Ist Codescholar sicher?

Codescholar — Nerq Trust Score 52.2/100 (Note C-). Basierend auf der Analyse von 5 Vertrauensdimensionen wird es als bemerkenswerte Sicherheitsbedenken eingestuft. Zuletzt aktualisiert: 2026-04-24.

Verwende Codescholar mit Vorsicht. Codescholar ist ein software tool mit einem Nerq-Vertrauenswert von 52.2/100 (C-), basierend auf 5 unabhängigen Datendimensionen. Unter der Nerq-Vertrauensschwelle Sicherheit: 0/100. Wartung: 1/100. Beliebtheit: 0/100. Daten von mehreren öffentlichen Quellen einschließlich Paketregistern, GitHub, NVD, OSV.dev und OpenSSF Scorecard. Zuletzt aktualisiert: 2026-04-24. Maschinenlesbare Daten (JSON).

Ist Codescholar sicher?

CAUTION — Codescholar has a Nerq Trust Score of 52.2/100 (C-). Es hat moderat Vertrauenssignale, zeigt aber einige Problembereiche that warrant attention. Suitable for development use — review Sicherheit and Wartung signals before production deployment.

Sicherheitsanalyse → Codescholar Datenschutzbericht →

Was ist die Vertrauensbewertung von Codescholar?

Codescholar hat eine Nerq-Vertrauensbewertung von 52.2/100 und erhält die Note C-. Diese Bewertung basiert auf 5 unabhängig gemessenen Dimensionen.

Sicherheit
0
Konformität
92
Wartung
1
Dokumentation
1
Beliebtheit
0

Was sind die wichtigsten Sicherheitsergebnisse für Codescholar?

Das stärkste Signal von Codescholar ist konformität mit 92/100. Es wurden keine bekannten Schwachstellen erkannt. Hat die Nerq-Vertrauensschwelle von 70+ noch nicht erreicht.

Sicherheitsbewertung: 0/100 (schwach)
Wartung: 1/100 — geringe Wartungsaktivität
Konformität: 92/100 — covers 47 of 52 jurisdictions
Dokumentation: 1/100 — begrenzte Dokumentation
Beliebtheit: 0/100 — Community-Akzeptanz

Was ist Codescholar und wer pflegt es?

AutorBbadhub
KategorieResearch
Quellehttps://github.com/Bbadhub/CodeScholar
Frameworksopenai · anthropic
Protocolsmcp · rest

Regulatorische Konformität

EU AI Act Risk ClassMINIMAL
Compliance Score92/100
JurisdictionsAssessed across 52 jurisdictions

Beliebte Alternativen in research

binary-husky/gpt_academic
71.3/100 · B
github
hiyouga/LlamaFactory
65.5/100 · B-
github
unslothai/unsloth
66.7/100 · B-
github
stanford-oval/storm
72.3/100 · B
github
assafelovic/gpt-researcher
71.8/100 · B
github

What Is Codescholar?

Codescholar is a software tool in the research category: Context-aware academic research MCP server that analyzes codebases and links them to relevant papers.. Nerq Trust Score: 52/100 (C-).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including Sicherheit vulnerabilities, Wartung activity, license Konformität, and Community-Akzeptanz.

How Nerq Assesses Codescholar's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five Dimensionen. Here is how Codescholar performs in each:

The overall Trust Score of 52.2/100 (C-) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.

Who Should Use Codescholar?

Codescholar is designed for:

Risk guidance: Codescholar is suitable for development and testing environments. Before production deployment, conduct a thorough review of its Sicherheit posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Codescholar's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Überprüfen Sie das/die repository's Sicherheit policy, open issues, and recent commits for signs of active Wartung.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Codescholar's dependency tree.
  3. Bewertung permissions — Understand what access Codescholar requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Codescholar in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=CodeScholar
  6. Überprüfen Sie das/die license — Confirm that Codescholar's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
  7. Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses Sicherheit concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Codescholar

When evaluating whether Codescholar is safe, consider these category-specific risks:

Data handling

Understand how Codescholar processes, stores, and transmits your data. Überprüfen Sie das/die tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency Sicherheit

Check Codescholar's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher Sicherheit risk.

Update frequency

Regularly check for updates to Codescholar. Sicherheit patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Codescholar connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.

License and IP Konformität

Verify that Codescholar's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Codescholar in violation of its license can expose your organization to legal liability.

Codescholar and the EU AI Act

Codescholar is classified as Minimal Risk under the EU AI Act. This is the lowest risk category, meaning it faces minimal regulatory requirements. However, transparency obligations still apply.

Nerq's Konformität assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal Konformität.

Best Practices for Using Codescholar Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Codescholar while minimizing risk:

Conduct regular audits

Periodically review how Codescholar is used in your workflow. Check for unexpected behavior, permissions drift, and Konformität with your Sicherheit policies.

Keep dependencies updated

Ensure Codescholar and all its dependencies are running the latest stable versions to benefit from Sicherheit patches.

