Är Lilisa säker?
Lilisa — Nerq Trust Score 50.2/100 (Betyg D). Poäng baserad på 1 independent trust signals.
Lilisa är en programvara med ett Nerq-förtroendepoäng på 50.2/100 (D), baserat på 3 oberoende datadimensioner. Data hämtad från flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Senast uppdaterad: n/a. Maskinläsbar data (JSON).
Är Lilisa säker?
Förtroendepoäng i detalj — Lilisa has a Nerq Trust Score of 50.2/100 (D). Measured across 1 independent trust signal.
Vad är Lilisas förtroendepoäng?
Lilisa har ett Nerq-förtroendepoäng på 50.2/100 med betyget D. Denna poäng baseras på 1 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.
Vilka är de viktigaste säkerhetsresultaten för Lilisa?
Lilisas starkaste signal är regelefterlevnad på 100/100. Inga kända sårbarheter har upptäckts.
Vad är Lilisa och vem underhåller det?
| Utvecklare | darrel99 |
| Kategori | Uncategorized |
| Källa | https://huggingface.co/darrel99/lilisa |
| Protocols | huggingface_hub |
Regelefterlevnad
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdiktions | Assessed across 52 jurisdiktions |
What Is Lilisa?
Lilisa is a programvara in the uncategorized category available on huggingface_full. Nerq Trust Score: 50/100 (D).
Nerq independently analyzes every programvara, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.
How Nerq Assesses Lilisa's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensioner. Here is how Lilisa performs in each:
- Compliance (100/100): Lilisa is broadly compliant. Assessed against regulations in 52 jurisdiktions including the EU AI Act, CCPA, and GDPR.
The overall Trust Score of 50.2/100 (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 Lilisa?
Lilisa is commonly evaluated by:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Lilisa's measured signals (the trust signals above) 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 Lilisa's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any programvara:
- Check the source code — Granska repository säkerhet policy, open issues, and recent commits for signs of active underhåll.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Lilisa's dependency tree. - Recension permissions — Understand what access Lilisa requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Lilisa 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=lilisa - Granska license — Confirm that Lilisa'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 Lilisa
When evaluating whether Lilisa is safe, consider these category-specific risks:
Understand how Lilisa processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Lilisa's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.
Regularly check for updates to Lilisa. Säkerhet patches and bug fixes are only effective if you're running the latest version.
If Lilisa 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 Lilisa's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Lilisa in violation of its license can expose your organization to legal liability.
Best Practices for Using Lilisa Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Lilisa while minimizing risk:
Periodically review how Lilisa is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.
Ensure Lilisa and all its dependencies are running the latest stable versions to benefit from säkerhet patches.
Grant Lilisa only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Lilisa's säkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Lilisa is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Oberoende Review of Lilisa
Nerq's signals are one input. In the following situations, evaluate Lilisa's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Lilisa's measured trust score of 50.2/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Lilisa is suitable for any particular use.
How Lilisa 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. Lilisa's score of 50.2/100 is below the category average of 62/100.
This suggests that Lilisa 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 Lilisa 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, Lilisa'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 Lilisa's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=lilisa&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 Lilisa are strengthening or weakening over time.
Viktigaste slutsatser
- Lilisa has a measured Nerq Trust Score of 50.2/100 (D) — a composite of independent signals, not a suitability judgment.
- Among uncategorized tools, Lilisa scores below the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — säkerhet, underhåll, dokumentation, regelefterlevnad, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Vanliga frågor
Är Lilisa säker?
Vad är Lilisas förtroendepoäng?
Vilka är säkrare alternativ till Lilisa?
Hur ofta uppdateras Lilisas säkerhetspoäng?
Kan jag använda Lilisa i en reglerad miljö?
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Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.