Trust and health report
Failed-ML - trust report
Sourced, dated trust signals - maintenance label posture, repository provenance, and security scan status. Not a composite safety grade.
GraphCanon updated today · GitHub synced today
Maintenance
Recency and activity heuristics from public GitHub metadata (maintenance label, momentum); methodology: github_public_v1.
last push 757d ago
Provenance
Repository identity and fork provenance (github_public_v1).
- GitHub repo id: 525025357
- Not a fork
- Personal account
- Computed today
Security scan
Dependency advisory security scan when a lockfile is present. Not a full code audit.
- Status
- No lockfile
- Last scan
- today
- Scanner
- none
Method and caveats:these are sourced, dated heuristics from public GitHub data and optional dependency scans. A status like "no criticals found on 2026-07-11" is not a guarantee of safety. Read the full trust methodology · JSON report at /api/graphcanon/tools/kennethleungty-failed-ml/trust.
Common questions
- Is Failed-ML maintained?
- GraphCanon rates Failed-ML "Dormant" (18% maintenance signal from public GitHub metadata, computed today). Last push was 757 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
- Is Failed-ML safe to use?
- Last scanned today (none profile). Status: No lockfile. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits. GraphCanon does not certify Failed-ML as safe - review maintenance, provenance, and scan findings on this page before adopting.
- Is Failed-ML a fork?
- No. Failed-ML is not flagged as a fork in GitHub metadata at the time of the last refresh.
- Does Failed-ML have known security vulnerabilities?
- Last scanned today (none profile). Status: No lockfile. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits.
- How often is the Failed-ML trust report updated?
- Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed today (methodology github_public_v1).
- What does GraphCanon never claim about Failed-ML?
- We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for Failed-ML. Signals are sourced heuristics with explicit limits - see trust methodology.
- How does GraphCanon assess trust for Failed-ML?
- 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.