. The app uses LLMs to analyze the GitHub profiles of users who have starred the repository, capturing key details like the topics they are interested in. It takes screenshots of the stargazer's GitHub webpage, extracts text using an OCR model, and extracts insights embedded in the extracted text using LLMs. This app is inspired by the “original” Stargazers app written by Spencer Kimball (CEO of CockroachDB). While the original app exclusively used the GitHub API, this…

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