Trust and health report
Machine-Learning-Interviews - trust report
Sourced, dated trust signals - maintenance label posture, repository provenance, and security scan status. Not a composite safety grade.
GraphCanon updated 3w · GitHub synced 3w
Maintenance
Recency and activity heuristics from public GitHub metadata (maintenance label, momentum); methodology: github_public_v1.
last push 38d ago
Provenance
Repository identity and fork provenance (github_public_v1).
- GitHub repo id: 334567245
- Not a fork
- Personal account
- Computed 3w
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
No lockfile (source not queried)- Last query
- 1mo
- Scanner
- osv@v1
OpenSSF Scorecard
Not queried- Scanner
- openssf-scorecard@v1
Weekly public scans omit some checks at scale.
View source evidenceMethod 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/alirezadir-machine-learning-interviews/trust.
Common questions
- Is Machine-Learning-Interviews maintained?
- GraphCanon rates Machine-Learning-Interviews "Steady" (60% maintenance signal from public GitHub metadata, computed 3w). Last push was 38 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
- Is Machine-Learning-Interviews safe to use?
- Last scanned 1mo (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 Machine-Learning-Interviews as safe - review maintenance, provenance, and scan findings on this page before adopting.
- Is Machine-Learning-Interviews a fork?
- No. Machine-Learning-Interviews is not flagged as a fork in GitHub metadata at the time of the last refresh.
- Does Machine-Learning-Interviews have known security vulnerabilities?
- Last scanned 1mo (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 Machine-Learning-Interviews trust report updated?
- Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed 3w (methodology github_public_v1).
- What does GraphCanon never claim about Machine-Learning-Interviews?
- We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for Machine-Learning-Interviews. Signals are sourced heuristics with explicit limits - see trust methodology.
- How does GraphCanon assess trust for Machine-Learning-Interviews?
- 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.