Este Kanbun sigur?
Kanbun — Nerq Trust Score 64.5/100 (Nota C). Pe baza analizei a 5 dimensiuni de încredere, este în general sigur, dar cu unele preocupări. Ultima actualizare: 2026-04-24.
Folosiți Kanbun cu precauție. Kanbun este un software tool cu un Scor de Încredere Nerq de 64.5/100 (C), based on 5 dimensiuni independente de date. Sub pragul verificat Nerq Securitate: 0/100. Mentenanță: 1/100. Popularitate: 0/100. Date provenite din multiple surse publice inclusiv registre de pachete, GitHub, NVD, OSV.dev și OpenSSF Scorecard. Ultima actualizare: 2026-04-24. Date citibile de mașină (JSON).
Este Kanbun sigur?
CAUTION — Kanbun has a Nerq Trust Score of 64.5/100 (C). Are semnale de încredere moderat, dar prezintă unele zone de îngrijorare that warrant attention. Suitable for development use — review securitate and mentenanță signals before production deployment.
Care este scorul de încredere al Kanbun?
Kanbun are un Nerq Trust Score de 64.5/100 cu nota C. Acest scor se bazează pe 5 dimensiuni măsurate independent, inclusiv securitate, întreținere și adopție comunitară.
Care sunt principalele constatări de securitate pentru Kanbun?
Cel mai puternic semnal al Kanbun este conformitate la 100/100. Nu au fost detectate vulnerabilități cunoscute. It has not yet reached the Nerq Verified threshold of 70+.
Ce este Kanbun și cine îl întreține?
| Autor | sidmohan0 |
| Categorie | Coding |
| Sursă | https://github.com/sidmohan0/kanbun |
| Frameworks | anthropic |
| Protocols | rest |
Conformitate reglementară
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternative populare în coding
What Is Kanbun?
Kanbun is a software tool in the coding category: Kanbun is an agent orchestrator platform for managing multiple AI workstreams.. Nerq Trust Score: 64/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including securitate vulnerabilities, mentenanță activity, license conformitate, and adoptare comunitară.
How Nerq Assesses Kanbun's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensiuni. Here is how Kanbun performs in each:
- Securitate (0/100): Kanbun's securitate posture is poor. This score factors in known CVEs, dependency vulnerabilities, securitate policy presence, and code signing practices.
- Mentenanță (1/100): Kanbun 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 documentație, usage examples, and contribution guidelines.
- Compliance (100/100): Kanbun is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Bazat pe GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 64.5/100 (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 Kanbun?
Kanbun is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Kanbun is suitable for development and testing environments. Before production deployment, conduct a thorough review of its securitate posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Kanbun's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Verificați repository's securitate policy, open issues, and recent commits for signs of active mentenanță.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Kanbun's dependency tree. - Recenzie permissions — Understand what access Kanbun requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Kanbun 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=kanbun - Verificați license — Confirm that Kanbun'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 securitate concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Kanbun
When evaluating whether Kanbun is safe, consider these category-specific risks:
Understand how Kanbun processes, stores, and transmits your data. Verificați tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Kanbun's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher securitate risk.
Regularly check for updates to Kanbun. Securitate patches and bug fixes are only effective if you're running the latest version.
If Kanbun 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 Kanbun's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Kanbun in violation of its license can expose your organization to legal liability.
Kanbun and the EU AI Act
Kanbun 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 conformitate assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal conformitate.
Best Practices for Using Kanbun Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Kanbun while minimizing risk:
Periodically review how Kanbun is used in your workflow. Check for unexpected behavior, permissions drift, and conformitate with your securitate policies.
Ensure Kanbun and all its dependencies are running the latest stable versions to benefit from securitate patches.
Grant Kanbun only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Kanbun's securitate advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Kanbun is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Kanbun?
Even promising tools aren't right for every situation. Consider avoiding Kanbun in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional conformitate review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Kanbun's trust score of 64.5/100 meets your organization's risk tolerance. We recommend running a manual securitate assessment alongside the automated Nerq score.
How Kanbun Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Kanbun's score of 64.5/100 is above the category average of 62/100.
This positions Kanbun favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust dimensiuni.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderat 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 Kanbun 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 mentenanță patterns change, Kanbun'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 securitate and quality. Conversely, a downward trend may signal reduced mentenanță, growing technical debt, or unresolved vulnerabilities. To track Kanbun's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=kanbun&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 — securitate, mentenanță, documentație, conformitate, and community — has evolved independently, providing granular visibility into which aspects of Kanbun are strengthening or weakening over time.
Kanbun vs Alternative
In the coding category, Kanbun scores 64.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Kanbun vs AutoGPT — Trust Score: 74.7/100
- Kanbun vs ollama — Trust Score: 73.8/100
- Kanbun vs langchain — Trust Score: 71.3/100
Concluzii principale
- Kanbun has a Trust Score of 64.5/100 (C) and is not yet Nerq Verified.
- Kanbun shows moderat trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Kanbun 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.
Analiză detaliată a scorului
| Dimension | Score |
|---|---|
| Securitate | 0/100 |
| Mentenanță | 1/100 |
| Popularitate | 0/100 |
Bazat pe 3 dimensiuni. Data from multiple surse publice inclusiv registre de pachete, GitHub, NVD, OSV.dev și OpenSSF Scorecard.
Ce date colectează Kanbun?
Confidențialitate assessment for Kanbun is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Este Kanbun sigur?
Securitate score: 0/100. Review securitate practices and consider alternatives with higher securitate scores for sensitive use cases.
Nerq monitorizează această entitate față de NVD, OSV.dev și bazele de date de vulnerabilități specifice registrului pentru evaluarea continuă a securității.
Analiză completă: Raport de securitate Kanbun
Cum am calculat acest scor
Kanbun's trust score of 64.5/100 (C) este calculat din multiple surse publice inclusiv registre de pachete, GitHub, NVD, OSV.dev și OpenSSF Scorecard. Scorul reflectă 3 dimensiuni independente: securitate (0/100), mentenanță (1/100), popularitate (0/100). Fiecare dimensiune are pondere egală pentru a produce scorul de încredere compus.
Nerq analizează peste 7,5 milioane de entități din 26 de registre folosind aceeași metodologie, permițând compararea directă între entități. Scorurile sunt actualizate continuu pe măsură ce devin disponibile date noi.
Această pagină a fost revizuită ultima dată pe April 24, 2026. Versiunea datelor: 1.0.
Documentație completă a metodologiei · Date citibile de mașină (JSON API)
Întrebări frecvente
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Vezi și
Disclaimer: Scorurile de încredere Nerq sunt evaluări automatizate bazate pe semnale disponibile public. Nu sunt recomandări sau garanții. Efectuați întotdeauna propria verificare.