هل Simplellmfunc آمن؟
Simplellmfunc — Nerq درجة الثقة 53.7/100 (الدرجة D). بناءً على تحليل 1 أبعاد للثقة، يُعتبر لديه مخاوف أمنية ملحوظة. آخر تحديث: 2026-04-26.
استخدم Simplellmfunc بحذر. Simplellmfunc هو software tool بدرجة ثقة Nerq 53.7/100 (D), بناءً على 3 أبعاد بيانات مستقلة. أقل من العتبة الموصى بها 70. البيانات مصدرها قراءة آلية.
هل Simplellmfunc آمن؟
CAUTION — Simplellmfunc لديه درجة ثقة Nerq تبلغ 53.7/100 (D). لديه إشارات ثقة متوسطة لكنه يظهر بعض المجالات المثيرة للقلق التي تستحق الاهتمام. Suitable for development use — review security and maintenance signals before production deployment.
ما هي درجة ثقة Simplellmfunc؟
حصل Simplellmfunc على درجة ثقة Nerq تبلغ 53.7/100 بدرجة D. يعتمد هذا التقييم على 1 أبعاد مُقاسة بشكل مستقل.
ما هي النتائج الأمنية الرئيسية لـ Simplellmfunc؟
أقوى إشارة لـ Simplellmfunc هي الامتثال بدرجة 100/100. لم يتم اكتشاف أي ثغرات أمنية معروفة. لم يصل بعد إلى عتبة التحقق من Nerq البالغة 70+.
ما هو Simplellmfunc ومن يديره؟
| المؤلف | Ni Jingzhe |
| الفئة | Uncategorized |
| المصدر | https://pypi.org/project/SimpleLLMFunc/ |
الامتثال التنظيمي
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| الاختصاص القضائيs | Assessed across 52 ولاية قضائيةs |
What Is Simplellmfunc?
Simplellmfunc is a software tool in the uncategorized category: A lightweight yet complete LLM/Agent application development framework. Provides decorators that use function docstrings as prompts, requiring no function body implementation while allowing you to benefit from function definitions and type annotations for higher development efficiency. Seamlessly in. Nerq درجة الثقة: 54/100 (D).
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 Simplellmfunc's Safety
Nerq's درجة الثقة is calculated from 13+ independent signals aggregated into five أبعاد. Here is how Simplellmfunc performs in each:
- Compliance (100/100): Simplellmfunc is broadly compliant. Assessed against regulations in 52 ولاية قضائيةs including the EU AI Act, CCPA, and GDPR.
The overall درجة الثقة of 53.7/100 (D) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Simplellmfunc?
Simplellmfunc is designed for:
- المطورs and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Simplellmfunc is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
كيفية Verify Simplellmfunc's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for ثغرات أمنية معروفة in Simplellmfunc's dependency tree. - مراجعة permissions — Understand what access Simplellmfunc requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Simplellmfunc 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=SimpleLLMFunc - مراجعة the license — Confirm that Simplellmfunc'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.
- 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 Simplellmfunc
When evaluating whether Simplellmfunc is safe, consider these category-specific risks:
Understand how Simplellmfunc processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Simplellmfunc's dependency tree for ثغرات أمنية معروفة. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Simplellmfunc. الأمان patches and bug fixes are only effective if you're running the latest version.
If Simplellmfunc 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 Simplellmfunc's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Simplellmfunc in violation of its license can expose your organization to legal liability.
Best Practices for Using Simplellmfunc Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Simplellmfunc while minimizing risk:
Periodically review how Simplellmfunc is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Simplellmfunc and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Simplellmfunc only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Simplellmfunc's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Simplellmfunc is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Simplellmfunc?
Even promising tools aren't right for every situation. Consider avoiding Simplellmfunc in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Simplellmfunc's trust score of 53.7/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Simplellmfunc Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average درجة الثقة is 62/100. Simplellmfunc's score of 53.7/100 is near the category average of 62/100.
This places Simplellmfunc in line with the typical uncategorized tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.
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 Simplellmfunc 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, Simplellmfunc'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 Simplellmfunc's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=SimpleLLMFunc&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 Simplellmfunc are strengthening or weakening over time.
النقاط الرئيسية
- Simplellmfunc has a درجة الثقة of 53.7/100 (D) and is not yet Nerq Verified.
- Simplellmfunc shows متوسط trust signals. Conduct thorough due diligence before deploying to production environments.
- Among uncategorized tools, Simplellmfunc scores near the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
ما البيانات التي يجمعها Simplellmfunc؟
الخصوصية assessment for Simplellmfunc is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
هل Simplellmfunc آمن؟
درجة الأمان: under assessment. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
تحليل كامل: Simplellmfunc الأمان Report
كيف حسبنا هذه الدرجة
Simplellmfunc's trust score of 53.7/100 (D) يُحسب من multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 0 independent أبعاد: . يتم ترجيح كل بُعد بالتساوي لإنتاج درجة الثقة المركبة.
يحلل Nerq أكثر من 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. يتم تحديث النتائج باستمرار عند توفر بيانات جديدة.
This page was last reviewed on April 26, 2026. إصدار البيانات: 1.0.
الأسئلة الشائعة
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