Openclaw Umbrel安全吗?
Openclaw Umbrel — Nerq Trust Score 65.8/100 (C级). 基于5 independent trust signals的评分。
Openclaw Umbrel 是一个software tool Nerq 信任分数 65.8/100(C), 基于5个独立数据维度. 安全: 0/100. 维护: 1/100. 人气度: 0/100. 数据来源于多个公共来源,包括包注册表、GitHub、NVD、OSV.dev和OpenSSF Scorecard。最后更新:n/a。 机器可读数据(JSON).
Openclaw Umbrel安全吗?
信任评分详情 — Openclaw Umbrel has a Nerq Trust Score of 65.8/100 (C). Measured across 5 independent trust signals.
Openclaw Umbrel的信任评分是多少?
Openclaw Umbrel 的 Nerq 信任分数为 65.8/100,等级为 C。该分数基于 5 个独立测量的维度,包括安全性、维护和社区采用。
Openclaw Umbrel的主要安全发现是什么?
Openclaw Umbrel 最强的信号是 合规性,为 84/100。 未检测到已知漏洞。
Openclaw Umbrel是什么,谁在维护它?
| 开发者 | getumbrel |
| 类别 | Coding |
| 星标 | 5 |
| 来源 | https://github.com/getumbrel/openclaw-umbrel |
| Protocols | rest |
合规性
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 84/100 |
| 管辖权s | Assessed across 52 司法管辖区s |
coding中的热门替代品
What Is Openclaw Umbrel?
Openclaw Umbrel is a software tool in the coding category: An AI assistant Docker image for umbrelOS.. It has 5 GitHub stars. Nerq Trust Score: 66/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including 安全性 vulnerabilities, 维护 activity, license 合规性, and 社区采用.
How Nerq Assesses Openclaw Umbrel's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five 维度. Here is how Openclaw Umbrel performs in each:
- 安全性 (0/100): Openclaw Umbrel's 安全性 posture is poor. This score factors in known CVEs, dependency vulnerabilities, 安全性 policy presence, and code signing practices.
- 维护 (1/100): Openclaw Umbrel is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API 文档, usage examples, and contribution guidelines.
- Compliance (84/100): Openclaw Umbrel is broadly compliant. Assessed against regulations in 52 司法管辖区s including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. 基于 GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 65.8/100 (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 Openclaw Umbrel?
Openclaw Umbrel is commonly evaluated by:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Openclaw Umbrel's measured signals (安全性 0/100, 维护 1/100, 文档 0/100, 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 Openclaw Umbrel's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — 查看 repository's 安全性 policy, open issues, and recent commits for signs of active 维护.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Openclaw Umbrel's dependency tree. - 评论 permissions — Understand what access Openclaw Umbrel requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Openclaw Umbrel 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=openclaw-umbrel - 查看 license — Confirm that Openclaw Umbrel'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 安全性 concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Openclaw Umbrel
When evaluating whether Openclaw Umbrel is safe, consider these category-specific risks:
Understand how Openclaw Umbrel processes, stores, and transmits your data. 查看 tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Openclaw Umbrel's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher 安全性 risk.
Regularly check for updates to Openclaw Umbrel. 安全性 patches and bug fixes are only effective if you're running the latest version.
If Openclaw Umbrel 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 Openclaw Umbrel's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Openclaw Umbrel in violation of its license can expose your organization to legal liability.
Openclaw Umbrel and the EU AI Act
Openclaw Umbrel 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 合规性 assessment covers 52 司法管辖区s worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal 合规性.
Best Practices for Using Openclaw Umbrel Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Openclaw Umbrel while minimizing risk:
Periodically review how Openclaw Umbrel is used in your workflow. Check for unexpected behavior, permissions drift, and 合规性 with your 安全性 policies.
Ensure Openclaw Umbrel and all its dependencies are running the latest stable versions to benefit from 安全性 patches.
Grant Openclaw Umbrel only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Openclaw Umbrel's 安全性 advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Openclaw Umbrel is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant 独立 Review of Openclaw Umbrel
Nerq's signals are one input. In the following situations, evaluate Openclaw Umbrel'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 Openclaw Umbrel's measured trust score of 65.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Openclaw Umbrel is suitable for any particular use.
How Openclaw Umbrel 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. Openclaw Umbrel's score of 65.8/100 is above the category average of 62/100.
This positions Openclaw Umbrel favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust 维度.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks 中等 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 Openclaw Umbrel 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 维护 patterns change, Openclaw Umbrel'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 安全性 and quality. Conversely, a downward trend may signal reduced 维护, growing technical debt, or unresolved vulnerabilities. To track Openclaw Umbrel's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=openclaw-umbrel&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 — 安全性, 维护, 文档, 合规性, and community — has evolved independently, providing granular visibility into which aspects of Openclaw Umbrel are strengthening or weakening over time.
Openclaw Umbrel vs 替代品
In the coding category, Openclaw Umbrel scores 65.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Openclaw Umbrel vs AutoGPT — Trust Score: 65.3/100
- Openclaw Umbrel vs ollama — Trust Score: 64.4/100
- Openclaw Umbrel vs langchain — Trust Score: 77.0/100
主要结论
- Openclaw Umbrel has a measured Nerq Trust Score of 65.8/100 (C) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Openclaw Umbrel scores above the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — 安全性, 维护, 文档, 合规性, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
常见问题
Openclaw Umbrel安全吗?
Openclaw Umbrel的信任评分是多少?
Openclaw Umbrel有哪些更安全的替代品?
Openclaw Umbrel的安全评分多久更新一次?
我可以在受监管的环境中使用Openclaw Umbrel吗?
另请参阅
Disclaimer: Nerq 信任评分是基于公开信号的自动评估。它们不构成建议或保证。请始终进行自己的验证。