Безопасен ли Agent Data?
Agent Data — Nerq Trust Score 63.1/100 (Оценка C). На основе анализа 5 измерений доверия, считается в целом безопасным, но с некоторыми опасениями. Последнее обновление: 2026-03-31.
Используйте Agent Data с осторожностью. Agent Data is a software tool с рейтингом доверия Nerq 63.1/100 (C), based on 5 independent data dimensions. Ниже рекомендуемого порога в 70. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-31. Машинночитаемые данные (JSON).
Безопасен ли Agent Data?
ОСТОРОЖНО — Agent Data имеет рейтинг доверия Nerq 63.1/100 (C). Умеренные сигналы доверия, но есть отдельные области, требующие внимания. Подходит для разработки — проверьте сигналы безопасности и обслуживания перед развёртыванием в продакшене.
Каков рейтинг доверия Agent Data?
Agent Data имеет рейтинг доверия Nerq 63.1/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
Каковы основные выводы по безопасности Agent Data?
Agent Data's strongest signal is соответствие at 100/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
Что такое Agent Data и кто его поддерживает?
| Разработчик | VK-Chart |
| Категория | data |
| Источник | https://github.com/VK-Chart/agent-data |
Соответствие нормативам
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Популярные альтернативы в data
What Is Agent Data?
Agent Data is a software tool in the data category: Manages data autonomously.. Nerq Trust Score: 63/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Agent Data's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Agent Data performs in each:
- Безопасность (0/100): Agent Data's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Обслуживание (1/100): Agent Data 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 documentation, usage examples, and contribution guidelines.
- Compliance (100/100): Agent Data is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 63.1/100 (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 Agent Data?
Agent Data 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: Agent Data is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Agent Data's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Agent Data's dependency tree. - Отзыв permissions — Understand what access Agent Data requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Agent Data 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=agent-data - Проверьте license — Confirm that Agent Data'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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Agent Data
When evaluating whether Agent Data is safe, consider these category-specific risks:
Understand how Agent Data processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Agent Data's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Agent Data. Security patches and bug fixes are only effective if you're running the latest version.
If Agent Data 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 Agent Data's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Agent Data in violation of its license can expose your organization to legal liability.
Agent Data and the EU AI Act
Agent Data 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 compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Agent Data Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Agent Data while minimizing risk:
Periodically review how Agent Data is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Agent Data and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Agent Data only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Agent Data's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Agent Data is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Agent Data?
Even promising tools aren't right for every situation. Consider avoiding Agent Data in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Agent Data 63.1/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Agent Data 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. Agent Data's score of 63.1/100 is above the category average of 62/100.
This positions Agent Data favorably among data tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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 Agent Data 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 maintenance patterns change, Agent Data'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 security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Agent Data's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=agent-data&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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Agent Data are strengthening or weakening over time.
Agent Data vs Alternatives
В категории data, Agent Data получает 63.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Agent Data vs firecrawl — Trust Score: 73.8/100
- Agent Data vs MinerU — Trust Score: 84.6/100
- Agent Data vs mindsdb — Trust Score: 77.5/100
Основные выводы
- Agent Data имеет рейтинг доверия 63.1/100 (C) and is not yet Nerq Verified.
- Agent Data shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among data tools, Agent Data 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.
Часто задаваемые вопросы
Безопасен ли Agent Data для использования?
Что такое Agent Data's trust score?
Какие более безопасные альтернативы Agent Data?
How often is Agent Data's safety score updated?
Можно ли использовать Agent Data в регулируемой среде?
Disclaimer: Рейтинги доверия Nerq — это автоматические оценки, основанные на публично доступных сигналах. Они не являются рекомендацией или гарантией. Всегда проводите собственную проверку.