Home/automl-gs/Trust report

Trust and health report

automl-gs - trust report

Sourced, dated trust signals - maintenance label posture, repository provenance, and security scan status. Not a composite safety grade.

GraphCanon updated 2w · GitHub synced 2w

Maintenance

Recency and activity heuristics from public GitHub metadata (maintenance label, momentum); methodology: github_public_v1.

Dormant18% signal

last push 2477d ago · last release 7y

Provenance

Repository identity and fork provenance (github_public_v1).

  • GitHub repo id: 165542441
  • Not a fork
  • Personal account
  • Computed 2w

Security intelligence

Source-by-source security scan results from public intelligence providers. Missing, partial, or failed queries are shown explicitly and are not treated as clean.

OSV dependency advisories

Published findings
Last query
1mo
Scanner
osv@v1
Stored findings
14
View source evidence

deps.dev advisories

Not queried
Scanner
deps.dev@v1
View source evidence

OpenSSF Scorecard

Not queried
Scanner
openssf-scorecard@v1

Weekly public scans omit some checks at scale.

View source evidence

Dependency advisories (deduplicated)

Jinja2 sandbox escape via string formatting
jinja2@2.8 · CVE-2019-10906 · osv@v1
requirements.txt
Jinja2 sandbox escape vulnerability
jinja2@2.8 · CVE-2016-10745 · osv@v1
requirements.txt
Jinja2 vulnerable to sandbox breakout through attr filter selecting format method
jinja2@2.8 · CVE-2025-27516 · osv@v1
requirements.txt
Regular Expression Denial of Service (ReDoS) in Jinja2
jinja2@2.8 · CVE-2020-28493 · osv@v1
requirements.txt
Jinja vulnerable to HTML attribute injection when passing user input as keys to xmlattr filter
jinja2@2.8 · CVE-2024-22195 · osv@v1
requirements.txt
Jinja vulnerable to HTML attribute injection when passing user input as keys to xmlattr filter
jinja2@2.8 · CVE-2024-34064 · osv@v1
requirements.txt
Jinja has a sandbox breakout through indirect reference to format method
jinja2@2.8 · CVE-2024-56326 · osv@v1
requirements.txt

Method and caveats: these are sourced, dated heuristics from public GitHub data and external security intelligence providers. A status like "no published findings from this source" is not a guarantee of safety. Read the full trust methodology · JSON report at /api/graphcanon/tools/minimaxir-automl-gs/trust.

Common questions

Is automl-gs maintained?
GraphCanon rates automl-gs "Dormant" (18% maintenance signal from public GitHub metadata, computed 2w). Last push was 2477 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
Is automl-gs safe to use?
Last scanned 1mo (deps profile). Status: 2 high, 5 medium, 7 low - 2 high, 5 medium, 7 low finding(s) in the latest scan. GraphCanon does not claim the project is safe or vulnerability-free; review findings on the trust report. GraphCanon does not certify automl-gs as safe - review maintenance, provenance, and scan findings on this page before adopting.
Is automl-gs a fork?
No. automl-gs is not flagged as a fork in GitHub metadata at the time of the last refresh.
Does automl-gs have known security vulnerabilities?
Last scanned 1mo (deps profile). Status: 2 high, 5 medium, 7 low - 2 high, 5 medium, 7 low finding(s) in the latest scan. GraphCanon does not claim the project is safe or vulnerability-free; review findings on the trust report.
How often is the automl-gs trust report updated?
Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed 2w (methodology github_public_v1).
What does GraphCanon never claim about automl-gs?
We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for automl-gs. Signals are sourced heuristics with explicit limits - see trust methodology.
How does GraphCanon assess trust for automl-gs?
Signals are sourced from public GitHub metadata and optional dependency/MCP manifest scans, each tagged with methodology version and computed date. GraphCanon does not publish a composite safety grade. Read trust methodology for full scope and limits.

Was this helpful?

Anonymous feedback helps us improve pages and translations.