Bun Runtime Mcp安全吗?
Bun Runtime Mcp — Nerq Trust Score 50.9/100 (D级). 基于5 independent trust signals的评分。
Bun Runtime Mcp 是一个software tool Nerq 信任分数 50.9/100(D), 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).
Bun Runtime Mcp安全吗?
信任评分详情 — Bun Runtime Mcp has a Nerq Trust Score of 50.9/100 (D). Measured across 5 independent trust signals.
Bun Runtime Mcp的信任评分是多少?
Bun Runtime Mcp 的 Nerq 信任分数为 50.9/100,等级为 D。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。
Bun Runtime Mcp的主要安全发现是什么?
Bun Runtime Mcp 最强的信号是 合规性,为 100/100。 未检测到已知漏洞。
Bun Runtime Mcp是什么,谁在维护它?
| 开发者 | idyllic-labs |
| 类别 | Devops |
| 来源 | https://github.com/idyllic-labs/bun-runtime-mcp |
| Frameworks | anthropic |
| Protocols | mcp · rest · websocket |
合规性
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| 管辖权s | Assessed across 52 司法管辖区s |
devops中的热门替代品
What Is Bun Runtime Mcp?
Bun Runtime Mcp is a DevOps tool: Drop-in MCP server for inspecting and debugging running Bun processes.. Nerq Trust Score: 51/100 (D).
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 Bun Runtime Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five 维度. Here is how Bun Runtime Mcp performs in each:
- 安全性 (0/100): Bun Runtime Mcp'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): Bun Runtime Mcp 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 文档, usage examples, and contribution guidelines.
- Compliance (100/100): Bun Runtime Mcp 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 50.9/100 (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 Bun Runtime Mcp?
Bun Runtime Mcp is commonly evaluated by:
- Developers and teams working with devops tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Bun Runtime Mcp's measured signals (安全性 0/100, 维护 1/100, 文档 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 Bun Runtime Mcp'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 Bun Runtime Mcp's dependency tree. - 评论 permissions — Understand what access Bun Runtime Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Bun Runtime Mcp 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=bun-runtime-mcp - 查看 license — Confirm that Bun Runtime Mcp'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 Bun Runtime Mcp
When evaluating whether Bun Runtime Mcp is safe, consider these category-specific risks:
Understand how Bun Runtime Mcp processes, stores, and transmits your data. 查看 tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Bun Runtime Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher 安全性 risk.
Regularly check for updates to Bun Runtime Mcp. 安全性 patches and bug fixes are only effective if you're running the latest version.
If Bun Runtime Mcp 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 Bun Runtime Mcp's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Bun Runtime Mcp in violation of its license can expose your organization to legal liability.
Bun Runtime Mcp and the EU AI Act
Bun Runtime Mcp 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 Bun Runtime Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Bun Runtime Mcp while minimizing risk:
Periodically review how Bun Runtime Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and 合规性 with your 安全性 policies.
Ensure Bun Runtime Mcp and all its dependencies are running the latest stable versions to benefit from 安全性 patches.
Grant Bun Runtime Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Bun Runtime Mcp'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 Bun Runtime Mcp is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant 独立 Review of Bun Runtime Mcp
Nerq's signals are one input. In the following situations, evaluate Bun Runtime Mcp'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 Bun Runtime Mcp's measured trust score of 50.9/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Bun Runtime Mcp is suitable for any particular use.
How Bun Runtime Mcp Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among DevOps tools, the average Trust Score is 63/100. Bun Runtime Mcp's score of 50.9/100 is below the category average of 63/100.
This suggests that Bun Runtime Mcp trails behind many comparable DevOps tools. Organizations with strict 安全性 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 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 Bun Runtime Mcp 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, Bun Runtime Mcp'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 Bun Runtime Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=bun-runtime-mcp&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 Bun Runtime Mcp are strengthening or weakening over time.
Bun Runtime Mcp vs 替代品
In the devops category, Bun Runtime Mcp scores 50.9/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Bun Runtime Mcp vs ansible — Trust Score: 74.9/100
- Bun Runtime Mcp vs Flowise — Trust Score: 67.5/100
- Bun Runtime Mcp vs learn-claude-code — Trust Score: 72.1/100
主要结论
- Bun Runtime Mcp has a measured Nerq Trust Score of 50.9/100 (D) — a composite of independent signals, not a suitability judgment.
- Among DevOps tools, Bun Runtime Mcp scores below the category average of 63/100 (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
Bun Runtime Mcp安全吗?
Bun Runtime Mcp的信任评分是多少?
Bun Runtime Mcp有哪些更安全的替代品?
Bun Runtime Mcp的安全评分多久更新一次?
我可以在受监管的环境中使用Bun Runtime Mcp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。