Muma Mem Güvenli mi?

Muma Mem — Nerq Trust Score 68.8/100 (C notu). 5 güven boyutunun analizine dayanarak, genel olarak güvenli ancak bazı endişeler var olarak değerlendirilmektedir. Son güncelleme: 2026-06-21.

Muma Mem kullanırken dikkatli olun. Muma Mem bir software tool Nerq Güven Puanı ile 68.8/100 (C), based on 5 bağımsız veri boyutu. Nerq Doğrulanmış eşiğinin altında Güvenlik: 0/100. Bakım: 1/100. Popülerlik: 0/100. Veriler şuradan alınmıştır: paket kayıtları, GitHub, NVD, OSV.dev ve OpenSSF Scorecard dahil birden fazla genel kaynak. Son güncelleme: 2026-06-21. Makine tarafından okunabilir veri (JSON).

Muma Mem Güvenli mi?

CAUTION — Muma Mem has a Nerq Trust Score of 68.8/100 (C). Orta düzeyde güven sinyallerine sahip olmakla birlikte bazı endişe alanları göstermektedir that warrant attention. Suitable for development use — review güvenlik and bakım signals before production deployment.

Güvenlik Analizi → Muma Mem Gizlilik Raporu →

Muma Mem'in güven puanı nedir?

Muma Mem'in Nerq Güven Puanı 68.8/100 olup C notu almıştır. Bu puan 5 bağımsız olarak ölçülen boyuta dayanmaktadır.

Güvenlik
0
Uyumluluk
96
Bakım
1
Dokümantasyon
1
Popülerlik
0

Muma Mem için temel güvenlik bulguları nelerdir?

Muma Mem'in en güçlü sinyali 96/100 ile uyumluluk'dir. Bilinen güvenlik açığı tespit edilmemiştir. Henüz Nerq Doğrulanmış eşiğine (70+) ulaşamamıştır.

Güvenlik puanı: 0/100 (zayıf)
Bakım: 1/100 — düşük bakım etkinliği
Uyumluluk: 96/100 — covers 49 of 52 jurisdictions
Dokümantasyon: 1/100 — sınırlı belgeleme
Popülerlik: 0/100 — 1 yıldız github

Muma Mem nedir ve kim tarafından yönetilmektedir?

Geliştiriciblazejp83
KategoriCoding
Yıldız1
Kaynakhttps://github.com/blazejp83/MUMA-Mem
Frameworksopenai · huggingface
Protocolsrest

Düzenleyici Uyumluluk

EU AI Act Risk ClassMINIMAL
Compliance Score96/100
JurisdictionsAssessed across 52 jurisdictions

coding kategorisindeki popüler alternatifler

Significant-Gravitas/AutoGPT
61.8/100 · C+
github
ollama/ollama
56.5/100 · C
github
langchain-ai/langchain
69.8/100 · B-
github
x1xhlol/system-prompts-and-models-of-ai-tools
55.0/100 · C
github
anomalyco/opencode
62.6/100 · C+
github

What Is Muma Mem?

Muma Mem is a software tool in the coding category: MUMA-Mem is a multi-user multi-agent memory system for OpenClaw, enhancing memory management with intelligent features.. It has 1 GitHub stars. Nerq Trust Score: 69/100 (C).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including güvenlik vulnerabilities, bakım activity, license uyumluluk, and topluluk benimsemesi.

How Nerq Assesses Muma Mem's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five boyut. Here is how Muma Mem performs in each:

The overall Trust Score of 68.8/100 (C) 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 Muma Mem?

Muma Mem is designed for:

Risk guidance: Muma Mem is suitable for development and testing environments. Before production deployment, conduct a thorough review of its güvenlik posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Muma Mem's Safety Yourself

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

  1. Check the source code — İnceleyin repository's güvenlik policy, open issues, and recent commits for signs of active bakım.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Muma Mem's dependency tree.
  3. İnceleme permissions — Understand what access Muma Mem requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Muma Mem 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=MUMA-Mem
  6. İnceleyin license — Confirm that Muma Mem'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.
  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 güvenlik concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Muma Mem

When evaluating whether Muma Mem is safe, consider these category-specific risks:

Data handling

Understand how Muma Mem processes, stores, and transmits your data. İnceleyin tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency güvenlik

Check Muma Mem's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher güvenlik risk.

