Er Jinni sikker?

Jinni — Nerq Trust Score 59.0/100 (Karakter D). Score baseret på 4 independent trust signals.

Jinni er en software tool med en Nerq Tillidsscore på 59.0/100 (D), based on 4 uafhængige datadimensioner. Vedligeholdelse: 0/100. Popularitet: 1/100. Data hentet fra flere offentlige kilder herunder pakkeregistre, GitHub, NVD, OSV.dev og OpenSSF Scorecard. Sidst opdateret: n/a. Maskinlæsbare data (JSON).

Er Jinni sikker?

Tillidsscore detaljer — Jinni has a Nerq Trust Score of 59.0/100 (D). Measured across 4 independent trust signals.

Sikkerhedsanalyse → Jinni privatlivsrapport →

Hvad er Jinnis tillidsscore?

Jinni har en Nerq Trust Score på 59.0/100 med karakteren D. Denne score er baseret på 4 uafhængigt målte dimensioner, herunder sikkerhed, vedligeholdelse og community-adoption.

Overholdelse
100
Vedligeholdelse
0
Dokumentation
0
Popularitet
1

Hvad er de vigtigste sikkerhedsresultater for Jinni?

Jinnis stærkeste signal er overholdelse på 100/100. Ingen kendte sårbarheder er fundet.

⚠Vedligeholdelse: 0/100 — lav vedligeholdelsesaktivitet
⚠Overholdelse: 100/100 — covers 52 of 52 jurisdictions
⚠Dokumentation: 0/100 — begrænset dokumentation
⚠Popularitet: 1/100 — 270 stjerner på mcp registry

Hvad er Jinni og hvem vedligeholder det?

Udviklersmat-dev
KategoriInfrastructure
Stjerner270
Kildehttps://github.com/smat-dev/jinni
Protocolsmcp

Lovgivningsmæssig overholdelse

EU AI Act Risk ClassNot assessed
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdictions

Populære alternativer i infrastructure

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What Is Jinni?

Jinni is a software tool in the infrastructure category: Bring your project into LLM context - tool and MCP server. It has 270 GitHub stars. Nerq Trust Score: 59/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including sikkerhed vulnerabilities, vedligeholdelse activity, license overholdelse, and fællesskabsadoption.

How Nerq Assesses Jinni's Safety

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

The overall Trust Score of 59.0/100 (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 Jinni?

Jinni is commonly evaluated by:

How to read the signals: Jinni's measured signals (vedligeholdelse 0/100, dokumentation 0/100, community 1/100) 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 Jinni's Safety Yourself

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

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

Common Safety Concerns with Jinni

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

Data handling

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

Dependency sikkerhed

Check Jinni's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher sikkerhed risk.

Update frequency

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

Third-party integrations

If Jinni 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 overholdelse

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

Best Practices for Using Jinni Safely

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

Conduct regular audits

Periodically review how Jinni is used in your workflow. Check for unexpected behavior, permissions drift, and overholdelse with your sikkerhed policies.

Keep dependencies updated

Ensure Jinni and all its dependencies are running the latest stable versions to benefit from sikkerhed patches.

Follow least privilege

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

Monitor for sikkerhed advisories

Subscribe to Jinni's sikkerhed 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 Jinni is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Jinni

Nerq's signals are one input. In the following situations, evaluate Jinni's measured signals against your own requirements before making a decision:

For each situation, compare Jinni's measured trust score of 59.0/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Jinni is suitable for any particular use.

How Jinni Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among infrastructure tools, the average Trust Score is 62/100. Jinni's score of 59.0/100 is near the category average of 62/100.

This places Jinni in line with the typical infrastructure 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 moderat 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 Jinni 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 vedligeholdelse patterns change, Jinni'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 sikkerhed and quality. Conversely, a downward trend may signal reduced vedligeholdelse, growing technical debt, or unresolved vulnerabilities. To track Jinni's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=jinni&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 — sikkerhed, vedligeholdelse, dokumentation, overholdelse, and community — has evolved independently, providing granular visibility into which aspects of Jinni are strengthening or weakening over time.

Jinni vs Alternativer

In the infrastructure category, Jinni scores 59.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Vigtigste pointer

Ofte stillede spørgsmål

Er Jinni sikker?
jinni med en Nerq Tillidsscore på 59.0/100 (D). Stærkeste signal: overholdelse (100/100). Score baseret på Vedligeholdelse (0/100), Popularitet (1/100), Dokumentation (0/100).
Hvad er Jinnis tillidsscore?
jinni: 59.0/100 (D). Score baseret på Vedligeholdelse (0/100), Popularitet (1/100), Dokumentation (0/100). Compliance: 100/100. Scorer opdateres når nye data bliver tilgængelige. API: GET nerq.ai/v1/preflight?target=jinni
Hvad er sikrere alternativer til Jinni?
I kategorien Infrastructure, higher-rated alternatives include n8n-io/n8n (69/100), langflow-ai/langflow (77/100), langgenius/dify (70/100). jinni scores 59.0/100.
Hvor ofte opdateres Jinnis sikkerhedsscore?
Nerq recomputes Jinni's trust score as new data becomes available. Current: 59.0/100 (D). API: GET nerq.ai/v1/preflight?target=jinni
Kan jeg bruge Jinni i et reguleret miljø?
Jinni: 59.0/100 (D). Compliance: 52 of 52 jurisdictions. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Se også

Disclaimer: Nerqs tillidsscorer er automatiserede vurderinger baseret på offentligt tilgængelige signaler. De udgør ikke anbefalinger eller garantier. Foretag altid din egen verificering.

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