Is Learn2Slither veilig?
Learn2Slither — Nerq Trust Score 65.4/100 (C-beoordeling). Op basis van analyse van 5 vertrouwensdimensies wordt het beschouwd als over het algemeen veilig maar met enkele zorgen. Laatst bijgewerkt: 2026-04-26.
Gebruik Learn2Slither met voorzichtigheid. Learn2Slither is een software tool met een Nerq Vertrouwensscore van 65.4/100 (C), based on 5 onafhankelijke gegevensdimensies. Onder de geverifieerde drempel van Nerq Beveiliging: 0/100. Onderhoud: 1/100. Populariteit: 0/100. Gegevens afkomstig van meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard. Laatst bijgewerkt: 2026-04-26. Machineleesbare gegevens (JSON).
Is Learn2Slither veilig?
CAUTION — Learn2Slither has a Nerq Trust Score of 65.4/100 (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 Learn2Slither?
Learn2Slither heeft een Nerq Trust Score van 65.4/100 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 Learn2Slither?
Het sterkste signaal van Learn2Slither is naleving met 92/100. Er zijn geen bekende kwetsbaarheden gedetecteerd. It has not yet reached the Nerq Verified threshold of 70+.
Wat is Learn2Slither en wie onderhoudt het?
| Ontwikkelaar | alfux |
| Categorie | Coding |
| Bron | https://github.com/alfux/Learn2Slither |
Naleving van regelgeving
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 92/100 |
| Jurisdictions | Assessed across 52 jurisdicties |
Populaire alternatieven in coding
What Is Learn2Slither?
Learn2Slither is a software tool in the coding category: AI agent trained to play and win at Snake game.. Nerq Trust Score: 65/100 (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 Learn2Slither's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensies. Here is how Learn2Slither performs in each:
- Beveiliging (0/100): Learn2Slither's beveiliging posture is poor. This score factors in known CVEs, dependency vulnerabilities, beveiliging policy presence, and code signing practices.
- Onderhoud (1/100): Learn2Slither 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 documentatie, usage examples, and contribution guidelines.
- Compliance (92/100): Learn2Slither 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 65.4/100 (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 Learn2Slither?
Learn2Slither 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: Learn2Slither 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 Learn2Slither'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 Learn2Slither's dependency tree. - Beoordeling permissions — Understand what access Learn2Slither requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Learn2Slither 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=Learn2Slither - Bekijk de license — Confirm that Learn2Slither'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 Learn2Slither
When evaluating whether Learn2Slither is safe, consider these category-specific risks:
Understand how Learn2Slither processes, stores, and transmits your data. Bekijk de tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Learn2Slither's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher beveiliging risk.
Regularly check for updates to Learn2Slither. Beveiliging patches and bug fixes are only effective if you're running the latest version.
If Learn2Slither 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 Learn2Slither's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Learn2Slither in violation of its license can expose your organization to legal liability.
Learn2Slither and the EU AI Act
Learn2Slither 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 Learn2Slither Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Learn2Slither while minimizing risk:
Periodically review how Learn2Slither is used in your workflow. Check for unexpected behavior, permissions drift, and naleving with your beveiliging policies.
Ensure Learn2Slither and all its dependencies are running the latest stable versions to benefit from beveiliging patches.
Grant Learn2Slither only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Learn2Slither's beveiliging advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Learn2Slither is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Learn2Slither?
Even promising tools aren't right for every situation. Consider avoiding Learn2Slither 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 Learn2Slither's trust score of 65.4/100 meets your organization's risk tolerance. We recommend running a manual beveiliging assessment alongside the automated Nerq score.
How Learn2Slither 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. Learn2Slither's score of 65.4/100 is above the category average of 62/100.
This positions Learn2Slither 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 Learn2Slither 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, Learn2Slither'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 Learn2Slither's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Learn2Slither&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 Learn2Slither are strengthening or weakening over time.
Learn2Slither vs Alternatieven
In the coding category, Learn2Slither scores 65.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Learn2Slither vs AutoGPT — Trust Score: 74.7/100
- Learn2Slither vs ollama — Trust Score: 73.8/100
- Learn2Slither vs langchain — Trust Score: 71.3/100
Belangrijkste conclusies
- Learn2Slither has a Trust Score of 65.4/100 (C) and is not yet Nerq Verified.
- Learn2Slither shows matig trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Learn2Slither 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.
Gedetailleerde score-analyse
| Dimension | Score |
|---|---|
| Beveiliging | 0/100 |
| Onderhoud | 1/100 |
| Populariteit | 0/100 |
Gebaseerd op 3 dimensies. Data from meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard.
Welke gegevens verzamelt Learn2Slither?
Privacy assessment for Learn2Slither is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Learn2Slither veilig?
Beveiliging score: 0/100. Review beveiliging practices and consider alternatives with higher beveiliging scores for sensitive use cases.
Nerq bewaakt deze entiteit op NVD, OSV.dev en registerspecifieke kwetsbaarheidsdatabases voor voortdurende beveiligingsbeoordeling.
Volledige analyse: Learn2Slither Beveiligingsrapport
Hoe we deze score hebben berekend
Learn2Slither's trust score of 65.4/100 (C) wordt berekend uit meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard. De score weerspiegelt 3 onafhankelijke dimensies: beveiliging (0/100), onderhoud (1/100), populariteit (0/100). Elke dimensie heeft een gelijk gewicht om de samengestelde vertrouwensscore te produceren.
Nerq analyseert meer dan 7,5 miljoen entiteiten in 26 registers met dezelfde methodologie, waardoor directe vergelijking tussen entiteiten mogelijk is. Scores worden continu bijgewerkt naarmate er nieuwe gegevens beschikbaar komen.
Deze pagina is voor het laatst beoordeeld op April 26, 2026. Gegevensversie: 1.0.
Volledige methodologiedocumentatie · Machineleesbare gegevens (JSON API)
Veelgestelde vragen
Is Learn2Slither veilig?
Wat is de vertrouwensscore van Learn2Slither?
Wat zijn veiligere alternatieven voor Learn2Slither?
Hoe vaak wordt de beveiligingsscore van Learn2Slither bijgewerkt?
Kan ik Learn2Slither 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.