Är Datafetch säker?
Datafetch — Nerq Trust Score 42.5/100 (Betyg E). Poäng baserad på 3 independent trust signals.
Datafetch är en programvara med ett Nerq-förtroendepoäng på 42.5/100 (E), baserat på 3 oberoende datadimensioner. Underhåll: 0/100. Popularitet: 0/100. Data hämtad från flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Senast uppdaterad: n/a. Maskinläsbar data (JSON).
Är Datafetch säker?
Förtroendepoäng i detalj — Datafetch has a Nerq Trust Score of 42.5/100 (E). Measured across 3 independent trust signals.
Vad är Datafetchs förtroendepoäng?
Datafetch har ett Nerq-förtroendepoäng på 42.5/100 med betyget E. Denna poäng baseras på 3 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.
Vilka är de viktigaste säkerhetsresultaten för Datafetch?
Datafetchs starkaste signal är underhåll på 0/100. Inga kända sårbarheter har upptäckts.
Vad är Datafetch och vem underhåller det?
| Utvecklare | https://github.com/undici77/mcpdatafetchserver |
| Kategori | Data |
| Stjärnor | 2 |
| Källa | https://github.com/undici77/mcpdatafetchserver |
Populära alternativ inom data
What Is Datafetch?
Datafetch is a programvara in the data category: Fetches secure web content with various functionalities.. It has 2 GitHub-stjärnor. Nerq Trust Score: 42/100 (E).
Nerq independently analyzes every programvara, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.
How Nerq Assesses Datafetch's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensioner. Here is how Datafetch performs in each:
- Underhåll (0/100): Datafetch 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 dokumentation, usage examples, and contribution guidelines.
- Community (0/100): Community adoption is limited. Baserad på GitHub-stjärnor, forks, download counts, and ecosystem integrations.
The overall Trust Score of 42.5/100 (E) 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 Datafetch?
Datafetch is commonly evaluated by:
- Developers and teams working with data tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Datafetch's measured signals (underhåll 0/100, dokumentation 0/100, community 0/100) 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 Datafetch'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 Datafetch's dependency tree. - Recension permissions — Understand what access Datafetch requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Datafetch 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=DataFetch - Granska license — Confirm that Datafetch'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 Datafetch
When evaluating whether Datafetch is safe, consider these category-specific risks:
Understand how Datafetch processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Datafetch's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.
Regularly check for updates to Datafetch. Säkerhet patches and bug fixes are only effective if you're running the latest version.
If Datafetch 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 Datafetch's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Datafetch in violation of its license can expose your organization to legal liability.
Best Practices for Using Datafetch Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Datafetch while minimizing risk:
Periodically review how Datafetch is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.
Ensure Datafetch and all its dependencies are running the latest stable versions to benefit from säkerhet patches.
Grant Datafetch only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Datafetch's säkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Datafetch is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Oberoende Review of Datafetch
Nerq's signals are one input. In the following situations, evaluate Datafetch'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 Datafetch's measured trust score of 42.5/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Datafetch is suitable for any particular use.
How Datafetch Compares to Industry Standards
Nerq indexes over 6 million programvaras, apps, and packages across dozens of categories. Among data tools, the average Trust Score is 62/100. Datafetch's score of 42.5/100 is below the category average of 62/100.
This suggests that Datafetch trails behind many comparable data 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 Datafetch 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, Datafetch'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 Datafetch's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=DataFetch&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 Datafetch are strengthening or weakening over time.
Datafetch vs Alternativ
In the data category, Datafetch scores 42.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Datafetch vs firecrawl — Trust Score: 64.4/100
- Datafetch vs MinerU — Trust Score: 76.6/100
- Datafetch vs mindsdb — Trust Score: 68.1/100
Viktigaste slutsatser
- Datafetch has a measured Nerq Trust Score of 42.5/100 (E) — a composite of independent signals, not a suitability judgment.
- Among data tools, Datafetch 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 Datafetch säker?
Vad är Datafetchs förtroendepoäng?
Vilka är säkrare alternativ till Datafetch?
Hur ofta uppdateras Datafetchs säkerhetspoäng?
Kan jag använda Datafetch 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.