Är Llmprojects säker?
Llmprojects — Nerq Förtroendepoäng 54.6/100 (Betyg D). Baserat på analys av 5 tillitsdimensioner bedöms det som har anmärkningsvärda säkerhetsproblem. Senast uppdaterad: 2026-04-04.
Använd Llmprojects med försiktighet. Llmprojects är en software tool med ett Nerq-förtroendepoäng på 54.6/100 (D), baserat på 5 oberoende datadimensioner. Ligger under den rekommenderade gränsen på 70. Säkerhet: 0/100. Underhåll: 1/100. Popularitet: 0/100. Data hämtad från multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Senast uppdaterad: 2026-04-04. Maskinläsbar data (JSON).
Är Llmprojects säker?
VAR FÖRSIKTIG — Llmprojects har ett Nerq-förtroendepoäng på 54.6/100 (D). Har måttliga förtroendesignaler men uppvisar vissa oroande områden. Lämplig för utvecklingsanvändning — granska säkerhets- och underhållssignaler innan produktionsdriftsättning.
Vad är Llmprojectss förtroendepoäng?
Llmprojects har ett Nerq-förtroendepoäng på 54.6/100 med betyget D. Denna poäng baseras på 5 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.
Vilka är de viktigaste säkerhetsresultaten för Llmprojects?
Llmprojectss starkaste signal är regelefterlevnad på 48/100. Inga kända sårbarheter har upptäckts. Har ännu inte nått Nerqs verifieringströskel på 70+.
Vad är Llmprojects och vem underhåller det?
| Utvecklare | udit0303 |
| Kategori | health |
| Källa | https://github.com/udit0303/LLMprojects |
| Frameworks | langchain · openai |
| Protocols | mcp · rest |
Regelefterlevnad
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 48/100 |
| Jurisdiktions | Assessed across 52 jurisdiktions |
Populära alternativ inom health
What Is Llmprojects?
Llmprojects is a software tool in the health category: A medical bot that answers patient questions about food-drug interactions.. Nerq Förtroendepoäng: 55/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.
How Nerq Assesses Llmprojects's Safety
Nerq's Förtroendepoäng is calculated from 13+ independent signals aggregated into five dimensioner. Here is how Llmprojects performs in each:
- Säkerhet (0/100): Llmprojects's säkerhet posture is poor. This score factors in known CVEs, dependency vulnerabilities, säkerhet policy presence, and code signing practices.
- Underhåll (1/100): Llmprojects 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 (48/100): Llmprojects is regelefterlevnad gaps exist. Assessed against regulations in 52 jurisdiktions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Baserad på GitHub stars, forks, download counts, and ecosystem integrations.
The overall Förtroendepoäng of 54.6/100 (D) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Llmprojects?
Llmprojects is designed for:
- Developers and teams working with health tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Llmprojects is suitable for development and testing environments. Before production deployment, conduct a thorough review of its säkerhet posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Llmprojects's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- 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 kända sårbarheter in Llmprojects's dependency tree. - Recension permissions — Understand what access Llmprojects requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Llmprojects 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=LLMprojects - Granska license — Confirm that Llmprojects'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 Llmprojects
When evaluating whether Llmprojects is safe, consider these category-specific risks:
Understand how Llmprojects processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Llmprojects's dependency tree for kända sårbarheter. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.
Regularly check for updates to Llmprojects. Säkerhet patches and bug fixes are only effective if you're running the latest version.
If Llmprojects 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 Llmprojects's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Llmprojects in violation of its license can expose your organization to legal liability.
Llmprojects and the EU AI Act
Llmprojects 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 Llmprojects Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Llmprojects while minimizing risk:
Periodically review how Llmprojects is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.
Ensure Llmprojects and all its dependencies are running the latest stable versions to benefit from säkerhet patches.
Grant Llmprojects only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Llmprojects's säkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Llmprojects is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Llmprojects?
Even promising tools aren't right for every situation. Consider avoiding Llmprojects in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional regelefterlevnad review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Llmprojects är 54.6/100 meets your organization's risk tolerance. We recommend running a manual säkerhet assessment alongside the automated Nerq score.
How Llmprojects Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among health tools, the average Förtroendepoäng is 62/100. Llmprojects's score of 54.6/100 is near the category average of 62/100.
This places Llmprojects in line with the typical health 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.
Förtroendepoäng History
Nerq continuously monitors Llmprojects 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 underhåll patterns change, Llmprojects'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 Llmprojects's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=LLMprojects&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 Llmprojects are strengthening or weakening over time.
Llmprojects vs Alternativ
In the health category, Llmprojects scores 54.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Llmprojects vs MedicalGPT — Förtroendepoäng: 62.6/100
- Llmprojects vs open-health — Förtroendepoäng: 62.6/100
- Llmprojects vs Awesome-AI4Med — Förtroendepoäng: 62.6/100
Viktigaste slutsatser
- Llmprojects has a Förtroendepoäng of 54.6/100 (D) and is not yet Nerq Verified.
- Llmprojects shows måttlig trust signals. Conduct thorough due diligence before deploying to production environments.
- Among health tools, Llmprojects scores near the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Vanliga frågor
Är Llmprojects säker att använda?
Vad är Llmprojects's trust score?
Vilka säkrare alternativ finns till Llmprojects?
How often is Llmprojects's safety score updated?
Kan jag använda Llmprojects 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.