Gogogot est-il sûr ?

Gogogot — Nerq Trust Score 48.1/100 (Note D). Score basé sur 4 independent trust signals.

Gogogot est un software tool avec un Nerq Trust Score de 48.1/100 (D), basé sur 4 dimensions de données indépendantes. Sécurité: 0/100. Maintenance: 1/100. Popularité: 1/100. Données de plusieurs sources publiques dont les registres de paquets, GitHub, NVD, OSV.dev et OpenSSF Scorecard. Dernière mise à jour: n/a. Données lisibles par machine (JSON).

Gogogot est-il sûr ?

Détail du score de confiance — Gogogot has a Nerq Trust Score of 48.1/100 (D). Measured across 4 independent trust signals.

Analyse de Sécurité → Rapport de confidentialité de Gogogot →

Quel est le score de confiance de Gogogot ?

Gogogot a un Score de Confiance Nerq de 48.1/100, obtenant la note D. Ce score est basé sur 4 dimensions mesurées indépendamment.

Sécurité
0
Maintenance
1
Documentation
1
Popularité
1

Quels sont les résultats de sécurité clés pour Gogogot ?

Le signal le plus fort de Gogogot est maintenance à 1/100. Aucune vulnérabilité connue n'a été détectée.

⚠Score de sécurité: 0/100 (faible)
⚠Maintenance: 1/100 — faible activité de maintenance
⚠Documentation: 1/100 — documentation limitée
⚠Popularité: 1/100 — 382 étoiles sur github

Qu'est-ce que Gogogot et qui le maintient ?

Auteuraspasskiy
CatégorieAgent
Étoiles382
Sourcehttps://github.com/aspasskiy/GoGogot
Frameworksopenai · anthropic
Protocolsrest

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What Is Gogogot?

Gogogot is a software tool in the agent category: GoGogot is a lightweight self-hosted AI agent in Go.. It has 382 GitHub stars. Nerq Trust Score: 48/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including sécurité vulnerabilities, maintenance activity, license conformité, and adoption par la communauté.

How Nerq Assesses Gogogot's Safety

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

The overall Trust Score of 48.1/100 (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 Gogogot?

Gogogot is commonly evaluated by:

How to read the signals: Gogogot's measured signals (sécurité 0/100, maintenance 1/100, documentation 1/100, 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 Gogogot's Safety Yourself

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

  1. Check the source code — Examiner le/la repository's sécurité policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Gogogot's dependency tree.
  3. Avis permissions — Understand what access Gogogot requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Gogogot 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=GoGogot
  6. Examiner le/la license — Confirm that Gogogot'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 sécurité concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Gogogot

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

Data handling

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

Dependency sécurité

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

Update frequency

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

Third-party integrations

If Gogogot 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 conformité

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

Best Practices for Using Gogogot Safely

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

Conduct regular audits

Periodically review how Gogogot is used in your workflow. Check for unexpected behavior, permissions drift, and conformité with your sécurité policies.

Keep dependencies updated

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

Follow least privilege

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

Monitor for sécurité advisories

Subscribe to Gogogot's sécurité 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 Gogogot is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Gogogot

Nerq's signals are one input. In the following situations, evaluate Gogogot's measured signals against your own requirements before making a decision:

For each situation, compare Gogogot's measured trust score of 48.1/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Gogogot is suitable for any particular use.

How Gogogot Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among agent tools, the average Trust Score is 62/100. Gogogot's score of 48.1/100 is below the category average of 62/100.

This suggests that Gogogot trails behind many comparable agent tools. Organizations with strict sécurité 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 modéré 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 Gogogot 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 maintenance patterns change, Gogogot'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 sécurité and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Gogogot's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=GoGogot&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 — sécurité, maintenance, documentation, conformité, and community — has evolved independently, providing granular visibility into which aspects of Gogogot are strengthening or weakening over time.

Gogogot vs Alternatives

In the agent category, Gogogot scores 48.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Points Essentiels

Questions fréquentes

Gogogot est-il sûr ?
GoGogot avec un Nerq Trust Score de 48.1/100 (D). Signal le plus fort : maintenance (1/100). Score basé sur Sécurité (0/100), Maintenance (1/100), Popularité (1/100), Documentation (1/100).
Quel est le score de confiance de Gogogot ?
GoGogot: 48.1/100 (D). Score basé sur Sécurité (0/100), Maintenance (1/100), Popularité (1/100), Documentation (1/100). Les scores sont mis à jour lorsque de nouvelles données sont disponibles. API: GET nerq.ai/v1/preflight?target=GoGogot
Quelles sont les alternatives plus sûres à Gogogot ?
Dans la catégorie Agent, higher-rated alternatives include pocketpaw/pocketpaw (66/100), epiral/agent-clip (48/100), krillclaw/KrillClaw (55/100). GoGogot scores 48.1/100.
À quelle fréquence le score de sécurité de Gogogot est-il mis à jour ?
Nerq recomputes Gogogot's trust score as new data becomes available. Current: 48.1/100 (D). API: GET nerq.ai/v1/preflight?target=GoGogot
Puis-je utiliser Gogogot dans un environnement réglementé ?
Gogogot: 48.1/100 (D). Compliance signals are shown in the breakdown above. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Voir aussi

Disclaimer: Les scores de confiance Nerq sont des évaluations automatisées basées sur des signaux publiquement disponibles. Ce ne sont pas des recommandations ou des garanties. Effectuez toujours votre propre vérification.

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