Är Model Radar säker?

Model Radar — Nerq Trust Score 38.9/100 (Betyg E). Baserat på analys av 5 tillitsdimensioner bedöms det som har betydande säkerhetsrisker. Senast uppdaterad: 2026-04-23.

Var försiktig med Model Radar. Model Radar är en programvara med ett Nerq-förtroendepoäng på 38.9/100 (E). Under Nerqs verifierade tröskel Data hämtad från flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Senast uppdaterad: 2026-04-23. Maskinläsbar data (JSON).

Är Model Radar säker?

NO — USE WITH CAUTION — Model Radar has a Nerq Trust Score of 38.9/100 (E). Har lägre än genomsnittliga förtroendesignaler med betydande luckor in säkerhet, underhåll, or dokumentation. Not recommended for production use without thorough manual review and additional säkerhet measures.

Säkerhetsanalys → Model Radar integritetsrapport →

Vad är Model Radars förtroendepoäng?

Model Radar har ett Nerq-förtroendepoäng på 38.9/100 med betyget E. Denna poäng baseras på 5 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.

Övergripande förtroende
38.9

Vilka är de viktigaste säkerhetsresultaten för Model Radar?

Model Radars starkaste signal är övergripande förtroende på 38.9/100. Inga kända sårbarheter har upptäckts. Har ännu inte nått Nerqs verifieringströskel på 70+.

Sammansatt förtroendepoäng: 38.9/100 utifrån alla tillgängliga signaler

Vad är Model Radar och vem underhåller det?

Utvecklarehttps://github.com/srclight/model-radar
KategoriUncategorized
Källahttps://github.com/srclight/model-radar

What Is Model Radar?

Model Radar is a programvara in the uncategorized category: Pings and ranks 130+ free coding LLM models across 17 providers by latency in real-time.. Nerq Trust Score: 39/100 (E).

Nerq independently analyzes every programvara, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.

How Nerq Assesses Model Radar's Safety

Nerq evaluates every programvara across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core dimensioner: Säkerhet (known CVEs, dependency vulnerabilities, säkerhet policies), Underhåll (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 jurisdiktions), and Community (stars, forks, downloads, ecosystem integrations).

Model Radar receives an overall Trust Score of 38.9/100 (E), which Nerq considers low. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.

Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=Model Radar

Each dimension is weighted according to its importance for the tool's category. For example, Säkerhet and Underhåll carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Model Radar's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five dimensioner, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).

Who Should Use Model Radar?

Model Radar is designed for:

Risk guidance: We recommend caution with Model Radar. The low trust score suggests potential risks in säkerhet, underhåll, or community support. Consider using a more established alternative for any production or sensitive workload.

How to Verify Model Radar's Safety Yourself

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

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

Common Safety Concerns with Model Radar

When evaluating whether Model Radar is safe, consider these category-specific risks:

Data handling

Understand how Model Radar processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency säkerhet

Check Model Radar's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.

Update frequency

Regularly check for updates to Model Radar. Säkerhet patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Model Radar 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 regelefterlevnad

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

Best Practices for Using Model Radar Safely

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

Conduct regular audits

Periodically review how Model Radar is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.

Keep dependencies updated

Ensure Model Radar and all its dependencies are running the latest stable versions to benefit from säkerhet patches.

Follow least privilege

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

Monitor for säkerhet advisories

Subscribe to Model Radar's säkerhet 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 Model Radar is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Model Radar?

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

For each scenario, evaluate whether Model Radar's trust score of 38.9/100 meets your organization's risk tolerance. We recommend running a manual säkerhet assessment alongside the automated Nerq score.

How Model Radar Compares to Industry Standards

Nerq indexes over 6 million programvaras, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Model Radar's score of 38.9/100 is below the category average of 62/100.

This suggests that Model Radar trails behind many comparable uncategorized tools. Organizations with strict säkerhet 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 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 Model Radar 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, Model Radar'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 Model Radar's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Model Radar&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 Model Radar are strengthening or weakening over time.

Viktigaste slutsatser

Vilka data samlar Model Radar in?

Integritet assessment for Model Radar is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.

Är Model Radar säker?

Säkerhetspoäng: under granskning. Review säkerhet practices and consider alternatives with higher säkerhet scores for sensitive use cases.

Nerq övervakar denna entitet mot NVD, OSV.dev och registerspecifika sårbarhetsdatabaser för löpande säkerhetsbedömning.

Fullständig analys: Model Radar säkerhetsrapport

Så beräknade vi denna poäng

Model Radar's trust score of 38.9/100 (E) beräknas utifrån flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Poängen speglar 0 oberoende dimensioner: . Varje dimension ges lika vikt för att producera den sammansatta förtroendepoängen.

Nerq analyserar över 7,5 miljoner entiteter i 26 register med samma metodik, vilket möjliggör direkt jämförelse mellan entiteter. Poäng uppdateras löpande när ny data finns tillgänglig.

Den här sidan granskades senast April 23, 2026. Dataversion: 1.0.

Fullständig metodikdokumentation · Maskinläsbar data (JSON API)

Vanliga frågor

Är Model Radar säker?
Var försiktig. Model Radar med ett Nerq-förtroendepoäng på 38.9/100 (E). Starkaste signalen: övergripande förtroende (38.9/100). Poäng baserad på multiple trust dimensioner.
Vad är Model Radars förtroendepoäng?
Model Radar: 38.9/100 (E). Poäng baserad på multiple trust dimensioner. Poäng uppdateras när ny data finns tillgänglig. API: GET nerq.ai/v1/preflight?target=Model Radar
Vilka är säkrare alternativ till Model Radar?
I kategorin Uncategorized, fler programvara analyseras — kom tillbaka snart. Model Radar scores 38.9/100.
Hur ofta uppdateras Model Radars säkerhetspoäng?
Nerq continuously monitors Model Radar and updates its trust score as new data becomes available. Current: 38.9/100 (E), last verifierad 2026-04-23. API: GET nerq.ai/v1/preflight?target=Model Radar
Kan jag använda Model Radar i en reglerad miljö?
Model Radar har inte nått Nerqs verifieringsgräns på 70. Ytterligare granskning rekommenderas.
API: /v1/preflight Trust Badge API Docs

Se även

Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.

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