Je Modelence bezpečný?
Modelence — Nerq Trust Score 67.1/100 (Stupeň C). Na základě analýzy 5 dimenzí důvěryhodnosti je obecně bezpečný, ale s některými obavami. Naposledy aktualizováno: 2026-04-06.
Používejte Modelence s opatrností. Modelence je software tool se skóre důvěryhodnosti Nerq 67.1/100 (C), based on 5 nezávislých datových dimenzích. Pod ověřeným prahem Nerq Bezpečnost: 0/100. Údržba: 0/100. Popularita: 0/100. Data pocházejí z více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard. Naposledy aktualizováno: 2026-04-06. Strojově čitelná data (JSON).
Je Modelence bezpečný?
CAUTION — Modelence has a Nerq Trust Score of 67.1/100 (C). Má střední signály důvěryhodnosti, ale vykazuje některé oblasti k pozornosti that warrant attention. Suitable for development use — review bezpečnost and údržba signals before production deployment.
Jaké je skóre důvěryhodnosti Modelence?
Modelence má Nerq skóre důvěryhodnosti 67.1/100 se stupněm C. Toto skóre je založeno na 5 nezávisle měřených dimenzích.
Jaká jsou klíčová bezpečnostní zjištění pro Modelence?
Nejsilnější signál Modelence je shoda na 100/100. Nebyly zjištěny žádné známé zranitelnosti. Dosud nedosáhl ověřeného prahu Nerq 70+.
Co je Modelence a kdo jej spravuje?
| Autor | Unknown |
| Kategorie | Uncategorized |
| Hvězdičky | 347 |
| Zdroj | https://github.com/modelence/modelence |
Regulační shoda
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
What Is Modelence?
Modelence is a software tool in the uncategorized category: Modelence is an all-in-one TypeScript platform. We're building a Supabase alternative for MongoDB developers shipping production apps, with built-in database, auth, vector search and monitoring.. It has 347 GitHub stars. Nerq Trust Score: 67/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpečnost vulnerabilities, údržba activity, license shoda, and přijetí komunitou.
How Nerq Assesses Modelence's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimenzích. Here is how Modelence performs in each:
- Bezpečnost (0/100): Modelence's bezpečnost posture is poor. This score factors in known CVEs, dependency vulnerabilities, bezpečnost policy presence, and code signing practices.
- Údržba (0/100): Modelence is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API dokumentace, usage examples, and contribution guidelines.
- Compliance (100/100): Modelence is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Založeno na GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 67.1/100 (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 Modelence?
Modelence is designed for:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Modelence is suitable for development and testing environments. Before production deployment, conduct a thorough review of its bezpečnost posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Modelence's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Zkontrolujte repository's bezpečnost policy, open issues, and recent commits for signs of active údržba.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Modelence's dependency tree. - Recenze permissions — Understand what access Modelence requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Modelence 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=modelence/modelence - Zkontrolujte license — Confirm that Modelence'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 bezpečnost concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Modelence
When evaluating whether Modelence is safe, consider these category-specific risks:
Understand how Modelence processes, stores, and transmits your data. Zkontrolujte tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Modelence's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher bezpečnost risk.
Regularly check for updates to Modelence. Bezpečnost patches and bug fixes are only effective if you're running the latest version.
If Modelence 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 Modelence's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Modelence in violation of its license can expose your organization to legal liability.
Best Practices for Using Modelence Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Modelence while minimizing risk:
Periodically review how Modelence is used in your workflow. Check for unexpected behavior, permissions drift, and shoda with your bezpečnost policies.
Ensure Modelence and all its dependencies are running the latest stable versions to benefit from bezpečnost patches.
Grant Modelence only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Modelence's bezpečnost advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Modelence is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Modelence?
Even promising tools aren't right for every situation. Consider avoiding Modelence in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional shoda review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Modelence's trust score of 67.1/100 meets your organization's risk tolerance. We recommend running a manual bezpečnost assessment alongside the automated Nerq score.
How Modelence Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Modelence's score of 67.1/100 is above the category average of 62/100.
This positions Modelence favorably among uncategorized tools. While it outperforms the average, there is still room for improvement in certain trust dimenzích.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks střední 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 Modelence 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 údržba patterns change, Modelence'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 bezpečnost and quality. Conversely, a downward trend may signal reduced údržba, growing technical debt, or unresolved vulnerabilities. To track Modelence's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=modelence/modelence&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 — bezpečnost, údržba, dokumentace, shoda, and community — has evolved independently, providing granular visibility into which aspects of Modelence are strengthening or weakening over time.
Hlavní závěry
- Modelence has a Trust Score of 67.1/100 (C) and is not yet Nerq Verified.
- Modelence shows střední trust signals. Conduct thorough due diligence before deploying to production environments.
- Among uncategorized tools, Modelence 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.
Často kladené otázky
Je Modelence bezpečný?
Jaké je skóre důvěryhodnosti Modelence?
What are safer alternatives to Modelence?
How often is Modelence's safety score updated?
Can I use Modelence in a regulated environment?
Viz také
Disclaimer: Skóre důvěryhodnosti Nerq jsou automatizovaná hodnocení založená na veřejně dostupných signálech. Nejsou doporučením ani zárukou. Vždy proveďte vlastní ověření.