Follow least privilege

Grant Codescholar only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for Sicherheit advisories

Subscribe to Codescholar's Sicherheit advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Codescholar is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Codescholar?

Even promising tools aren't right for every situation. Consider avoiding Codescholar in these scenarios:

For each scenario, evaluate whether Codescholar's trust score of 52.2/100 meets your organization's risk tolerance. We recommend running a manual Sicherheit assessment alongside the automated Nerq score.

How Codescholar Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among research tools, the average Trust Score is 62/100. Codescholar's score of 52.2/100 is near the category average of 62/100.

This places Codescholar in line with the typical research tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderat in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.

Trust Score History

Nerq continuously monitors Codescholar and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or Wartung patterns change, Codescholar's score is updated within 24 hours.

Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to Sicherheit and quality. Conversely, a downward trend may signal reduced Wartung, growing technical debt, or unresolved vulnerabilities. To track Codescholar's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=CodeScholar&include=history

Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — Sicherheit, Wartung, Dokumentation, Konformität, and community — has evolved independently, providing granular visibility into which aspects of Codescholar are strengthening or weakening over time.

Codescholar vs Alternativen

In the research category, Codescholar scores 52.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Wichtigste Punkte

Detaillierte Bewertungsanalyse

DimensionBewertung
Sicherheit0/100
Wartung1/100
Beliebtheit0/100

Basierend auf 3 Dimensionen. Daten von mehreren öffentlichen Quellen einschließlich Paketregistern, GitHub, NVD, OSV.dev und OpenSSF Scorecard.

Welche Daten erhebt Codescholar?

Datenschutz assessment for Codescholar is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.

Ist Codescholar sicher?

Sicherheitsbewertung: 0/100. Review Sicherheit practices and consider alternatives with higher Sicherheit scores for sensitive use cases.

Nerq überwacht diese Entität anhand von NVD, OSV.dev und registerspezifischen Schwachstellendatenbanken für die laufende Sicherheitsbewertung.

Vollständige Analyse: Codescholar Sicherheitsbericht

Wie wir diese Bewertung berechnet haben

Codescholar's trust score of 52.2/100 (C-) wird berechnet aus mehreren öffentlichen Quellen einschließlich Paketregistern, GitHub, NVD, OSV.dev und OpenSSF Scorecard. Die Bewertung spiegelt wider 3 unabhängige Dimensionen: Sicherheit (0/100), Wartung (1/100), Beliebtheit (0/100). Jede Dimension wird gleich gewichtet, um die zusammengesetzte Vertrauensbewertung zu erstellen.

Nerq analysiert über 7,5 Millionen Entitäten in 26 Registern mit derselben Methodik, die einen direkten Vergleich zwischen Entitäten ermöglicht. Bewertungen werden kontinuierlich aktualisiert, sobald neue Daten verfügbar sind.

Diese Seite wurde zuletzt überprüft am April 24, 2026. Datenversion: 1.0.

Vollständige Methodendokumentation · Maschinenlesbare Daten (JSON-API)

Häufig gestellte Fragen

Ist Codescholar sicher?
Mit Vorsicht verwenden. CodeScholar mit einem Nerq-Vertrauenswert von 52.2/100 (C-). Stärkstes Signal: konformität (92/100). Bewertung basierend auf Sicherheit (0/100), Wartung (1/100), Beliebtheit (0/100), Dokumentation (1/100).
Was ist die Vertrauensbewertung von Codescholar?
CodeScholar: 52.2/100 (C-). Bewertung basierend auf Sicherheit (0/100), Wartung (1/100), Beliebtheit (0/100), Dokumentation (1/100). Compliance: 92/100. Bewertungen werden aktualisiert, wenn neue Daten verfügbar werden. API: GET nerq.ai/v1/preflight?target=CodeScholar
Was sind sicherere Alternativen zu Codescholar?
In der Kategorie Research, higher-rated alternatives include binary-husky/gpt_academic (71/100), hiyouga/LlamaFactory (66/100), unslothai/unsloth (67/100). CodeScholar scores 52.2/100.
Wie oft wird die Sicherheitsbewertung von Codescholar aktualisiert?
Nerq continuously monitors Codescholar and updates its trust score as new data becomes available. Current: 52.2/100 (C-), last verifiziert 2026-04-24. API: GET nerq.ai/v1/preflight?target=CodeScholar
Kann ich Codescholar in einer regulierten Umgebung verwenden?
Codescholar hat die Nerq-Verifizierungsschwelle von 70 nicht erreicht. Zusätzliche Prüfung empfohlen.
API: /v1/preflight Trust Badge API Docs

Siehe auch

Disclaimer: Nerq-Vertrauensbewertungen sind automatisierte Bewertungen basierend auf öffentlich verfügbaren Signalen. Sie sind keine Empfehlungen oder Garantien. Führen Sie immer Ihre eigene Sorgfaltsprüfung durch.

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