GuardDog
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GuardDog is a CLI tool to Identify malicious PyPI and npm packages
guarddog crates scan serde --output-format=json
guarddog crates verify /tmp/repo/Cargo.lock
guarddog pypi scan requests
guarddog pypi scan /tmp/suspicious.tar.gz --no-sandbox
guarddog npm scan s3://my-bucket/path/to/package/
guarddog pypi scan s3://my-bucket/path/to/package.tar.gz
guarddog pypi scan /tmp/triage.tar.gz --metadata /tmp/triage-metadata.json --output-format json
guarddog npm scan https://github.com/DataDog/malicious-software-packages-dataset/raw/refs/heads/main/samples/pypi/compromised_lib/mistralai/2.4.6/2026-05-12-mistralai-v2.4.6.zip --zip-password infected
echo 'mypassword' | guarddog pypi scan /tmp/suspicious_package.whl --zip-password -
guarddog verify <path>
guarddog pypi scan <package-name> --rules shadylinks
- uses: DataDog/guarddog@v2.5.0
with:
command: verify
package: <package-name>
guarddog --version
guarddog npm scan package.json
guarddog npm scan <package_name>
guarddog pypi scan <package_name> --output-format sarif > report.sarif
guarddog pypi list-rules
guarddog npm scan . && guarddog npm scan --exit-non-zero-on-finding
Summary
GuardDog is an open-source command-line tool that scans PyPI and npm packages, Go modules, Rust crates, RubyGems, GitHub ActionsGitHub ActionsGitHub's built-in CI/CD system that runs automated workflows triggered by repository events, letting cyber tools automate testing, building, and releasing without managing separate pipeline infrastructure., and VSCode extensions for signs of supply-chain attacks, using YARA-based static analysis alongside metadata checks. Rather than flagging every suspicious pattern, it correlates a package's capabilities with threat indicators found in the same file to score actual risk, which its README presents as the distinguishing approach. It is aimed at application security and software supply-chainsoftware supply-chainThe dependencies, tools and processes used to build and deliver software. Compromising one part can affect the products or organizations that rely on it. teams vetting open-source dependencies before they enter a build, and it can scan local directories, remote archives, or packages stored in S3, with a kernel-level sandbox available to isolate code during analysis. Maintained by Datadog, it sits in the software supply-chain security space alongside other package-scanning tools, and with 64 contributors, over 240 commits in the past year, and a release 44 days ago, it is under active development.
GuardDog is a CLI tool to Identify malicious PyPI and npm packages
How GuardDog helps
Does this package I'm about to pull in hide code an attacker doesn't want me to read?
runs YARA-based static analysis across the source looking for obfuscation techniques, including code hidden behind PyArmor, and reports the technique found
Is this open-source package safe to bring into the build before it lands in my lockfile?
downloads and scans the package source from its registry (PyPI, npm, Go, crates.io, RubyGems, GitHub Actions, or the VSCode marketplace) and reports the risks found, without requiring it to already be installed
Which package in this codebase is trying to phone home or exfiltrate data?
applies exfiltration and DNS-tunneling detection rules against each file and names the package and pattern matched, correlated with the capability that would let it act on the data
Can I trust code that's already sitting in my own archive or S3 bucket rather than the public registry?
scans local directories, remote archives, or packages stored in S3 directly, so vetting isn't limited to what a registry currently serves
Is a package's link to a suspicious domain something to worry about or just noise?
flags shady-link patterns, including deceptive top-level domains, and treats them as a threat indicator that only becomes a scored risk when paired with a capability that could use it
Languages
Command line
No command matches.
| option | found in | since | description |
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Values are placeholders taken from each option’s declared default. Nothing is executed here — the output shown is a recording of a run that already happened.
Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for GuardDog, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
Score cards are part of every paid plan.
See plans → Already subscribed? Sign in →Trajectory
Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail GuardDog puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
Checking release-note history…
Commercials
pricing & packaging history · Datadog vendor page59 readings of Datadog's pricing page since Sep 2021, with 27 relaunches of its plan lineup and 21 changes to what its plans include — each one dated, compared with the reading before it, and explained for someone buying the tool.
Pricing and packaging history is included with Researcher and Business. See how every vendor we track sells, and how that has changed over time, using data we don't publish anywhere else.
See plans → Already subscribed? Sign in →Plans by offering
Each offering on the pricing page links to its own page of plans, read at its latest capture.
Plan relaunches
Plans, prices and descriptions are quoted from the vendor's own pricing page as we read it on each date. A plan missing from a later reading is shown as no longer listed on the page — a statement about the page, not the product. Readings that failed to show any plans are left out rather than read as a change.
Website history
datadoghq.com, every changeDatadog's home page and 40 more pages as they looked each month from August 2021 to October 2026: 52 renders, 7 changes of tagline or palette. Step through them, play them, or put any two months side by side.
Website history is included with Researcher and Business.
See plans → Already subscribed? Sign in →← → or h l a month · Shift a year · [ ] previous / next change · Space play · 1 2 3 page · T whole page · C compare · F full size
← → or h l the right month · Shift the left · S swap · W wipe · T whole page · Esc back
Rebranding timeline
Dates bound when a change appeared between captures. Possible rebrands are AI suggestions; a redesign alone does not establish a rebrand.
Releases
36 entries
No entries match these filters.
- August 20261
- July 20261
- June 20263
- May 20263
- February 20261
- January 20264
- October 20251
- May 20251
- March 20251
- February 20251
- January 20251
- November 20241
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- May 20241
- April 20241
- November 20231
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- August 20231
- July 20232
- March 20231
- February 20232
- December 20221
- November 20222
Project health
Issue, contributor and maintainer activity in DataDog/guarddog, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 28 +13 vs prior 12 months
- Maintainers 2 +1 joined · −3 left, last 12 months
- Bus factor 1 committers behind half the commits
- Community-filed 78% of issues opened, last 12 months
- Median time to close 197 days first maintainer reply 2.8 days
- Open backlog 14 of 202 issues ever filed
- Issues opened / month 1 · 0 communitymaintainers
- Open backlog 14
- Contributors / month 0
- Commits / month 0
- Stars 1,205
- bugs 17%
- features 12%
- docs 3%
- other 68%
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
Libraries its release ships
What its latest release locks, checked against known advisories.None of its release's images build from a lockfile we can read.
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