Is Moska veilig?
Moska — Nerq Trust Score 66.0/100 (C-beoordeling). Op basis van analyse van 5 vertrouwensdimensies wordt het beschouwd als over het algemeen veilig maar met enkele zorgen. Laatst bijgewerkt: 2026-04-06.
Gebruik Moska met voorzichtigheid. Moska is een software tool met een Nerq Vertrouwensscore van 66.0/100 (C), based on 5 onafhankelijke gegevensdimensies. Onder de geverifieerde drempel van Nerq Beveiliging: 0/100. Onderhoud: 0/100. Populariteit: 0/100. Gegevens afkomstig van meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard. Laatst bijgewerkt: 2026-04-06. Machineleesbare gegevens (JSON).
Is Moska veilig?
CAUTION — Moska has a Nerq Trust Score of 66.0/100 (C). Heeft matige vertrouwenssignalen maar toont enkele aandachtspunten that warrant attention. Suitable for development use — review beveiliging and onderhoud signals before production deployment.
Wat is de vertrouwensscore van Moska?
Moska heeft een Nerq Trust Score van 66.0/100 met het cijfer C. Deze score is gebaseerd op 5 onafhankelijk gemeten dimensies, waaronder beveiliging, onderhoud en community-adoptie.
Wat zijn de belangrijkste beveiligingsbevindingen voor Moska?
Het sterkste signaal van Moska is naleving met 100/100. Er zijn geen bekende kwetsbaarheden gedetecteerd. It has not yet reached the Nerq Verified threshold of 70+.
Wat is Moska en wie onderhoudt het?
| Ontwikkelaar | arnotoro |
| Categorie | Coding |
| Bron | https://github.com/arnotoro/moska |
Naleving van regelgeving
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdicties |
Populaire alternatieven in coding
What Is Moska?
Moska is a software tool in the coding category: A Python game engine and AI for the hidden-information card game Moska using MCTS.. Nerq Trust Score: 66/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including beveiliging vulnerabilities, onderhoud activity, license naleving, and gemeenschapsacceptatie.
How Nerq Assesses Moska's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensies. Here is how Moska performs in each:
- Beveiliging (0/100): Moska's beveiliging posture is poor. This score factors in known CVEs, dependency vulnerabilities, beveiliging policy presence, and code signing practices.
- Onderhoud (0/100): Moska 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 documentatie, usage examples, and contribution guidelines.
- Compliance (100/100): Moska is broadly compliant. Assessed against regulations in 52 jurisdicties including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Gebaseerd op GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 66.0/100 (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 Moska?
Moska is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Moska is suitable for development and testing environments. Before production deployment, conduct a thorough review of its beveiliging posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Moska's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Bekijk de repository's beveiliging policy, open issues, and recent commits for signs of active onderhoud.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Moska's dependency tree. - Beoordeling permissions — Understand what access Moska requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Moska 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=moska - Bekijk de license — Confirm that Moska'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 beveiliging concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Moska
When evaluating whether Moska is safe, consider these category-specific risks:
Understand how Moska processes, stores, and transmits your data. Bekijk de tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Moska's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher beveiliging risk.
Regularly check for updates to Moska. Beveiliging patches and bug fixes are only effective if you're running the latest version.
If Moska 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 Moska's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Moska in violation of its license can expose your organization to legal liability.
Moska and the EU AI Act
Moska 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 naleving assessment covers 52 jurisdicties worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal naleving.
Best Practices for Using Moska Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Moska while minimizing risk:
Periodically review how Moska is used in your workflow. Check for unexpected behavior, permissions drift, and naleving with your beveiliging policies.
Ensure Moska and all its dependencies are running the latest stable versions to benefit from beveiliging patches.
Grant Moska only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Moska's beveiliging advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Moska is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Moska?
Even promising tools aren't right for every situation. Consider avoiding Moska in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional naleving review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Moska's trust score of 66.0/100 meets your organization's risk tolerance. We recommend running a manual beveiliging assessment alongside the automated Nerq score.
How Moska Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Moska's score of 66.0/100 is above the category average of 62/100.
This positions Moska favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust dimensies.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks matig 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 Moska 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 onderhoud patterns change, Moska'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 beveiliging and quality. Conversely, a downward trend may signal reduced onderhoud, growing technical debt, or unresolved vulnerabilities. To track Moska's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=moska&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 — beveiliging, onderhoud, documentatie, naleving, and community — has evolved independently, providing granular visibility into which aspects of Moska are strengthening or weakening over time.
Moska vs Alternatieven
In the coding category, Moska scores 66.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Moska vs AutoGPT — Trust Score: 74.7/100
- Moska vs ollama — Trust Score: 73.8/100
- Moska vs langchain — Trust Score: 86.4/100
Belangrijkste conclusies
- Moska has a Trust Score of 66.0/100 (C) and is not yet Nerq Verified.
- Moska shows matig trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Moska 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.
Veelgestelde vragen
Is Moska veilig?
Wat is de vertrouwensscore van Moska?
Wat zijn veiligere alternatieven voor Moska?
Hoe vaak wordt de beveiligingsscore van Moska bijgewerkt?
Kan ik Moska gebruiken in een gereguleerde omgeving?
Zie ook
Disclaimer: Nerq-vertrouwensscores zijn geautomatiseerde beoordelingen op basis van openbaar beschikbare signalen. Ze vormen geen aanbeveling of garantie. Voer altijd uw eigen verificatie uit.