Er Dataview trygt?
Dataview — Nerq Trust Score 50.2/100 (Karakter D). Basert på analyse av 1 tillidsdimensjoner vurderes det som har merkbare sikkerhetsproblemer. Sist oppdatert: 2026-04-23.
Bruk Dataview med forsiktighet. Dataview er en software tool har en Nerq-tillitspoeng på 50.2/100 (D), based on 3 uavhengige datadimensjoner. Under Nerqs verifiserte terskel Data hentet fra flere offentlige kilder inkludert pakkeregistre, GitHub, NVD, OSV.dev og OpenSSF Scorecard. Sist oppdatert: 2026-04-23. Maskinlesbare data (JSON).
Er Dataview trygt?
CAUTION — Dataview har en Nerq-tillitspoeng på 50.2/100 (D). Har moderat tillitssignaler, men viser noen bekymringsområder that warrant attention. Suitable for development use — review sikkerhet and vedlikehold signals before production deployment.
Hva er tillitspoengene til Dataview?
Dataview har en Nerq-tillitspoeng på 50.2/100 med karakteren D. Denne poengsummen er basert på 1 uavhengig målte dimensjoner, inkludert sikkerhet, vedlikehold og samfunnsadopsjon.
Hva er de viktigste sikkerhetsfunnene for Dataview?
Dataviews sterkeste signal er samsvar på 100/100. Ingen kjente sårbarheter er funnet. It has not yet reached the Nerq Verified threshold of 70+.
Hva er Dataview og hvem vedlikeholder det?
| Utvikler | jimmydao121 |
| Kategori | Uncategorized |
| Kilde | https://huggingface.co/datasets/jimmydao121/dataview |
| Protocols | huggingface_hub |
Regulatorisk samsvar
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
What Is Dataview?
Dataview is a software tool in the uncategorized category available on huggingface_dataset_full. Nerq Trust Score: 50/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including sikkerhet vulnerabilities, vedlikehold activity, license samsvar, and fellesskapsadopsjon.
How Nerq Assesses Dataview's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensjoner. Here is how Dataview performs in each:
- Compliance (100/100): Dataview is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
The overall Trust Score of 50.2/100 (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 Dataview?
Dataview is designed for:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Dataview is suitable for development and testing environments. Before production deployment, conduct a thorough review of its sikkerhet posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Dataview's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Gjennomgå repository sikkerhet policy, open issues, and recent commits for signs of active vedlikehold.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for kjente sårbarheter in Dataview's dependency tree. - Anmeldelse permissions — Understand what access Dataview requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Dataview 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=dataview - Gjennomgå license — Confirm that Dataview'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 sikkerhet concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Dataview
When evaluating whether Dataview is safe, consider these category-specific risks:
Understand how Dataview processes, stores, and transmits your data. Gjennomgå tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Dataview's dependency tree for kjente sårbarheter. Tools with outdated or unmaintained dependencies pose a higher sikkerhet risk.
Regularly check for updates to Dataview. Sikkerhet patches and bug fixes are only effective if you're running the latest version.
If Dataview 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 Dataview's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Dataview in violation of its license can expose your organization to legal liability.
Best Practices for Using Dataview Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Dataview while minimizing risk:
Periodically review how Dataview is used in your workflow. Check for unexpected behavior, permissions drift, and samsvar with your sikkerhet policies.
Ensure Dataview and all its dependencies are running the latest stable versions to benefit from sikkerhet patches.
Grant Dataview only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Dataview's sikkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Dataview is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Dataview?
Even promising tools aren't right for every situation. Consider avoiding Dataview in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional samsvar review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Dataview's trust score of 50.2/100 meets your organization's risk tolerance. We recommend running a manual sikkerhet assessment alongside the automated Nerq score.
How Dataview Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Dataview's score of 50.2/100 is below the category average of 62/100.
This suggests that Dataview trails behind many comparable uncategorized tools. Organizations with strict sikkerhet 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 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 Dataview 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 vedlikehold patterns change, Dataview'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 sikkerhet and quality. Conversely, a downward trend may signal reduced vedlikehold, growing technical debt, or unresolved vulnerabilities. To track Dataview's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=dataview&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 — sikkerhet, vedlikehold, dokumentasjon, samsvar, and community — has evolved independently, providing granular visibility into which aspects of Dataview are strengthening or weakening over time.
Viktigste punkter
- Dataview has a Trust Score of 50.2/100 (D) and is not yet Nerq Verified.
- Dataview shows moderat trust signals. Conduct thorough due diligence before deploying to production environments.
- Among uncategorized tools, Dataview scores below 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.
Hvilke data samler Dataview inn?
Personvern assessment for Dataview is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Er Dataview sikkert?
Sikkerhet score: under vurdering. Review sikkerhet practices and consider alternatives with higher sikkerhet scores for sensitive use cases.
Nerq overvåker denne enheten mot NVD, OSV.dev og registerspesifikke sårbarhetsdatabaser for løpende sikkerhetsvurdering.
Full analyse: Dataview sikkerhetsrapport
Slik beregnet vi denne poengsummen
Dataview's trust score of 50.2/100 (D) beregnes fra flere offentlige kilder inkludert pakkeregistre, GitHub, NVD, OSV.dev og OpenSSF Scorecard. Poengsummen gjenspeiler 0 uavhengige dimensjoner: . Hver dimensjon vektes likt for å produsere det samlede tillitspoenget.
Nerq analyserer over 7,5 millioner enheter i 26 registre med samme metodikk, noe som muliggjør direkte sammenligning mellom enheter. Poeng oppdateres fortløpende etter hvert som nye data blir tilgjengelige.
Denne siden ble sist gjennomgått den April 23, 2026. Dataversjon: 1.0.
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Se også
Disclaimer: Nerqs tillitspoeng er automatiserte vurderinger basert på offentlig tilgjengelige signaler. De utgjør ikke anbefalinger eller garantier. Utfør alltid din egen verifisering.