Maxun
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Is Maxun safe? Promising trust profile, but some evidence still deserves review.
Compare Maxun
How does it stack up against its Research & Data neighbours?
Pick any agent to compare →In detail: Maxun scores 62.3/100 (Grade C), ranked #596 of 1371 tracked open-source AI agent projects, on evidence coverage A (4 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 4.7/10; 36% of recent commits are signed; no published advisory affects its latest release (maxun); last pushed 2026-10-08. Every point is earned from checkable signals — never paid placement. How scoring works →
How Maxun could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Publish build provenance for its packagesPyPI Trusted Publishing attestations +14.7 → 77.0 B · #6 of 37
- Raise the OSSF Scorecard from 4.7 to 9.0lowest checks: CI-Tests 0, CII-Best-Practices 0, Dependency-Update-Tool 0 +9.0 → 71.3 B · #6 of 37
- Sign every commit36% signed today +3.2 → 65.5 B · #9 of 37
Chain of custody
Scanners check what the code says. This traces who ships Maxun and whether that has changed: from the source repository, through how changes are reviewed and released, to the package you install. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Partly signed
github.com/getmaxun/maxun, AGPL-3.0, last pushed 2026-10-08. 36% of the last 100 commits carry a verified signature; the rest can't be tied to a verified identity.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 4.7/10 (scanned Oct 3, 2026). The checks that decide who can get a change released:
- Code Review3
- Branch Protection1
- Signed Releasesn/a
- Dangerous Workflown/a
- Token Permissionsn/a
- Pinned Dependencies0
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 1CI-Tests 0CII-Best-Practices 0Code-Review 3Contributors 10Dangerous-Workflow -1Dependency-Update-Tool 0Fuzzing 0License 10Maintained 10Packaging -1Pinned-Dependencies 0SAST 0Security-Policy 10Signed-Releases -1Token-Permissions -1Vulnerabilities 10 -
Published packages Not linked
- PyPI maxun Source link points to getmaxun/python-sdk, same owner No build attestation
Without a build attestation, nothing proves the published files were built from this repository.
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What you install today No known advisories
Latest release checked: maxun 0.0.13. No published advisory affects it (OSV, checked 2026-10-09).
Changes to this chain
- 2026-08-07 Provenance drift warning cleared (now: unknown)
Evidence behind this score
Coverage A: 4 of 5 independent evidence types found.
- GitHub repository data
- Package downloads
- Supply-chain checks
- Public actions (missing)
- Community mentions
Verify this score yourself
Every build re-issues Maxun’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How Maxun compares in Research & Data
- #10 open-science 62.5 +0.2
- #11 EvoScientist 62.3 ±0
- #12 Maxun 62.3 this agent
- #13 OpenBB 60.5 −1.8
- #14 SurfSense 58.8 −3.5
Bars show each HVTrust score; the tick marks Maxun’s 62.3.
Where the 62.3 comes from
HVTrust dimensions vs the Research & Data average
62.3 / 100 · 100.0% confidenceMaxun Research & Data average (37 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade C reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage A is separate — it grades how many independent signal types back the score (4 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
90.3 / 100Common questions about Maxun
Does Maxun publish package provenance?
Does Maxun have an OpenSSF Scorecard?
Is Maxun actively maintained?
What license does Maxun use?
Are Maxun's commits signed?
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.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- browser
- database
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to Maxun's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.
Maintain Maxun?
For maintainers
HVTrust scores Maxun 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
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/maxun)
<a href="https://hvtracker.net/agents/maxun"><img src="https://hvtracker.net/badge/maxun.svg" alt="HVTrust"></a>
Other agents in Research & Data
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON