هل Fellowship Code آمن؟

Fellowship Code — Nerq درجة الثقة 74.8/100 (الدرجة B). بناءً على تحليل 5 أبعاد للثقة، يُعتبر آمنًا بشكل عام مع بعض المخاوف. آخر تحديث: 2026-04-06.

نعم، Fellowship Code آمن للاستخدام. Fellowship Code هو software tool بدرجة ثقة Nerq 74.8/100 (B), بناءً على 5 أبعاد بيانات مستقلة. موصى به للاستخدام. الأمان: 0/100. الصيانة: 1/100. الشعبية: 0/100. البيانات مصدرها قراءة آلية.

هل Fellowship Code آمن؟

YES — Fellowship Code لديه درجة ثقة Nerq تبلغ 74.8/100 (B). يستوفي عتبة ثقة Nerq مع إشارات قوية عبر الأمان والصيانة واعتماد المجتمع. موصى به للاستخدام — review the full report below for specific considerations.

تحليل الأمان → تقرير الخصوصية →

ما هي درجة ثقة Fellowship Code؟

حصل Fellowship Code على درجة ثقة Nerq تبلغ 74.8/100 بدرجة B. يعتمد هذا التقييم على 5 أبعاد مُقاسة بشكل مستقل.

الأمان
0
الامتثال
100
الصيانة
1
التوثيق
1
الشعبية
0

ما هي النتائج الأمنية الرئيسية لـ Fellowship Code؟

أقوى إشارة لـ Fellowship Code هي الامتثال بدرجة 100/100. لم يتم اكتشاف أي ثغرات أمنية معروفة. يستوفي عتبة التحقق من Nerq البالغة 70+.

درجة الأمان: 0/100 (ضعيف)
الصيانة: 1/100 — نشاط صيانة منخفض
الامتثال: 100/100 — covers 52 of 52 ولاية قضائيةs
التوثيق: 1/100 — توثيق محدود
الشعبية: 0/100 — اعتماد المجتمع

ما هو Fellowship Code ومن يديره؟

المؤلفendaoment
الفئةCoding
المصدرhttps://github.com/endaoment/fellowship-code
Frameworksanthropic

الامتثال التنظيمي

EU AI Act Risk ClassMINIMAL
Compliance Score100/100
الاختصاص القضائيsAssessed across 52 ولاية قضائيةs

بدائل شائعة في coding

Significant-Gravitas/AutoGPT
74.7/100 · B
github
ollama/ollama
73.8/100 · B
github
langchain-ai/langchain
86.4/100 · A
github
x1xhlol/system-prompts-and-models-of-ai-tools
73.8/100 · B
github
anomalyco/opencode
87.9/100 · A
github

What Is Fellowship Code?

Fellowship Code is a software tool in the coding category: An open-source multi-agent AI engineering team for Cursor and Claude Code.. Nerq درجة الثقة: 75/100 (B).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and اعتماد المجتمع.

How Nerq Assesses Fellowship Code's Safety

Nerq's درجة الثقة is calculated from 13+ independent signals aggregated into five أبعاد. Here is how Fellowship Code performs in each:

The overall درجة الثقة of 74.8/100 (B) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.

Who Should Use Fellowship Code?

Fellowship Code is designed for:

Risk guidance: Fellowship Code meets the minimum threshold for production use, but we recommend monitoring for security advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

كيفية Verify Fellowship Code's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for ثغرات أمنية معروفة in Fellowship Code's dependency tree.
  3. مراجعة permissions — Understand what access Fellowship Code requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Fellowship Code in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=fellowship-code
  6. مراجعة the license — Confirm that Fellowship Code'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 عملاء that differ from the open-source license.
  7. 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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Fellowship Code

When evaluating whether Fellowship Code is safe, consider these category-specific risks:

Data handling

Understand how Fellowship Code processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Fellowship Code's dependency tree for ثغرات أمنية معروفة. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Fellowship Code. الأمان patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Fellowship Code 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.

الترخيص and IP compliance

Verify that Fellowship Code's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Fellowship Code in violation of its license can expose your organization to legal liability.

Fellowship Code and the EU AI Act

Fellowship Code 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 compliance assessment covers 52 ولاية قضائيةs worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.

Best Practices for Using Fellowship Code Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Fellowship Code while minimizing risk:

Conduct regular audits

Periodically review how Fellowship Code is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Fellowship Code and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

Grant Fellowship Code only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for security advisories

Subscribe to Fellowship Code's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Fellowship Code is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Fellowship Code?

Even well-trusted tools aren't right for every situation. Consider avoiding Fellowship Code in these scenarios:

For each scenario, evaluate whether Fellowship Code's trust score of 74.8/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Fellowship Code Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average درجة الثقة is 62/100. Fellowship Code's score of 74.8/100 is significantly above the category average of 62/100.

This places Fellowship Code in the top tier of coding tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature security practices, consistent release cadence, and broad اعتماد المجتمع.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks متوسط 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.

درجة الثقة History

Nerq continuously monitors Fellowship Code and recalculates its درجة الثقة 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 maintenance patterns change, Fellowship Code'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 security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Fellowship Code's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=fellowship-code&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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Fellowship Code are strengthening or weakening over time.

Fellowship Code vs البدائل

In the coding category, Fellowship Code scores 74.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:

النقاط الرئيسية

الأسئلة الشائعة

هل Fellowship Code آمن؟
نعم، هو آمن للاستخدام. fellowship-code بدرجة ثقة Nerq 74.8/100 (B). أقوى إشارة: الامتثال (100/100). التقييم مبني على الأمان (0/100), الصيانة (1/100), الشعبية (0/100), التوثيق (1/100).
ما هي درجة ثقة Fellowship Code؟
fellowship-code: 74.8/100 (B). التقييم مبني على الأمان (0/100), الصيانة (1/100), الشعبية (0/100), التوثيق (1/100). Compliance: 100/100. يتم تحديث النتائج عند توفر بيانات جديدة. API: GET nerq.ai/v1/preflight?target=fellowship-code
ما هي البدائل الأكثر أمانًا لـ Fellowship Code؟
في فئة Coding، البدائل الأعلى تقييمًا تشمل Significant-Gravitas/AutoGPT (75/100), ollama/ollama (74/100), langchain-ai/langchain (86/100). fellowship-code scores 74.8/100.
كم مرة يتم تحديث درجة أمان Fellowship Code؟
Nerq continuously monitors Fellowship Code and updates its trust score as new data becomes available. البيانات من multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 74.8/100 (B), last موثق 2026-04-06. API: GET nerq.ai/v1/preflight?target=fellowship-code
هل يمكنني استخدام Fellowship Code في بيئة منظمة؟
Yes — Fellowship Code meets the Nerq Verified threshold (70+). Combine this with your internal security review for regulated deployments.
API: /v1/preflight Trust Badge واجهة برمجة التطبيقات Docs

انظر أيضاً

إخلاء المسؤولية: درجات ثقة Nerq هي تقييمات آلية مبنية على إشارات متاحة للعموم. وهي ليست توصيات أو ضمانات. قم دائمًا بإجراء العناية الواجبة الخاصة بك.

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