Stablebot est-il sûr ?
Stablebot — Nerq Trust Score 49.8/100 (Note D). Score basé sur 1 independent trust signals.
Stablebot est un software tool avec un Nerq Trust Score de 49.8/100 (D), basé sur 3 dimensions de données indépendantes. 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).
Stablebot est-il sûr ?
Détail du score de confiance — Stablebot has a Nerq Trust Score of 49.8/100 (D). Measured across 1 independent trust signal.
Quel est le score de confiance de Stablebot ?
Stablebot a un Score de Confiance Nerq de 49.8/100, obtenant la note D. Ce score est basé sur 1 dimensions mesurées indépendamment.
Quels sont les résultats de sécurité clés pour Stablebot ?
Le signal le plus fort de Stablebot est conformité à 100/100. Aucune vulnérabilité connue n'a été détectée.
Qu'est-ce que Stablebot et qui le maintient ?
| Auteur | RamaZyx |
| Catégorie | Uncategorized |
| Source | https://huggingface.co/RamaZyx/StableBOT |
| Protocols | huggingface_hub |
Conformité réglementaire
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
What Is Stablebot?
Stablebot is a software tool in the uncategorized category available on huggingface_full. Nerq Trust Score: 50/100 (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 Stablebot's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Stablebot performs in each:
- Compliance (100/100): Stablebot is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
The overall Trust Score of 49.8/100 (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 Stablebot?
Stablebot is commonly evaluated by:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Stablebot's measured signals (the trust signals above) 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 Stablebot's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Examiner le/la repository sécurité 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 Stablebot's dependency tree. - Avis permissions — Understand what access Stablebot requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Stablebot 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=StableBOT - Examiner le/la license — Confirm that Stablebot'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 sécurité concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Stablebot
When evaluating whether Stablebot is safe, consider these category-specific risks:
Understand how Stablebot processes, stores, and transmits your data. Examiner le/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Stablebot's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher sécurité risk.
Regularly check for updates to Stablebot. Sécurité patches and bug fixes are only effective if you're running the latest version.
If Stablebot 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 Stablebot's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Stablebot in violation of its license can expose your organization to legal liability.
Best Practices for Using Stablebot Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Stablebot while minimizing risk:
Periodically review how Stablebot is used in your workflow. Check for unexpected behavior, permissions drift, and conformité with your sécurité policies.
Ensure Stablebot and all its dependencies are running the latest stable versions to benefit from sécurité patches.
Grant Stablebot only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Stablebot's sécurité advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Stablebot is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Stablebot
Nerq's signals are one input. In the following situations, evaluate Stablebot'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 Stablebot's measured trust score of 49.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Stablebot is suitable for any particular use.
How Stablebot Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Stablebot's score of 49.8/100 is below the category average of 62/100.
This suggests that Stablebot trails behind many comparable uncategorized 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 Stablebot 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, Stablebot'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 Stablebot's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=StableBOT&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 Stablebot are strengthening or weakening over time.
Points Essentiels
- Stablebot has a measured Nerq Trust Score of 49.8/100 (D) — a composite of independent signals, not a suitability judgment.
- Among uncategorized tools, Stablebot scores below the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — sécurité, maintenance, documentation, conformité, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Questions fréquentes
Stablebot est-il sûr ?
Quel est le score de confiance de Stablebot ?
Quelles sont les alternatives plus sûres à Stablebot ?
À quelle fréquence le score de sécurité de Stablebot est-il mis à jour ?
Puis-je utiliser Stablebot dans un environnement réglementé ?
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.