Is Abstract Distances Safe?

Abstract Distances — Nerq Trust Score 46.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25

Abstract Distances is a Python package with a Nerq Trust Score of 46.2/100 (D), based on 3 independent data dimensions. Last analyzed: 2026-03-25 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).

Is Abstract Distances safe?

Trust Score Breakdown — Abstract Distances has a Nerq Trust Score of 46.2/100 (D). Measured across 2 independent trust signals (as of 2026-03-25).

Security Analysis → Abstract Distances Privacy Report →

What is Abstract Distances's trust score?

Abstract Distances has a Nerq Trust Score of 46.2/100, earning a D grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.

Security
90
Popularity
0

What are the key security findings for Abstract Distances?

Abstract Distances's strongest signal is security at 90/100. No known vulnerabilities have been detected.

Security score: 90/100 (strong)
Popularity: 0/100 — community adoption

What is Abstract Distances and who maintains it?

Authorputkoff
CategoryPython Packages
SourceN/A

Abstract Distances Across Platforms

Same developer/company in other registries:

abstract-apis
48/100 · npm
@putkoff/abstract-apis
48/100 · npm
@putkoff/abstract-utilities
48/100 · npm
@putkoff/abstract_utilities
48/100 · npm
@putkoff/abstract-files
48/100 · npm

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Safety Guide: Abstract Distances

What is Abstract Distances?

Abstract Distances is a Python package.

How to Verify Safety

Run pip audit or safety check. Review on PyPI for download stats.

You can also check the trust score via API: GET /v1/preflight?target=abstract-distances

Key Safety Concerns for Python package

When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.

Measured Signals

Abstract Distances has a Nerq Trust Score of 46/100 (D). This score is a composite of automated measurements of security, maintenance, community, and quality signals.

Key Takeaways

Frequently Asked Questions

Is Abstract Distances Safe?
abstract-distances with a Nerq Trust Score of 46.2/100 (D). Strongest signal: security (90/100). Score based on Security (90/100), Popularity (0/100).
What is Abstract Distances's trust score?
abstract-distances: 46.2/100 (D). Score based on Security (90/100), Popularity (0/100). Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=abstract-distances
What are safer alternatives to Abstract Distances?
In the Python Packages category, more Python packages are being analyzed — check back soon. abstract-distances scores 46.2/100.
Does Abstract Distances have known vulnerabilities?
Nerq checks Abstract Distances against NVD, OSV.dev, and registry-specific vulnerability databases. Current security score: 90/100. Run your package manager's audit command for the latest findings.
Is Abstract Distances actively maintained?
Abstract Distances maintenance score: N/A. Check the repository for recent commit activity and issue responsiveness.
API: /v1/preflight Trust Badge API Docs

See Also

Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.

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