¿Es Shared Knowledge Seguro?
Shared Knowledge — Nerq Puntuación de Confianza 67.5/100 (Grado C). Basado en el análisis de 5 dimensiones de confianza, se considera generalmente seguro pero con algunas preocupaciones. Última actualización: 2026-04-01.
Usa Shared Knowledge con precaución. Shared Knowledge is a software tool with a Nerq Puntuación de Confianza de 67.5/100 (C), based on 5 independent data dimensions. It is below the recommended threshold of 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. Última actualización: 2026-04-01. Datos legibles por máquina (JSON).
¿Es Shared Knowledge Seguro?
CAUTION — Shared Knowledge tiene una Puntuación de Confianza Nerq de 67.5/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
¿Cuál es la puntuación de confianza de Shared Knowledge?
Shared Knowledge tiene una Puntuación de Confianza Nerq de 67.5/100, obteniendo un grado C. Esta puntuación se basa en 5 dimensiones medidas independientemente.
¿Cuáles son los hallazgos de seguridad clave de Shared Knowledge?
La señal más fuerte de Shared Knowledge es cumplimiento con 100/100. No se han detectado vulnerabilidades conocidas. Aún no ha alcanzado el umbral verificado de Nerq de 70+.
¿Qué es Shared Knowledge y quién lo mantiene?
| Autor | leetcrypt |
| Categoría | infrastructure |
| Estrellas | 1 |
| Fuente | https://github.com/leetcrypt/shared-knowledge |
| Protocols | rest |
Cumplimiento Regulatorio
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternativas Populares en infrastructure
What Is Shared Knowledge?
Shared Knowledge is a software tool in the infrastructure category: A central nervous system for coordinating tasks among multiple agents.. It has 1 GitHub stars. Nerq Trust Puntuación: 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 Shared Knowledge's Safety
Nerq's Puntuación de Confianza is calculated from 13+ independent signals aggregated into five dimensions. Here is how Shared Knowledge performs in each:
- Seguridad (0/100): Shared Knowledge's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Mantenimiento (1/100): Shared Knowledge 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 (100/100): Shared Knowledge 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 Puntuación de Confianza de 67.5/100 (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 Shared Knowledge?
Shared Knowledge is designed for:
- Developers and teams working with infrastructure tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Shared Knowledge 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 Shared Knowledge's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Revisar 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 known vulnerabilities in Shared Knowledge's dependency tree. - Revisar permissions — Understand what access Shared Knowledge requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Shared Knowledge 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=shared-knowledge - Revisar the license — Confirm that Shared Knowledge'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 Shared Knowledge
When evaluating whether Shared Knowledge is safe, consider these category-specific risks:
Understand how Shared Knowledge processes, stores, and transmits your data. Revisar the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Shared Knowledge's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Shared Knowledge. Security patches and bug fixes are only effective if you're running the latest version.
If Shared Knowledge 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 Shared Knowledge's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Shared Knowledge in violation of its license can expose your organization to legal liability.
Shared Knowledge and the EU AI Act
Shared Knowledge 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 Shared Knowledge Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Shared Knowledge while minimizing risk:
Periodically review how Shared Knowledge is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Shared Knowledge and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Shared Knowledge only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Shared Knowledge's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Shared Knowledge is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Shared Knowledge?
Even promising tools aren't right for every situation. Consider avoiding Shared Knowledge 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 Shared Knowledge de 67.5/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Shared Knowledge Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among infrastructure tools, the average Puntuación de Confianza is 62/100. Shared Knowledge's score of 67.5/100 is above the category average of 62/100.
This positions Shared Knowledge favorably among infrastructure 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.
Puntuación de Confianza History
Nerq continuously monitors Shared Knowledge and recalculates its Puntuación de Confianza 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, Shared Knowledge'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 Shared Knowledge's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=shared-knowledge&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 Shared Knowledge are strengthening or weakening over time.
Shared Knowledge vs Alternatives
In the infrastructure category, Shared Knowledge tiene una puntuación de 67.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Shared Knowledge vs n8n — Trust Puntuación: 78.5/100
- Shared Knowledge vs langflow — Trust Puntuación: 87.6/100
- Shared Knowledge vs dify — Trust Puntuación: 79.1/100
Puntos Clave
- Shared Knowledge tiene una Puntuación de Confianza de 67.5/100 (C) and is not yet Nerq Verified.
- Shared Knowledge shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among infrastructure tools, Shared Knowledge 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.
Preguntas Frecuentes
¿Es Shared Knowledge safe to use?
¿Cuál es la puntuación de confianza de Shared Knowledge?
¿Cuáles son alternativas más seguras a Shared Knowledge?
How often is Shared Knowledge's safety score updated?
Can I use Shared Knowledge in a regulated environment?
Disclaimer: Las puntuaciones de confianza de Nerq son evaluaciones automatizadas basadas en señales disponibles públicamente. No son respaldos ni garantías. Siempre realice su propia diligencia debida.