Apakah Dataanalystagent Aman?

Berhati-hatilah dengan Dataanalystagent. Dataanalystagent is a software tool dengan Skor Kepercayaan Nerq sebesar 49.4/100 (D), based on 3 independent data dimensions. Di bawah ambang batas yang direkomendasikan yaitu 70. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-27. Data yang dapat dibaca mesin (JSON).

Apakah Dataanalystagent Aman?

TIDAK — GUNAKAN DENGAN HATI-HATI — Dataanalystagent memiliki Skor Kepercayaan Nerq sebesar 49.4/100 (D). Memiliki sinyal kepercayaan di bawah rata-rata dengan celah signifikan di keamanan, pemeliharaan, atau dokumentasi. Tidak direkomendasikan untuk penggunaan produksi tanpa tinjauan manual menyeluruh dan langkah keamanan tambahan.

Rincian Skor Kepercayaan

Kepatuhan
100

Temuan Utama

Compliance: 100/100 — covers 52 of 52 jurisdictions

Detail

PembuatKarthikMuraliM
Kategoriuncategorized
Sumberhttps://huggingface.co/spaces/KarthikMuraliM/DataAnalystAgent
Protocolshuggingface_hub

Kepatuhan Regulasi

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

What Is Dataanalystagent?

Dataanalystagent is a software tool in the uncategorized category available on huggingface_space_full. Nerq Trust Score: 49/100 (D).

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 Dataanalystagent's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Dataanalystagent performs in each:

The overall Trust Score of 49.4/100 (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 Dataanalystagent?

Dataanalystagent is designed for:

Risk guidance: We recommend caution with Dataanalystagent. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.

How to Verify Dataanalystagent's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Dataanalystagent's dependency tree.
  3. Ulasan permissions — Understand what access Dataanalystagent requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Dataanalystagent 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=DataAnalystAgent
  6. Tinjau license — Confirm that Dataanalystagent'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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Dataanalystagent

When evaluating whether Dataanalystagent is safe, consider these category-specific risks:

Data handling

Understand how Dataanalystagent processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Dataanalystagent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Dataanalystagent. Security patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Dataanalystagent 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 compliance

Verify that Dataanalystagent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Dataanalystagent in violation of its license can expose your organization to legal liability.

Best Practices for Using Dataanalystagent Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Dataanalystagent while minimizing risk:

Conduct regular audits

Periodically review how Dataanalystagent is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Dataanalystagent and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

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

Monitor for security advisories

Subscribe to Dataanalystagent's security 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 Dataanalystagent is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Dataanalystagent?

Even promising tools aren't right for every situation. Consider avoiding Dataanalystagent in these scenarios:

Skor kepercayaan

For each scenario, evaluate whether Dataanalystagent sebesar 49.4/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Dataanalystagent 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. Dataanalystagent's score of 49.4/100 is below the category average of 62/100.

This suggests that Dataanalystagent trails behind many comparable uncategorized tools. Organizations with strict security 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 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 Dataanalystagent 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, Dataanalystagent'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 Dataanalystagent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=DataAnalystAgent&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 Dataanalystagent are strengthening or weakening over time.

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Dataanalystagent aman digunakan?
Berhati-hatilah. DataAnalystAgent memiliki Skor Kepercayaan Nerq sebesar 49.4/100 (D). Sinyal terkuat: kepatuhan (100/100). Skor berdasarkan beberapa dimensi kepercayaan.
Berapa skor kepercayaan Dataanalystagent?
DataAnalystAgent: 49.4/100 (D). Skor berdasarkan: beberapa dimensi kepercayaan. Compliance: 100/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=DataAnalystAgent
Apa alternatif yang lebih aman dari Dataanalystagent?
Dalam kategori uncategorized, more software tools are being analyzed — kunjungi kembali segera. DataAnalystAgent mendapat skor 49.4/100.
How often is Dataanalystagent's safety score updated?
Nerq continuously monitors Dataanalystagent and updates its trust score as new data becomes available. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 49.4/100 (D), last verified 2026-03-27. API: GET nerq.ai/v1/preflight?target=DataAnalystAgent
Bisakah saya menggunakan Dataanalystagent di lingkungan teregulasi?
Dataanalystagent 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: Skor kepercayaan Nerq adalah penilaian otomatis berdasarkan sinyal yang tersedia secara publik. Ini bukan rekomendasi atau jaminan. Selalu lakukan verifikasi mandiri Anda sendiri.