Är Openllmetry säker?
Openllmetry — Nerq Förtroendepoäng 70.6/100 (Betyg B). Baserat på analys av 5 tillitsdimensioner bedöms det som generellt säkert men med vissa farhågor. Senast uppdaterad: 2026-03-31.
Ja, Openllmetry är säker att använda. Openllmetry is a software tool med ett Nerq-förtroendepoäng på 70.6/100 (B), based on 5 independent data dimensions. It is recommended for use. Security: 0/100. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-31. Maskinläsbar data (JSON).
Är Openllmetry säker?
JA — Openllmetry har ett Nerq-förtroendepoäng på 70.6/100 (B). Uppfyller Nerqs förtroendetröskel med starka signaler inom säkerhet, underhåll och communityanvändning. Recommended for use — se hela rapporten nedan för specifika överväganden.
Vad är Openllmetrys förtroendepoäng?
Openllmetry har ett Nerq-förtroendepoäng på 70.6/100, earning a B grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
Vilka är de viktigaste säkerhetsresultaten för Openllmetry?
Openllmetry's strongest signal is regelefterlevnad at 100/100. No kända sårbarheter have been detected. It meets the Nerq Verified threshold of 70+.
Vad är Openllmetry och vem underhåller det?
| Utvecklare | Unknown |
| Kategori | AI tool |
| Stjärnor | 6,846 |
| Källa | https://github.com/traceloop/openllmetry |
Regelefterlevnad
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Populära alternativ inom AI tool
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 Förtroendepoäng: 71/100 (B).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Openllmetry's Safety
Nerq's Förtroendepoäng is calculated from 13+ independent signals aggregated into five dimensions. Here is how Openllmetry performs in each:
- Säkerhet (0/100): Openllmetry's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Underhåll (0/100): Openllmetry is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (100/100): Openllmetry is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Förtroendepoäng 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:
- Developers and teams working with AI tool tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Openllmetry meets the minimum threshold for production use, but we recommend monitoring for security 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:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for kända sårbarheter in Openllmetry's dependency tree. - Recension permissions — Understand what access Openllmetry requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Openllmetry 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=traceloop/openllmetry - Granska 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.
- 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 security 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:
Understand how Openllmetry processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Openllmetry's dependency tree for kända sårbarheter. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Openllmetry. Security patches and bug fixes are only effective if you're running the latest version.
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.
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:
Periodically review how Openllmetry is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Openllmetry and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Openllmetry only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Openllmetry's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
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:
- Scenarios where Openllmetry's specific capabilities exceed your actual needs — simpler tools may be safer
- Air-gapped environments where the tool cannot receive security updates
- Projects with strict regulatory requirements that haven't been explicitly validated
For each scenario, evaluate whether Openllmetry är 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 Förtroendepoäng 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 dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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.
Förtroendepoäng History
Nerq continuously monitors Openllmetry and recalculates its Förtroendepoäng 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 maintenance 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 security and quality. Conversely, a downward trend may signal reduced maintenance, 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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Openllmetry are strengthening or weakening over time.
Openllmetry vs Alternatives
In the AI tool category, Openllmetry scores 70.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Openllmetry vs openclaw — Förtroendepoäng: 84.3/100
- Openllmetry vs stable-diffusion-webui — Förtroendepoäng: 69.3/100
- Openllmetry vs prompts.chat — Förtroendepoäng: 69.3/100
Viktigaste slutsatser
- Openllmetry has a Förtroendepoäng of 70.6/100 (B) and is Nerq Verified.
- Openllmetry meets the minimum threshold for production deployment, though monitoring and additional guardrails are recommended.
- Among AI tool tools, Openllmetry scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Vanliga frågor
Är Openllmetry säker att använda?
Vad är Openllmetry's trust score?
Vilka säkrare alternativ finns till Openllmetry?
How often is Openllmetry's safety score updated?
Kan jag använda Openllmetry i en reglerad miljö?
Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.