MLflow

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, eva

Observability & Evaluation Python Grade A Listed Apache-2.0
Listing state
Listed
HVTrust
90.7/100 · Grade A
Last push
2026-06-04 · 0d ago
Recent change
New

Quick Trust Read

Verdict
Strong public trust posture, backed by multiple independent signals.
90.7/100 · Grade A
Strongest Signal
Identity / Provenance
18.0/18
Weakest Signal
Safety / Integrity
19.5/25
What Would Improve It
Improve safety / integrity to lift the weakest part of the trust profile.
Recent Changes
2026-06-02
Newly Listed
First tracked at rank #9
Maintainer Checklist
Raise Scorecard signals Current OSSF Scorecard is 5.6/10. Tighten the weakest checks to improve public safety evidence.
94.0
Activity Score · out of 100
90.7
HVTrust Score · out of 100
#11
Global Rank · of 206
#1

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade A reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Full methodology →

Signals refreshed 2026-06-04 18:04 UTC · Repo last pushed today

Rank Trend

2026-06-02 2026-06-04

Activity & Reach

Stars
26.3k
Forks
5.8k
Last Push
2026-06-04
today
Commits (4 wk)
640
Downloads (7d)
8,826,861
pypi
HN mentions (30d)
2
Open Issues
2076
Rank Change
▼2
was #9

Analysis

HVTrust Dimensions

90.7 / 100 · 100.0% confidence
Safety / IntegrityOSSF, provenance, signatures
19.5 / 25
Identity / ProvenanceListing and build link
18.0 / 18
TransparencyLicense and public checks
13.3 / 17
MaintenanceFreshness and commits
20.0 / 20
AdoptionStars and downloads
19.9 / 20

Activity Inputs

94.0 / 100
StarsRepository reach
26.5 / 30
FreshnessLast push recency
25.0 / 25
ActivityRecent commits
25 / 25
CommunityFork signal
17.5 / 20

Supply Chain Trust

Package Provenance
Verified
pypi attestation
OSSF Scorecard
5.6 / 10
via deps.dev · OpenSSF
Signed Commits
100%
of last 100 commits verified
Code-Review 10
Maintained 10
Security-Policy 10
CII-Best-Practices 0
Dangerous-Workflow 0
License 10
Pinned-Dependencies -1
Token-Permissions 10
Signed-Releases 0
Binary-Artifacts 10
Branch-Protection 3
Packaging 10
Fuzzing 0
SAST 0

Is MLflow safe?

Public supply-chain signals for MLflow are strong: it has multiple independent trust indicators in place. This does not replace your own security review, but MLflow carries less obvious unverified-evidence risk than projects with thin signals.
Does MLflow publish package provenance?
Yes. MLflow's package releases carry build provenance attestations, which cryptographically link the published package back to its source repository and CI workflow.
Does MLflow have an OpenSSF Scorecard?
MLflow has an OpenSSF Scorecard score of 5.6/10. The Scorecard checks for branch protection, signed releases, dependency updates, fuzzing, code review, and other supply-chain hygiene items. See the full check breakdown on this page.
Is MLflow actively maintained?
Actively maintained. The repository was pushed to within the last 1 day(s).
What license does MLflow use?
MLflow ships under Apache-2.0. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are MLflow's commits signed?
100% of the last 100 commits to MLflow are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.

Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.

Compare MLflow head-to-head

Runtime trust — coming soon

HVTrust currently scores supply-chain signals. We're adding runtime trust next: what an agent actually does when it runs — what it can reach, which tools it carries, what external services it depends on. Track progress on the roadmap →

  • MCP support
  • Tool / plugin surface
  • External service deps
  • Package provenance drift

Maintain MLflow?

HVTrust scores MLflow from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.

Reputation Timeline

Listed 1
2026-06-02
Newly Listed
First tracked at rank #9

Embed Badge Badge guide for maintainers →

HVTrust 90.7 Grade A
Markdown:
[![HVTrust](https://hvtracker.net/badge/mlflow.svg)](https://hvtracker.net/agents/mlflow)
HTML:
<a href="https://hvtracker.net/agents/mlflow"><img src="https://hvtracker.net/badge/mlflow.svg" alt="HVTrust"></a>

Other agents in Observability & Evaluation

MLflow head-to-head

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OSSF Scorecard via deps.dev · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v3.1 · Raw JSON