Är Codescholar säker?
Codescholar — Nerq Förtroendepoäng 67.6/100 (Betyg C). Baserat på analys av 5 tillitsdimensioner bedöms det som generellt säkert men med vissa farhågor. Senast uppdaterad: 2026-04-02.
Använd Codescholar med försiktighet. Codescholar is a software tool med ett Nerq-förtroendepoäng på 67.6/100 (C), based on 5 independent data dimensions. Ligger under den rekommenderade gränsen på 70. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-02. Maskinläsbar data (JSON).
Är Codescholar säker?
VAR FÖRSIKTIG — Codescholar har ett Nerq-förtroendepoäng på 67.6/100 (C). Har måttliga förtroendesignaler men uppvisar vissa oroande områden. Lämplig för utvecklingsanvändning — granska säkerhets- och underhållssignaler innan produktionsdriftsättning.
Vad är Codescholars förtroendepoäng?
Codescholar har ett Nerq-förtroendepoäng på 67.6/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
Vilka är de viktigaste säkerhetsresultaten för Codescholar?
Codescholar's strongest signal is regelefterlevnad at 92/100. No kända sårbarheter have been detected. It has not yet reached the Nerq Verified threshold of 70+.
Vad är Codescholar och vem underhåller det?
| Utvecklare | Bbadhub |
| Kategori | research |
| Källa | https://github.com/Bbadhub/CodeScholar |
| Frameworks | openai · anthropic |
| Protocols | mcp · rest |
Regelefterlevnad
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 92/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Populära alternativ inom research
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 Förtroendepoäng: 68/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Codescholar's Safety
Nerq's Förtroendepoäng is calculated from 13+ independent signals aggregated into five dimensions. Here is how Codescholar performs in each:
- Säkerhet (0/100): Codescholar's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Underhåll (1/100): Codescholar is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (92/100): Codescholar is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Förtroendepoäng of 67.6/100 (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:
- Developers and teams working with research tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Codescholar is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security 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:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for kända sårbarheter in Codescholar's dependency tree. - Recension permissions — Understand what access Codescholar requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Codescholar in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=CodeScholar - Granska 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.
- 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 security 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:
Understand how Codescholar processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Codescholar's dependency tree for kända sårbarheter. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Codescholar. Security patches and bug fixes are only effective if you're running the latest version.
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.
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 compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
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:
Periodically review how Codescholar is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Codescholar and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Codescholar only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Codescholar's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
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:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Codescholar är 67.6/100 meets your organization's risk tolerance. We recommend running a manual security 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 Förtroendepoäng is 62/100. Codescholar's score of 67.6/100 is above the category average of 62/100.
This positions Codescholar favorably among research tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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.
Förtroendepoäng History
Nerq continuously monitors Codescholar and recalculates its Förtroendepoäng 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 maintenance 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 security and quality. Conversely, a downward trend may signal reduced maintenance, 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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Codescholar are strengthening or weakening over time.
Codescholar vs Alternatives
In the research category, Codescholar scores 67.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Codescholar vs gpt_academic — Förtroendepoäng: 71.3/100
- Codescholar vs LlamaFactory — Förtroendepoäng: 89.1/100
- Codescholar vs unsloth — Förtroendepoäng: 86.6/100
Viktigaste slutsatser
- Codescholar has a Förtroendepoäng of 67.6/100 (C) and is not yet Nerq Verified.
- Codescholar shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among research tools, Codescholar scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Vanliga frågor
Är Codescholar säker att använda?
Vad är Codescholar's trust score?
Vilka säkrare alternativ finns till Codescholar?
How often is Codescholar's safety score updated?
Kan jag använda Codescholar i en reglerad miljö?
Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.