JMjmsmtn·Sep 17, 2025Submission
GuardDog is a CLI tool to Identify malicious PyPI and NPM packages
3 points · Open discussionDataDog
guarddog
Python2022–2025
DataDog / guarddog
guarddog
:snake: :mag: GuardDog is a CLI tool to Identify malicious PyPI and npm packages
3Distinct people
3Mentions
0Explicit recommenders
1.3KGitHub stars
What to know before exploring
What it is
:snake: :mag: GuardDog is a CLI tool to Identify malicious PyPI and npm packages
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year3 dated mentions
Observed mentions: 2022-11-15 20:38:24 UTC to 2025-09-17 18:46:33 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 1 | 1 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
3 sourcesI've been very cautious the last couple of years due to these bad actors when looking at packages that might suit my needs. If there is no online presence of the source code (git anything, zips/gzs, etc), multiple packages submitted in a short time frame, or a greater than normal amount, an/or a derivation/plugin of a popular package it's usually a no-go.
For those that I do possibly trust, I then download the package (pip download) and review it. Doing a quick regex for URLs or exec() calls helps, but I probably should use something like guarddog (https://github.com/DataDog/guarddog)
In PyPI new user and new project registrations temporarily suspendedIdentify malicious PyPI packages using static analysis and metadata heuristics
2 points · Open discussion