Je Qclaw bezpečný?
Qclaw — Nerq Trust Score 63.1/100 (Stupeň C). Skóre založeno na 5 independent trust signals.
Qclaw je software tool se skóre důvěryhodnosti Nerq 63.1/100 (C), based on 5 nezávislých datových dimenzích. Bezpečnost: 0/100. Údržba: 1/100. Popularita: 0/100. Data pocházejí z více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard. Naposledy aktualizováno: n/a. Strojově čitelná data (JSON).
Je Qclaw bezpečný?
Rozpis skóre důvěryhodnosti — Qclaw has a Nerq Trust Score of 63.1/100 (C). Measured across 5 independent trust signals.
Jaké je skóre důvěryhodnosti Qclaw?
Qclaw má Nerq skóre důvěryhodnosti 63.1/100 se stupněm C. Toto skóre je založeno na 5 nezávisle měřených dimenzích.
Jaká jsou klíčová bezpečnostní zjištění pro Qclaw?
Nejsilnější signál Qclaw je shoda na 94/100. Nebyly zjištěny žádné známé zranitelnosti.
Co je Qclaw a kdo jej spravuje?
| Autor | QuantumClaw |
| Kategorie | Ai Assistant |
| Zdroj | https://github.com/QuantumClaw/QClaw |
| Frameworks | anthropic |
| Protocols | rest |
Regulační shoda
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 94/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Populární alternativy v ai_assistant
What Is Qclaw?
Qclaw is a software tool in the ai_assistant category: Open-source AI agent runtime with a knowledge graph for understanding business.. Nerq Trust Score: 63/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpečnost vulnerabilities, údržba activity, license shoda, and přijetí komunitou.
How Nerq Assesses Qclaw's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimenzích. Here is how Qclaw performs in each:
- Bezpečnost (0/100): Qclaw's bezpečnost posture is poor. This score factors in known CVEs, dependency vulnerabilities, bezpečnost policy presence, and code signing practices.
- Údržba (1/100): Qclaw 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 dokumentace, usage examples, and contribution guidelines.
- Compliance (94/100): Qclaw is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Založeno na GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 63.1/100 (C) 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 Qclaw?
Qclaw is commonly evaluated by:
- Developers and teams working with ai_assistant tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Qclaw's measured signals (bezpečnost 0/100, údržba 1/100, dokumentace 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 Qclaw's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Zkontrolujte repository's bezpečnost policy, open issues, and recent commits for signs of active údržba.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Qclaw's dependency tree. - Recenze permissions — Understand what access Qclaw requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Qclaw 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=QClaw - Zkontrolujte license — Confirm that Qclaw'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 bezpečnost concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Qclaw
When evaluating whether Qclaw is safe, consider these category-specific risks:
Understand how Qclaw processes, stores, and transmits your data. Zkontrolujte tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Qclaw's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher bezpečnost risk.
Regularly check for updates to Qclaw. Bezpečnost patches and bug fixes are only effective if you're running the latest version.
If Qclaw 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 Qclaw's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Qclaw in violation of its license can expose your organization to legal liability.
Best Practices for Using Qclaw Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Qclaw while minimizing risk:
Periodically review how Qclaw is used in your workflow. Check for unexpected behavior, permissions drift, and shoda with your bezpečnost policies.
Ensure Qclaw and all its dependencies are running the latest stable versions to benefit from bezpečnost patches.
Grant Qclaw only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Qclaw's bezpečnost advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Qclaw is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Qclaw
Nerq's signals are one input. In the following situations, evaluate Qclaw'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 Qclaw's measured trust score of 63.1/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Qclaw is suitable for any particular use.
How Qclaw Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among ai_assistant tools, the average Trust Score is 62/100. Qclaw's score of 63.1/100 is above the category average of 62/100.
This positions Qclaw favorably among ai_assistant tools. While it outperforms the average, there is still room for improvement in certain trust dimenzích.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks střední 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 Qclaw 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 údržba patterns change, Qclaw'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 bezpečnost and quality. Conversely, a downward trend may signal reduced údržba, growing technical debt, or unresolved vulnerabilities. To track Qclaw's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=QClaw&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 — bezpečnost, údržba, dokumentace, shoda, and community — has evolved independently, providing granular visibility into which aspects of Qclaw are strengthening or weakening over time.
Qclaw vs Alternativy
In the ai_assistant category, Qclaw scores 63.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Qclaw vs Mastra Docs — Trust Score: 61.6/100
- Qclaw vs openakita — Trust Score: 60.7/100
- Qclaw vs openchamber — Trust Score: 82.5/100
Hlavní závěry
- Qclaw has a measured Nerq Trust Score of 63.1/100 (C) — a composite of independent signals, not a suitability judgment.
- Among ai_assistant tools, Qclaw scores above the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — bezpečnost, údržba, dokumentace, shoda, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Často kladené otázky
Je Qclaw bezpečný?
Jaké je skóre důvěryhodnosti Qclaw?
Jaké jsou bezpečnější alternativy k Qclaw?
Jak často se aktualizuje bezpečnostní skóre Qclaw?
Mohu používat Qclaw v regulovaném prostředí?
Viz také
Disclaimer: Skóre důvěryhodnosti Nerq jsou automatizovaná hodnocení založená na veřejně dostupných signálech. Nejsou doporučením ani zárukou. Vždy proveďte vlastní ověření.