¿Es Tianji Seguro?
Tianji — Nerq Trust Score 47.7/100 (Grado D). Puntuación basada en 3 independent trust signals.
Tianji es un software tool con un Nerq Trust Score de 47.7/100 (D), basado en 3 dimensiones de datos independientes. Mantenimiento: 0/100. Popularidad: 1/100. Datos de múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard. Última actualización: n/a. Datos legibles por máquina (JSON).
¿Es Tianji Seguro?
Desglose de Puntuación de Confianza — Tianji has a Nerq Trust Score of 47.7/100 (D). Measured across 3 independent trust signals.
¿Cuál es la puntuación de confianza de Tianji?
Tianji tiene una Puntuación de Confianza Nerq de 47.7/100, obteniendo un grado D. Esta puntuación se basa en 3 dimensiones medidas independientemente.
¿Cuáles son los hallazgos de seguridad clave de Tianji?
La señal más fuerte de Tianji es popularidad con 1/100. No se han detectado vulnerabilidades conocidas.
¿Qué es Tianji y quién lo mantiene?
| Autor | https://github.com/msgbyte/tianji |
| Categoría | Automation |
| Estrellas | 3,009 |
| Fuente | https://github.com/msgbyte/tianji |
Alternativas Populares en automation
What Is Tianji?
Tianji is a automation platform: Bridges AI assistants with the Tianji platform for survey management.. It has 3,009 GitHub stars. Nerq Trust Score: 48/100 (D).
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 Tianji's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensiones. Here is how Tianji performs in each:
- Mantenimiento (0/100): Tianji 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 documentación, usage examples, and contribution guidelines.
- Community (1/100): Community adoption is limited. Basado en GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 47.7/100 (D) is the weighted combination of these measured signals. It is a measurement, not a pass/fail or suitability judgment — weigh the individual signals against your own requirements.
Who Typically Evaluates Tianji?
Tianji is commonly evaluated by:
- Teams automating repetitive workflows
- Organizations connecting multiple tools and services
- Developers building event-driven AI pipelines
How to read the signals: Tianji's measured signals (mantenimiento 0/100, documentación 0/100, community 1/100) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.
How to Verify Tianji's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Revisar el/la repository seguridad policy, open issues, and recent commits for signs of active mantenimiento.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Tianji's dependency tree. - Reseña permissions — Understand what access Tianji requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Tianji 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=Tianji - Revisar el/la license — Confirm that Tianji'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 seguridad concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Tianji
When evaluating whether Tianji is safe, consider these category-specific risks:
Understand how Tianji processes, stores, and transmits your data. Revisar el/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Tianji's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher seguridad risk.
Regularly check for updates to Tianji. Seguridad patches and bug fixes are only effective if you're running the latest version.
If Tianji 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 Tianji's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Tianji in violation of its license can expose your organization to legal liability.
Best Practices for Using Tianji Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Tianji while minimizing risk:
Periodically review how Tianji is used in your workflow. Check for unexpected behavior, permissions drift, and cumplimiento with your seguridad policies.
Ensure Tianji and all its dependencies are running the latest stable versions to benefit from seguridad patches.
Grant Tianji only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Tianji's seguridad advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Tianji is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Tianji
Nerq's signals are one input. In the following situations, evaluate Tianji's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Tianji's measured trust score of 47.7/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Tianji is suitable for any particular use.
How Tianji Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among automation tools, the average Trust Score is 64/100. Tianji's score of 47.7/100 is below the category average of 64/100.
This suggests that Tianji trails behind many comparable automation tools. Organizations with strict seguridad requirements should evaluate whether higher-scoring alternatives better meet their needs.
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 Tianji 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, Tianji'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 Tianji's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Tianji&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 Tianji are strengthening or weakening over time.
Tianji vs Alternativas
In the automation category, Tianji scores 47.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Tianji vs Windows Desktop Control — Trust Score: 62.0/100
- Tianji vs gemma-7b — Trust Score: 68.9/100
- Tianji vs Notte Browser — Trust Score: 50.7/100
Puntos Clave
- Tianji has a measured Nerq Trust Score of 47.7/100 (D) — a composite of independent signals, not a suitability judgment.
- Among automation tools, Tianji scores below the category average of 64/100 (a positional measurement relative to peers).
- The individual signals — seguridad, mantenimiento, documentación, cumplimiento, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Preguntas Frecuentes
¿Es Tianji Seguro?
¿Cuál es la puntuación de confianza de Tianji?
¿Cuáles son alternativas más seguras a Tianji?
¿Con qué frecuencia se actualiza la puntuación de Tianji?
¿Puedo usar Tianji en un entorno regulado?
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.