Czy Openllmetry jest bezpieczny?

Openllmetry — Nerq Wynik zaufania 70.6/100 (Ocena B). Na podstawie analizy 5 wymiarów zaufania, jest ogólnie bezpieczny, ale z pewnymi zastrzeżeniami. Ostatnia aktualizacja: 2026-04-03.

Tak, Openllmetry jest bezpieczny w użyciu. Openllmetry is a software tool with a Nerq Wynik zaufania of 70.6/100 (B), based on 5 niezależnych wymiarów danych. It is recommended for use. Bezpieczeństwo: 0/100. Konserwacja: 0/100. Popularity: 0/100. Dane pochodzą z multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Ostatnia aktualizacja: 2026-04-03. Dane odczytywalne maszynowo (JSON).

Czy Openllmetry jest bezpieczny?

TAK — Openllmetry has a Nerq Wynik zaufania of 70.6/100 (B). Spełnia próg zaufania Nerq z silnymi sygnałami w zakresie bezpieczeństwa, konserwacji i przyjęcia przez społeczność. Recommended for use — zapoznaj się z pełnym raportem poniżej, aby uzyskać szczegółowe informacje.

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Jaki jest wynik zaufania Openllmetry?

Openllmetry has a Nerq Wynik zaufania of 70.6/100, earning a B grade. This score is based on 5 independently measured wymiarów including bezpieczeństwo, konserwacja, and przyjęcie przez społeczność.

Bezpieczeństwo
0
Zgodność
100
Konserwacja
0
Dokumentacja
0
Popularność
0

Jakie są kluczowe ustalenia bezpieczeństwa dla Openllmetry?

Openllmetry's strongest signal is zgodność at 100/100. No known vulnerabilities have been detected. It meets the Nerq Verified threshold of 70+.

Wynik bezpieczeństwa: 0/100 (weak)
Konserwacja: 0/100 — niska aktywność utrzymania
Compliance: 100/100 — covers 52 of 52 jurisdictions
Documentation: 0/100 — ograniczona dokumentacja
Popularity: 0/100 — 6,846 gwiazdek na github

Czym jest Openllmetry i kto go utrzymuje?

AutorUnknown
KategoriaAI tool
Gwiazdki6,846
Źródłohttps://github.com/traceloop/openllmetry

Zgodność z przepisami

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

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What Is Openllmetry?

Openllmetry is a software tool in the AI tool category: Open-source observability for your GenAI or LLM application, based on OpenTelemetry. It has 6,846 GitHub stars. Nerq Wynik zaufania: 71/100 (B).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpieczeństwo vulnerabilities, konserwacja activity, license zgodność, and przyjęcie przez społeczność.

How Nerq Assesses Openllmetry's Safety

Nerq's Wynik zaufania is calculated from 13+ independent signals aggregated into five wymiarów. Here is how Openllmetry performs in each:

The overall Wynik zaufania of 70.6/100 (B) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.

Who Should Use Openllmetry?

Openllmetry is designed for:

Risk guidance: Openllmetry meets the minimum threshold for production use, but we recommend monitoring for bezpieczeństwo advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

How to Verify Openllmetry's Safety Yourself

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

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

Common Safety Concerns with Openllmetry

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

Data handling

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

Dependency bezpieczeństwo

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

Update frequency

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

Third-party integrations

If Openllmetry 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 zgodność

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

Best Practices for Using Openllmetry Safely

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

Conduct regular audits

Periodically review how Openllmetry is used in your workflow. Check for unexpected behavior, permissions drift, and zgodność with your bezpieczeństwo policies.

Keep dependencies updated

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

Follow least privilege

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

Monitor for bezpieczeństwo advisories

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

When Should You Avoid Openllmetry?

Even well-trusted tools aren't right for every situation. Consider avoiding Openllmetry in these scenarios:

wynik zaufania

For each scenario, evaluate whether Openllmetry 70.6/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Openllmetry Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among AI tool tools, the average Wynik zaufania is 62/100. Openllmetry's score of 70.6/100 is above the category average of 62/100.

This positions Openllmetry favorably among AI tool tools. While it outperforms the average, there is still room for improvement in certain trust wymiarów.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks umiarkowany 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.

Wynik zaufania History

Nerq continuously monitors Openllmetry and recalculates its Wynik zaufania 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 konserwacja patterns change, Openllmetry'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 bezpieczeństwo and quality. Conversely, a downward trend may signal reduced konserwacja, growing technical debt, or unresolved vulnerabilities. To track Openllmetry's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=traceloop/openllmetry&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 — bezpieczeństwo, konserwacja, dokumentacja, zgodność, and community — has evolved independently, providing granular visibility into which aspects of Openllmetry are strengthening or weakening over time.

Openllmetry vs Alternatywy

In the AI tool category, Openllmetry uzyskuje 70.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kluczowe wnioski

Często zadawane pytania

Czy Openllmetry jest bezpieczny w użyciu?
Tak, jest bezpieczny w użyciu. traceloop/openllmetry has a Nerq Wynik zaufania of 70.6/100 (B). Najsilniejszy sygnał: zgodność (100/100). Wynik oparty na bezpieczeństwo (0/100), konserwacja (0/100), popularność (0/100), dokumentacja (0/100).
Czym jest Openllmetry's trust score?
traceloop/openllmetry: 70.6/100 (B). Wynik oparty na: bezpieczeństwo (0/100), konserwacja (0/100), popularność (0/100), dokumentacja (0/100). Compliance: 100/100. Wyniki są aktualizowane wraz z pojawianiem się nowych danych. API: GET nerq.ai/v1/preflight?target=traceloop/openllmetry
Jakie są bezpieczniejsze alternatywy dla Openllmetry?
In the AI tool category, alternatywy z wyższym wynikiem to: openclaw/openclaw (84/100), AUTOMATIC1111/stable-diffusion-webui (69/100), f/prompts.chat (69/100). traceloop/openllmetry uzyskuje 70.6/100.
How often is Openllmetry's safety score updated?
Nerq continuously monitors Openllmetry and updates its trust score as new data becomes available. Dane pochodzą z multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 70.6/100 (B), last zweryfikowane 2026-04-03. API: GET nerq.ai/v1/preflight?target=traceloop/openllmetry
Czy mogę używać Openllmetry w środowisku regulowanym?
Yes — Openllmetry meets the Nerq Verified threshold (70+). Combine this with your internal bezpieczeństwo review for regulated deployments.
API: /v1/preflight Trust Badge API Docs

Disclaimer: Wyniki zaufania Nerq to zautomatyzowane oceny oparte na publicznie dostępnych sygnałach. Nie stanowią rekomendacji ani gwarancji. Zawsze przeprowadzaj własną weryfikację.

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