Är Muma Mem säker?
Muma Mem — Nerq Trust Score 59.9/100 (Betyg D). Poäng baserad på 5 independent trust signals.
Muma Mem är en programvara med ett Nerq-förtroendepoäng på 59.9/100 (D), baserat på 5 oberoende datadimensioner. Säkerhet: 0/100. Underhåll: 1/100. Popularitet: 0/100. Data hämtad från flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Senast uppdaterad: n/a. Maskinläsbar data (JSON).
Är Muma Mem säker?
Förtroendepoäng i detalj — Muma Mem has a Nerq Trust Score of 59.9/100 (D). Measured across 5 independent trust signals.
Vad är Muma Mems förtroendepoäng?
Muma Mem har ett Nerq-förtroendepoäng på 59.9/100 med betyget D. Denna poäng baseras på 5 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.
Vilka är de viktigaste säkerhetsresultaten för Muma Mem?
Muma Mems starkaste signal är regelefterlevnad på 96/100. Inga kända sårbarheter har upptäckts.
Vad är Muma Mem och vem underhåller det?
| Utvecklare | blazejp83 |
| Kategori | Coding |
| Stjärnor | 1 |
| Källa | https://github.com/blazejp83/MUMA-Mem |
| Frameworks | openai · huggingface |
| Protocols | rest |
Regelefterlevnad
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 96/100 |
| Jurisdiktions | Assessed across 52 jurisdiktions |
Populära alternativ inom coding
What Is Muma Mem?
Muma Mem is a programvara 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-stjärnor. Nerq Trust Score: 60/100 (D).
Nerq independently analyzes every programvara, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.
How Nerq Assesses Muma Mem's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensioner. Here is how Muma Mem performs in each:
- Säkerhet (0/100): Muma Mem's säkerhet posture is poor. This score factors in known CVEs, dependency vulnerabilities, säkerhet policy presence, and code signing practices.
- Underhåll (1/100): Muma Mem 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 dokumentation, usage examples, and contribution guidelines.
- Compliance (96/100): Muma Mem is broadly compliant. Assessed against regulations in 52 jurisdiktions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Baserad på GitHub-stjärnor, forks, download counts, and ecosystem integrations.
The overall Trust Score of 59.9/100 (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 Muma Mem?
Muma Mem 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: Muma Mem's measured signals (säkerhet 0/100, underhåll 1/100, dokumentation 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 Muma Mem's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any programvara:
- Check the source code — Granska repository's säkerhet policy, open issues, and recent commits for signs of active underhåll.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Muma Mem's dependency tree. - Recension permissions — Understand what access Muma Mem requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Muma Mem 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=MUMA-Mem - Granska 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.
- 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 säkerhet 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:
Understand how Muma Mem processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Muma Mem's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.
Regularly check for updates to Muma Mem. Säkerhet patches and bug fixes are only effective if you're running the latest version.
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.
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 regelefterlevnad assessment covers 52 jurisdiktions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal regelefterlevnad.
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:
Periodically review how Muma Mem is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.
Ensure Muma Mem and all its dependencies are running the latest stable versions to benefit from säkerhet patches.
Grant Muma Mem only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Muma Mem's säkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Muma Mem is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Oberoende Review of Muma Mem
Nerq's signals are one input. In the following situations, evaluate Muma Mem'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 Muma Mem's measured trust score of 59.9/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Muma Mem is suitable for any particular use.
How Muma Mem Compares to Industry Standards
Nerq indexes over 6 million programvaras, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Muma Mem's score of 59.9/100 is near the category average of 62/100.
This places Muma Mem in line with the typical coding 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 måttlig 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 underhåll 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 säkerhet and quality. Conversely, a downward trend may signal reduced underhåll, 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 — säkerhet, underhåll, dokumentation, regelefterlevnad, and community — has evolved independently, providing granular visibility into which aspects of Muma Mem are strengthening or weakening over time.
Muma Mem vs Alternativ
In the coding category, Muma Mem scores 59.9/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Muma Mem vs AutoGPT — Trust Score: 65.3/100
- Muma Mem vs ollama — Trust Score: 64.4/100
- Muma Mem vs langchain — Trust Score: 77.0/100
Viktigaste slutsatser
- Muma Mem has a measured Nerq Trust Score of 59.9/100 (D) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Muma Mem scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — säkerhet, underhåll, dokumentation, regelefterlevnad, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Vanliga frågor
Är Muma Mem säker?
Vad är Muma Mems förtroendepoäng?
Vilka är säkrare alternativ till Muma Mem?
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Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.