¿Es Sciagentsdiscovery Seguro?

Sciagentsdiscovery — Nerq Trust Score 69.0/100 (Grado C). Basado en el análisis de 5 dimensiones de confianza, se considera generalmente seguro pero con algunas preocupaciones. Última actualización: 2026-04-24.

Usa Sciagentsdiscovery con precaución. Sciagentsdiscovery es un software tool con un Nerq Trust Score de 69.0/100 (C), basado en 5 dimensiones de datos independientes. Por debajo del umbral verificado de Nerq Seguridad: 0/100. Mantenimiento: 1/100. Popularidad: 1/100. Datos de múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard. Última actualización: 2026-04-24. Datos legibles por máquina (JSON).

¿Es Sciagentsdiscovery Seguro?

CAUTION — Sciagentsdiscovery has a Nerq Trust Score of 69.0/100 (C). Tiene señales de confianza moderadas pero muestra algunas áreas de preocupación that warrant attention. Suitable for development use — review seguridad and mantenimiento signals before production deployment.

Análisis de Seguridad → Informe de Privacidad de Sciagentsdiscovery →

¿Cuál es la puntuación de confianza de Sciagentsdiscovery?

Sciagentsdiscovery tiene una Puntuación de Confianza Nerq de 69.0/100, obteniendo un grado C. Esta puntuación se basa en 5 dimensiones medidas independientemente.

Seguridad
0
Cumplimiento
100
Mantenimiento
1
Documentación
0
Popularidad
1

¿Cuáles son los hallazgos de seguridad clave de Sciagentsdiscovery?

La señal más fuerte de Sciagentsdiscovery es cumplimiento con 100/100. No se han detectado vulnerabilidades conocidas. Aún no ha alcanzado el umbral verificado de Nerq de 70+.

Puntuación de seguridad: 0/100 (débil)
Mantenimiento: 1/100 — baja actividad de mantenimiento
Cumplimiento: 100/100 — covers 52 of 52 jurisdictions
Documentación: 0/100 — documentación limitada
Popularidad: 1/100 — 587 estrellas en github

¿Qué es Sciagentsdiscovery y quién lo mantiene?

AutorUnknown
CategoríaResearch
Estrellas587
Fuentehttps://github.com/lamm-mit/SciAgentsDiscovery

Cumplimiento Regulatorio

EU AI Act Risk ClassMINIMAL
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdictions

Alternativas Populares en research

binary-husky/gpt_academic
71.3/100 · B
github
hiyouga/LlamaFactory
65.5/100 · B-
github
unslothai/unsloth
66.7/100 · B-
github
stanford-oval/storm
72.3/100 · B
github
assafelovic/gpt-researcher
71.8/100 · B
github

What Is Sciagentsdiscovery?

Sciagentsdiscovery is a software tool in the research category: A research-oriented AI agent for scientific discovery.. It has 587 GitHub stars. Nerq Trust Score: 69/100 (C).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including seguridad vulnerabilities, mantenimiento activity, license cumplimiento, and adopción por la comunidad.

How Nerq Assesses Sciagentsdiscovery's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensiones. Here is how Sciagentsdiscovery performs in each:

The overall Trust Score of 69.0/100 (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 Sciagentsdiscovery?

Sciagentsdiscovery is designed for:

Risk guidance: Sciagentsdiscovery is suitable for development and testing environments. Before production deployment, conduct a thorough review of its seguridad posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Sciagentsdiscovery's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Revisar el/la repository's seguridad policy, open issues, and recent commits for signs of active mantenimiento.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Sciagentsdiscovery's dependency tree.
  3. Reseña permissions — Understand what access Sciagentsdiscovery requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Sciagentsdiscovery in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=lamm-mit/SciAgentsDiscovery
  6. Revisar el/la license — Confirm that Sciagentsdiscovery'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.
  7. 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 seguridad concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Sciagentsdiscovery

When evaluating whether Sciagentsdiscovery is safe, consider these category-specific risks:

Data handling

Understand how Sciagentsdiscovery processes, stores, and transmits your data. Revisar el/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency seguridad

Check Sciagentsdiscovery's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher seguridad risk.

Update frequency

Regularly check for updates to Sciagentsdiscovery. Seguridad patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Sciagentsdiscovery 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.

License and IP cumplimiento

Verify that Sciagentsdiscovery's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Sciagentsdiscovery in violation of its license can expose your organization to legal liability.

Sciagentsdiscovery and the EU AI Act

Sciagentsdiscovery 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 cumplimiento assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal cumplimiento.

Best Practices for Using Sciagentsdiscovery Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Sciagentsdiscovery while minimizing risk:

Conduct regular audits

Periodically review how Sciagentsdiscovery is used in your workflow. Check for unexpected behavior, permissions drift, and cumplimiento with your seguridad policies.

