Apakah Kanbot Aman?
Kanbot — Nerq Trust Score 48.7/100 (Nilai D). Skor berdasarkan 5 independent trust signals.
Kanbot adalah software tool dengan Skor Kepercayaan Nerq sebesar 48.7/100 (D), based on 5 dimensi data independen. Keamanan: 0/100. Pemeliharaan: 1/100. Popularitas: 0/100. Data bersumber dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Terakhir diperbarui: n/a. Data yang dapat dibaca mesin (JSON).
Apakah Kanbot Aman?
Rincian Skor Kepercayaan — Kanbot has a Nerq Trust Score of 48.7/100 (D). Measured across 5 independent trust signals.
Berapa skor kepercayaan Kanbot?
Kanbot memiliki Skor Kepercayaan Nerq 48.7/100 dengan nilai D. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.
Apa temuan keamanan utama untuk Kanbot?
Sinyal terkuat Kanbot adalah kepatuhan pada 100/100. Tidak ada kerentanan yang diketahui terdeteksi.
Apa itu Kanbot dan siapa yang mengelolanya?
| Pembuat | Liparu |
| Kategori | Productivity |
| Sumber | https://github.com/Liparu/Kanbot |
| Frameworks | anthropic |
| Protocols | rest · websocket |
Kepatuhan Regulasi
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternatif Populer di productivity
What Is Kanbot?
Kanbot is a software tool in the productivity category: AI-Agent Friendly Kanban Application with Calendar Integration. Nerq Trust Score: 49/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including keamanan vulnerabilities, pemeliharaan activity, license kepatuhan, and adopsi komunitas.
How Nerq Assesses Kanbot's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensi. Here is how Kanbot performs in each:
- Keamanan (0/100): Kanbot's keamanan posture is poor. This score factors in known CVEs, dependency vulnerabilities, keamanan policy presence, and code signing practices.
- Pemeliharaan (1/100): Kanbot 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 dokumentasi, usage examples, and contribution guidelines.
- Compliance (100/100): Kanbot is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Berdasarkan GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 48.7/100 (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 Kanbot?
Kanbot is commonly evaluated by:
- Developers and teams working with productivity tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Kanbot's measured signals (keamanan 0/100, pemeliharaan 1/100, dokumentasi 1/100, community 0/100) 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 Kanbot's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Tinjau repository's keamanan policy, open issues, and recent commits for signs of active pemeliharaan.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Kanbot's dependency tree. - Ulasan permissions — Understand what access Kanbot requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Kanbot 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=Kanbot - Tinjau license — Confirm that Kanbot'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 keamanan concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Kanbot
When evaluating whether Kanbot is safe, consider these category-specific risks:
Understand how Kanbot processes, stores, and transmits your data. Tinjau tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Kanbot's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher keamanan risk.
Regularly check for updates to Kanbot. Keamanan patches and bug fixes are only effective if you're running the latest version.
If Kanbot 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 Kanbot's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Kanbot in violation of its license can expose your organization to legal liability.
Kanbot and the EU AI Act
Kanbot 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 kepatuhan assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal kepatuhan.
Best Practices for Using Kanbot Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Kanbot while minimizing risk:
Periodically review how Kanbot is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.
Ensure Kanbot and all its dependencies are running the latest stable versions to benefit from keamanan patches.
Grant Kanbot only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Kanbot's keamanan advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Kanbot is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Kanbot
Nerq's signals are one input. In the following situations, evaluate Kanbot'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 Kanbot's measured trust score of 48.7/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Kanbot is suitable for any particular use.
How Kanbot Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among productivity tools, the average Trust Score is 62/100. Kanbot's score of 48.7/100 is below the category average of 62/100.
This suggests that Kanbot trails behind many comparable productivity tools. Organizations with strict keamanan 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 sedang 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 Kanbot 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 pemeliharaan patterns change, Kanbot'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 keamanan and quality. Conversely, a downward trend may signal reduced pemeliharaan, growing technical debt, or unresolved vulnerabilities. To track Kanbot's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Kanbot&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 — keamanan, pemeliharaan, dokumentasi, kepatuhan, and community — has evolved independently, providing granular visibility into which aspects of Kanbot are strengthening or weakening over time.
Kanbot vs Alternatif
In the productivity category, Kanbot scores 48.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Kanbot vs cherry-studio — Trust Score: 73.9/100
- Kanbot vs ToolJet — Trust Score: 76.5/100
- Kanbot vs posthog — Trust Score: 60.3/100
Kesimpulan Utama
- Kanbot has a measured Nerq Trust Score of 48.7/100 (D) — a composite of independent signals, not a suitability judgment.
- Among productivity tools, Kanbot scores below the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — keamanan, pemeliharaan, dokumentasi, kepatuhan, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Pertanyaan yang Sering Diajukan
Apakah Kanbot Aman?
Berapa skor kepercayaan Kanbot?
Apa alternatif yang lebih aman dari Kanbot?
Seberapa sering skor keamanan Kanbot diperbarui?
Bisakah saya menggunakan Kanbot di lingkungan yang diatur?
Lihat juga
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