Update frequency

Regularly check for updates to Muma Mem. Güvenlik patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Muma Mem 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.

License and IP uyumluluk

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

Muma Mem and the EU AI Act

Muma Mem 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 uyumluluk assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal uyumluluk.

Best Practices for Using Muma Mem Safely

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

Conduct regular audits

Periodically review how Muma Mem is used in your workflow. Check for unexpected behavior, permissions drift, and uyumluluk with your güvenlik policies.

Keep dependencies updated

Ensure Muma Mem and all its dependencies are running the latest stable versions to benefit from güvenlik patches.

Follow least privilege

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

Monitor for güvenlik advisories

Subscribe to Muma Mem's güvenlik 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 Muma Mem is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Muma Mem?

Even promising tools aren't right for every situation. Consider avoiding Muma Mem in these scenarios:

For each scenario, evaluate whether Muma Mem's trust score of 68.8/100 meets your organization's risk tolerance. We recommend running a manual güvenlik assessment alongside the automated Nerq score.

How Muma Mem 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. Muma Mem's score of 68.8/100 is above the category average of 62/100.

This positions Muma Mem favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust boyut.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks orta 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 Muma Mem 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 bakım patterns change, Muma Mem'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 güvenlik and quality. Conversely, a downward trend may signal reduced bakım, growing technical debt, or unresolved vulnerabilities. To track Muma Mem's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=MUMA-Mem&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 — güvenlik, bakım, dokümantasyon, uyumluluk, and community — has evolved independently, providing granular visibility into which aspects of Muma Mem are strengthening or weakening over time.

Muma Mem vs Alternatifler

In the coding category, Muma Mem scores 68.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Temel Çıkarımlar

Sık Sorulan Sorular

Muma Mem Güvenli mi?
Dikkatli kullanın. MUMA-Mem Nerq Güven Puanı ile 68.8/100 (C). En güçlü sinyal: uyumluluk (96/100). Puan şuna dayalı: Güvenlik (0/100), Bakım (1/100), Popülerlik (0/100), Dokümantasyon (1/100).
Muma Mem'in güven puanı nedir?
MUMA-Mem: 68.8/100 (C). Puan şuna dayalı: Güvenlik (0/100), Bakım (1/100), Popülerlik (0/100), Dokümantasyon (1/100). Compliance: 96/100. Yeni veriler mevcut olduğunda puanlar güncellenir. API: GET nerq.ai/v1/preflight?target=MUMA-Mem
Muma Mem için daha güvenli alternatifler nelerdir?
Coding kategorisinde, higher-rated alternatives include Significant-Gravitas/AutoGPT (62/100), ollama/ollama (56/100), langchain-ai/langchain (70/100). MUMA-Mem scores 68.8/100.
Muma Mem güvenlik puanı ne sıklıkla güncellenir?
Nerq continuously monitors Muma Mem and updates its trust score as new data becomes available. Current: 68.8/100 (C), last doğrulanmış 2026-06-21. API: GET nerq.ai/v1/preflight?target=MUMA-Mem
Muma Mem'i düzenlenmiş bir ortamda kullanabilir miyim?
Muma Mem Nerq doğrulama eşiği olan 70'e ulaşmadı. Ek inceleme önerilir.
API: /v1/preflight Trust Badge API Docs

Ayrıca bakınız

Disclaimer: Nerq güven puanları, kamuya açık sinyallere dayanan otomatik değerlendirmelerdir. Tavsiye veya garanti niteliğinde değildir. Her zaman kendi doğrulamanızı yapın.

Analiz ve önbelleğe alma için çerezler kullanıyoruz. Gizlilik