Apakah Sql Llm Agent Aman?

Sql Llm Agent — Nerq Trust Score 70.5/100 (Nilai B). Berdasarkan analisis 5 dimensi kepercayaan, dianggap umumnya aman tetapi memiliki beberapa kekhawatiran. Terakhir diperbarui: 2026-04-01.

Ya, Sql Llm Agent aman digunakan. Sql Llm Agent is a software tool dengan Skor Kepercayaan Nerq sebesar 70.5/100 (B), based on 5 independent data dimensions. It is recommended for use. 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: 2026-04-01. Data yang dapat dibaca mesin (JSON).

Apakah Sql Llm Agent Aman?

YA — Sql Llm Agent memiliki Skor Kepercayaan Nerq sebesar 70.5/100 (B). Memenuhi ambang batas kepercayaan Nerq dengan sinyal kuat di keamanan, pemeliharaan, dan adopsi komunitas. Recommended for use — tinjau laporan lengkap di bawah untuk pertimbangan spesifik.

Analisis Keamanan → Laporan Privasi {name} →

Berapa skor kepercayaan Sql Llm Agent?

Sql Llm Agent memiliki Skor Kepercayaan Nerq 70.5/100 dengan nilai B. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.

Keamanan
0
Kepatuhan
100
Pemeliharaan
1
Dokumentasi
1
Popularitas
0

Apa temuan keamanan utama untuk Sql Llm Agent?

Sinyal terkuat Sql Llm Agent adalah kepatuhan pada 100/100. Tidak ada kerentanan yang diketahui terdeteksi. Memenuhi ambang verifikasi Nerq 70+.

Skor keamanan: 0/100 (weak)
Maintenance: 1/100 — low maintenance activity
Compliance: 100/100 — covers 52 of 52 jurisdictions
Documentation: 1/100 — limited documentation
Popularity: 0/100 — community adoption

Apa itu Sql Llm Agent dan siapa yang mengelolanya?

Pembuatlunatictiol
Kategoricoding
Sumberhttps://github.com/lunatictiol/sql-llm-agent
Frameworkslangchain · ollama · huggingface
Protocolsrest

Kepatuhan Regulasi

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

Alternatif Populer di coding

Significant-Gravitas/AutoGPT
74.7/100 · B
github
ollama/ollama
73.8/100 · B
github
langchain-ai/langchain
86.4/100 · A
github
x1xhlol/system-prompts-and-models-of-ai-tools
73.8/100 · B
github
anomalyco/opencode
87.9/100 · A
github

What Is Sql Llm Agent?

Sql Llm Agent is a software tool in the coding category: A schema-grounded SQL generation system for converting natural language questions into valid PostgreSQL SELECT queries.. Nerq Trust Score: 70/100 (B).

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 Sql Llm Agent's Safety

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

The overall Trust Score of 70.5/100 (B) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.

Who Should Use Sql Llm Agent?

Sql Llm Agent is designed for:

Risk guidance: Sql Llm Agent meets the minimum threshold for production use, but we recommend monitoring for security advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

How to Verify Sql Llm Agent'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's 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 Sql Llm Agent's dependency tree.
  3. Ulasan permissions — Understand what access Sql Llm Agent requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Sql Llm Agent 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=sql-llm-agent
  6. Tinjau license — Confirm that Sql Llm Agent'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 Sql Llm Agent

When evaluating whether Sql Llm Agent is safe, consider these category-specific risks:

Data handling

Understand how Sql Llm Agent 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 Sql Llm Agent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

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

Third-party integrations

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

Sql Llm Agent and the EU AI Act

Sql Llm Agent 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 Sql Llm Agent Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

Subscribe to Sql Llm Agent'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 Sql Llm Agent is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Sql Llm Agent?

Even well-trusted tools aren't right for every situation. Consider avoiding Sql Llm Agent in these scenarios:

Skor kepercayaan

For each scenario, evaluate whether Sql Llm Agent sebesar 70.5/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Sql Llm Agent Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Sql Llm Agent's score of 70.5/100 is above the category average of 62/100.

This positions Sql Llm Agent favorably among coding 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 Sql Llm Agent 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, Sql Llm Agent'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 Sql Llm Agent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=sql-llm-agent&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 Sql Llm Agent are strengthening or weakening over time.

Sql Llm Agent vs Alternatives

Dalam kategori coding, Sql Llm Agent mendapat skor 70.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Sql Llm Agent aman digunakan?
Ya, aman digunakan. sql-llm-agent memiliki Skor Kepercayaan Nerq sebesar 70.5/100 (B). Sinyal terkuat: kepatuhan (100/100). Skor berdasarkan security (0/100), maintenance (1/100), popularity (0/100), documentation (1/100).
Berapa skor kepercayaan Sql Llm Agent?
sql-llm-agent: 70.5/100 (B). Skor berdasarkan: security (0/100), maintenance (1/100), popularity (0/100), documentation (1/100). Compliance: 100/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=sql-llm-agent
Apa alternatif yang lebih aman dari Sql Llm Agent?
Dalam kategori coding, alternatif berperingkat lebih tinggi termasuk Significant-Gravitas/AutoGPT (75/100), ollama/ollama (74/100), langchain-ai/langchain (86/100). sql-llm-agent mendapat skor 70.5/100.
How often is Sql Llm Agent's safety score updated?
Nerq continuously monitors Sql Llm Agent 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: 70.5/100 (B), last verified 2026-04-01. API: GET nerq.ai/v1/preflight?target=sql-llm-agent
Bisakah saya menggunakan Sql Llm Agent di lingkungan teregulasi?
Yes — Sql Llm Agent meets the Nerq Verified threshold (70+). Combine this with your internal security review for regulated deployments.
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.

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