Keep dependencies updated

Ensure Sciagentsdiscovery and all its dependencies are running the latest stable versions to benefit from seguridad patches.

Follow least privilege

Grant Sciagentsdiscovery only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for seguridad advisories

Subscribe to Sciagentsdiscovery's seguridad advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Sciagentsdiscovery is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Sciagentsdiscovery?

Even promising tools aren't right for every situation. Consider avoiding Sciagentsdiscovery in these scenarios:

For each scenario, evaluate whether Sciagentsdiscovery's trust score of 69.0/100 meets your organization's risk tolerance. We recommend running a manual seguridad assessment alongside the automated Nerq score.

How Sciagentsdiscovery Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among research tools, the average Trust Score is 62/100. Sciagentsdiscovery's score of 69.0/100 is above the category average of 62/100.

This positions Sciagentsdiscovery favorably among research tools. While it outperforms the average, there is still room for improvement in certain trust dimensiones.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderado 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 Sciagentsdiscovery 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 mantenimiento patterns change, Sciagentsdiscovery'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 seguridad and quality. Conversely, a downward trend may signal reduced mantenimiento, growing technical debt, or unresolved vulnerabilities. To track Sciagentsdiscovery's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=lamm-mit/SciAgentsDiscovery&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 — seguridad, mantenimiento, documentación, cumplimiento, and community — has evolved independently, providing granular visibility into which aspects of Sciagentsdiscovery are strengthening or weakening over time.

Sciagentsdiscovery vs Alternativas

In the research category, Sciagentsdiscovery scores 69.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Puntos Clave

Análisis Detallado de Puntuación

DimensionScore
Seguridad0/100
Mantenimiento1/100
Popularidad1/100

Basado en 3 dimensiones. Data from múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard.

¿Qué datos recopila Sciagentsdiscovery?

Privacidad assessment for Sciagentsdiscovery is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.

¿Es Sciagentsdiscovery seguro?

Seguridad score: 0/100. Review seguridad practices and consider alternatives with higher seguridad scores for sensitive use cases.

Nerq monitorea esta entidad contra NVD, OSV.dev y bases de datos de vulnerabilidades específicas del registro para evaluación de seguridad continua.

Análisis completo: Informe de Seguridad de Sciagentsdiscovery

Cómo calculamos esta puntuación

Sciagentsdiscovery's trust score of 69.0/100 (C) se calcula a partir de múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard. La puntuación refleja 3 dimensiones independientes: seguridad (0/100), mantenimiento (1/100), popularidad (1/100). Cada dimensión se pondera equitativamente para producir la puntuación de confianza compuesta.

Nerq analiza más de 7,5 millones de entidades en 26 registros usando la misma metodología, permitiendo comparación directa entre entidades. Las puntuaciones se actualizan continuamente a medida que hay nuevos datos.

Esta página fue revisada por última vez el April 24, 2026. Versión de datos: 1.0.

Documentación completa de metodología · Datos legibles por máquinas (API JSON)

Preguntas Frecuentes

¿Es Sciagentsdiscovery Seguro?
Usar con precaución. lamm-mit/SciAgentsDiscovery con un Nerq Trust Score de 69.0/100 (C). Señal más fuerte: cumplimiento (100/100). Puntuación basada en Seguridad (0/100), Mantenimiento (1/100), Popularidad (1/100), Documentación (0/100).
¿Cuál es la puntuación de confianza de Sciagentsdiscovery?
lamm-mit/SciAgentsDiscovery: 69.0/100 (C). Puntuación basada en Seguridad (0/100), Mantenimiento (1/100), Popularidad (1/100), Documentación (0/100). Compliance: 100/100. Las puntuaciones se actualizan cuando hay nuevos datos. API: GET nerq.ai/v1/preflight?target=lamm-mit/SciAgentsDiscovery
¿Cuáles son alternativas más seguras a Sciagentsdiscovery?
En la categoría Research, higher-rated alternatives include binary-husky/gpt_academic (71/100), hiyouga/LlamaFactory (66/100), unslothai/unsloth (67/100). lamm-mit/SciAgentsDiscovery scores 69.0/100.
¿Con qué frecuencia se actualiza la puntuación de Sciagentsdiscovery?
Nerq continuously monitors Sciagentsdiscovery and updates its trust score as new data becomes available. Current: 69.0/100 (C), last verificado 2026-04-24. API: GET nerq.ai/v1/preflight?target=lamm-mit/SciAgentsDiscovery
¿Puedo usar Sciagentsdiscovery en un entorno regulado?
Sciagentsdiscovery no ha alcanzado el umbral de verificación Nerq de 70. Se recomienda diligencia adicional.
API: /v1/preflight Trust Badge API Docs

Ver también

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.

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