Безопасен ли Data Analyst Deepagent?

Data Analyst Deepagent — Nerq Trust Score 67.7/100 (Оценка C). На основе анализа 5 измерений доверия, считается в целом безопасным, но с некоторыми опасениями. Последнее обновление: 2026-04-04.

Используйте Data Analyst Deepagent с осторожностью. Data Analyst Deepagent — это software tool с рейтингом доверия Nerq 67.7/100 (C), based on 5 независимых показателей данных. Ниже рекомендуемого порога в 70. Безопасность: 0/100. Обслуживание: 1/100. Популярность: 0/100. Данные из multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Последнее обновление: 2026-04-04. Машинночитаемые данные (JSON).

Безопасен ли Data Analyst Deepagent?

ОСТОРОЖНО — Data Analyst Deepagent имеет рейтинг доверия Nerq 67.7/100 (C). Умеренные сигналы доверия, но есть отдельные области, требующие внимания. Подходит для разработки — проверьте сигналы безопасности и обслуживания перед развёртыванием в продакшене.

Анализ безопасности → Отчёт о конфиденциальности {name} →

Каков рейтинг доверия Data Analyst Deepagent?

Data Analyst Deepagent имеет Nerq Trust Score 67.7/100 с оценкой C. Этот балл основан на 5 независимо измеренных параметрах, включая безопасность, обслуживание и принятие сообществом.

Безопасность
0
Соответствие
100
Обслуживание
1
Документация
1
Популярность
0

Каковы основные выводы по безопасности Data Analyst Deepagent?

Самый сильный сигнал Data Analyst Deepagent — соответствие на уровне 100/100. Известных уязвимостей не обнаружено. It has not yet reached the Nerq Verified threshold of 70+.

Рейтинг безопасности: 0/100 (weak)
Обслуживание: 1/100 — низкая активность поддержки
Compliance: 100/100 — covers 52 of 52 jurisdictions
Documentation: 1/100 — ограниченная документация
Популярность: 0/100 — принятие сообществом

Что такое Data Analyst Deepagent и кто его поддерживает?

РазработчикBoualamHamza
Категорияdata
Источникhttps://github.com/BoualamHamza/Data-analyst-DeepAgent
Frameworksopenai · anthropic
Protocolsrest

Соответствие нормативам

EU AI Act Risk ClassMINIMAL
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdictions

Популярные альтернативы в data

firecrawl/firecrawl
73.8/100 · B
github
MinerU
84.6/100 · A
github
mindsdb/mindsdb
77.5/100 · B
github
PostHog
51.9/100 · D
pulsemcp
Graphiti
51.9/100 · D
pulsemcp

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 безопасность vulnerabilities, обслуживание activity, license соответствие, and принятие сообществом.

How Nerq Assesses Data Analyst Deepagent's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five показателей. Here is how Data Analyst Deepagent performs in each:

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:

Risk guidance: Data Analyst Deepagent is suitable for development and testing environments. Before production deployment, conduct a thorough review of its безопасность 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:

  1. Check the source code — Проверьте repository's безопасность policy, open issues, and recent commits for signs of active обслуживание.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Data Analyst Deepagent's dependency tree.
  3. Отзыв permissions — Understand what access Data Analyst Deepagent requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Data Analyst Deepagent in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=Data-analyst-DeepAgent
  6. Проверьте 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.
  7. 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 безопасность 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:

Data handling

Understand how Data Analyst Deepagent processes, stores, and transmits your data. Проверьте tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency безопасность

Check Data Analyst Deepagent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher безопасность risk.

Update frequency

Regularly check for updates to Data Analyst Deepagent. Безопасность patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

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.

License and IP соответствие

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 соответствие assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal соответствие.

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:

Conduct regular audits

Periodically review how Data Analyst Deepagent is used in your workflow. Check for unexpected behavior, permissions drift, and соответствие with your безопасность policies.

Keep dependencies updated

Ensure Data Analyst Deepagent and all its dependencies are running the latest stable versions to benefit from безопасность patches.

Follow least privilege

Grant Data Analyst Deepagent only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for безопасность advisories

Subscribe to Data Analyst Deepagent's безопасность advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

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:

рейтинг доверия

For each scenario, evaluate whether Data Analyst Deepagent 67.7/100 meets your organization's risk tolerance. We recommend running a manual безопасность 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 показателей.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks умеренный 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 обслуживание 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 безопасность and quality. Conversely, a downward trend may signal reduced обслуживание, 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 — безопасность, обслуживание, документация, соответствие, 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 Альтернативы

В категории data, Data Analyst Deepagent получает 67.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Основные выводы

Часто задаваемые вопросы

Безопасен ли Data Analyst Deepagent для использования?
Используйте с осторожностью. Data-analyst-DeepAgent имеет рейтинг доверия Nerq 67.7/100 (C). Самый сильный сигнал: соответствие (100/100). Рейтинг основан на безопасность (0/100), обслуживание (1/100), популярность (0/100), документация (1/100).
Что такое Data Analyst Deepagent's trust score?
Data-analyst-DeepAgent: 67.7/100 (C). Рейтинг основан на: безопасность (0/100), обслуживание (1/100), популярность (0/100), документация (1/100). Compliance: 100/100. Рейтинги обновляются по мере поступления новых данных. API: GET nerq.ai/v1/preflight?target=Data-analyst-DeepAgent
Какие более безопасные альтернативы Data Analyst Deepagent?
В категории data, альтернативы с более высоким рейтингом: firecrawl/firecrawl (74/100), MinerU (85/100), mindsdb/mindsdb (78/100). Data-analyst-DeepAgent получает 67.7/100.
How often is Data Analyst Deepagent's safety score updated?
Nerq continuously monitors Data Analyst Deepagent and updates its trust score as new data becomes available. Данные из multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 67.7/100 (C), last верифицировано 2026-04-04. API: GET nerq.ai/v1/preflight?target=Data-analyst-DeepAgent
Можно ли использовать Data Analyst Deepagent в регулируемой среде?
Data Analyst Deepagent has not reached the Nerq Verified threshold of 70. Additional due diligence is recommended for regulated environments.
API: /v1/preflight Trust Badge API Docs

Disclaimer: Рейтинги доверия Nerq — это автоматические оценки, основанные на публично доступных сигналах. Они не являются рекомендацией или гарантией. Всегда проводите собственную проверку.

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