Er Data Analyst Deepagent trygt?
Data Analyst Deepagent — Nerq Trust Score 67.7/100 (Karakter C). Basert på analyse av 5 tillidsdimensjoner vurderes det som generelt trygt men med visse bekymringer. Sist oppdatert: 2026-04-08.
Bruk Data Analyst Deepagent med forsiktighet. Data Analyst Deepagent er en software tool har en Nerq-tillitspoeng på 67.7/100 (C), based on 5 uavhengige datadimensjoner. Under Nerqs verifiserte terskel Sikkerhet: 0/100. Vedlikehold: 1/100. Popularitet: 0/100. Data hentet fra flere offentlige kilder inkludert pakkeregistre, GitHub, NVD, OSV.dev og OpenSSF Scorecard. Sist oppdatert: 2026-04-08. Maskinlesbare data (JSON).
Er Data Analyst Deepagent trygt?
CAUTION — Data Analyst Deepagent har en Nerq-tillitspoeng på 67.7/100 (C). 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 Data Analyst Deepagent?
Data Analyst Deepagent har en Nerq-tillitspoeng på 67.7/100 med karakteren C. Denne poengsummen er basert på 5 uavhengig målte dimensjoner, inkludert sikkerhet, vedlikehold og samfunnsadopsjon.
Hva er de viktigste sikkerhetsfunnene for Data Analyst Deepagent?
Data Analyst Deepagents 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 Data Analyst Deepagent og hvem vedlikeholder det?
| Utvikler | BoualamHamza |
| Kategori | Data |
| Kilde | https://github.com/BoualamHamza/Data-analyst-DeepAgent |
| Frameworks | openai · anthropic |
| Protocols | rest |
Regulatorisk samsvar
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Populære alternativer i data
What Is Data Analyst Deepagent?
Data Analyst Deepagent is a software tool in the data category: AI-powered data analyst agent for querying databases, generating visualizations, and detecting anomalies.. Nerq Trust Score: 68/100 (C).
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 Data Analyst Deepagent's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensjoner. Here is how Data Analyst Deepagent performs in each:
- Sikkerhet (0/100): Data Analyst Deepagent's sikkerhet posture is poor. This score factors in known CVEs, dependency vulnerabilities, sikkerhet policy presence, and code signing practices.
- Vedlikehold (1/100): Data Analyst Deepagent 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 dokumentasjon, usage examples, and contribution guidelines.
- Compliance (100/100): Data Analyst Deepagent is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Basert på GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 67.7/100 (C) 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 Data Analyst Deepagent?
Data Analyst Deepagent is designed for:
- Developers and teams working with data tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Data Analyst Deepagent 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 Data Analyst Deepagent'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's 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 Data Analyst Deepagent's dependency tree. - Anmeldelse permissions — Understand what access Data Analyst Deepagent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Data Analyst Deepagent 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=Data-analyst-DeepAgent - Gjennomgå license — Confirm that Data Analyst Deepagent'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 Data Analyst Deepagent
When evaluating whether Data Analyst Deepagent is safe, consider these category-specific risks:
Understand how Data Analyst Deepagent processes, stores, and transmits your data. Gjennomgå tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Data Analyst Deepagent's dependency tree for kjente sårbarheter. Tools with outdated or unmaintained dependencies pose a higher sikkerhet risk.
Regularly check for updates to Data Analyst Deepagent. Sikkerhet patches and bug fixes are only effective if you're running the latest version.
If Data Analyst Deepagent 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 Data Analyst Deepagent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Data Analyst Deepagent in violation of its license can expose your organization to legal liability.
Data Analyst Deepagent and the EU AI Act
Data Analyst Deepagent 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 samsvar assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal samsvar.
Best Practices for Using Data Analyst Deepagent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Data Analyst Deepagent while minimizing risk:
Periodically review how Data Analyst Deepagent is used in your workflow. Check for unexpected behavior, permissions drift, and samsvar with your sikkerhet policies.
Ensure Data Analyst Deepagent and all its dependencies are running the latest stable versions to benefit from sikkerhet patches.
Grant Data Analyst Deepagent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Data Analyst Deepagent's sikkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Data Analyst Deepagent is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Data Analyst Deepagent?
Even promising tools aren't right for every situation. Consider avoiding Data Analyst Deepagent 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 Data Analyst Deepagent's trust score of 67.7/100 meets your organization's risk tolerance. We recommend running a manual sikkerhet assessment alongside the automated Nerq score.
How Data Analyst Deepagent Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among data tools, the average Trust Score is 62/100. Data Analyst Deepagent's score of 67.7/100 is above the category average of 62/100.
This positions Data Analyst Deepagent favorably among data tools. While it outperforms the average, there is still room for improvement in certain trust dimensjoner.
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 Data Analyst Deepagent 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, Data Analyst Deepagent'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 Data Analyst Deepagent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Data-analyst-DeepAgent&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 Data Analyst Deepagent are strengthening or weakening over time.
Data Analyst Deepagent vs Alternativer
In the data category, Data Analyst Deepagent scores 67.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Data Analyst Deepagent vs firecrawl — Trust Score: 73.8/100
- Data Analyst Deepagent vs MinerU — Trust Score: 84.6/100
- Data Analyst Deepagent vs mindsdb — Trust Score: 77.5/100
Viktigste punkter
- Data Analyst Deepagent has a Trust Score of 67.7/100 (C) and is not yet Nerq Verified.
- Data Analyst Deepagent shows moderat trust signals. Conduct thorough due diligence before deploying to production environments.
- Among data tools, Data Analyst Deepagent 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.
Ofte stilte spørsmål
Er Data Analyst Deepagent trygt?
Hva er tillitspoengene til Data Analyst Deepagent?
Hva er tryggere alternativer til Data Analyst Deepagent?
Hvor ofte oppdateres Data Analyst Deepagents sikkerhetspoeng?
Kan jeg bruke Data Analyst Deepagent i et regulert miljø?
Se også
Disclaimer: Nerqs tillitspoeng er automatiserte vurderinger basert på offentlig tilgjengelige signaler. De utgjør ikke anbefalinger eller garantier. Utfør alltid din egen verifisering.