Apakah Value Extraction Aman?
Value Extraction — Nerq Trust Score 37.9/100 (Nilai E). Berdasarkan analisis 5 dimensi kepercayaan, dianggap memiliki risiko keamanan yang signifikan. Terakhir diperbarui: 2026-04-02.
Berhati-hatilah dengan Value Extraction. Value Extraction is a software tool dengan Skor Kepercayaan Nerq sebesar 37.9/100 (E). Di bawah ambang batas yang direkomendasikan yaitu 70. Data bersumber dari multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Terakhir diperbarui: 2026-04-02. Data yang dapat dibaca mesin (JSON).
Apakah Value Extraction Aman?
TIDAK — GUNAKAN DENGAN HATI-HATI — Value Extraction memiliki Skor Kepercayaan Nerq sebesar 37.9/100 (E). 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.
Berapa skor kepercayaan Value Extraction?
Value Extraction memiliki Skor Kepercayaan Nerq 37.9/100 dengan nilai E. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.
Apa temuan keamanan utama untuk Value Extraction?
Sinyal terkuat Value Extraction adalah kepercayaan keseluruhan pada 37.9/100. Tidak ada kerentanan yang diketahui terdeteksi. Belum mencapai ambang verifikasi Nerq 70+.
Apa itu Value Extraction dan siapa yang mengelolanya?
| Pembuat | 0x0e62b4fe5aa3800f6098f33bab5f28077c62caba |
| Kategori | uncategorized |
| Sumber | https://8004scan.io/agents/value-extraction |
What Is Value Extraction?
Value Extraction is a software tool in the uncategorized category: Crypto market intelligence agent. Real-time BTC/ETH/macro analysis, on-chain whale tracking, CEX flow monitoring. AI-powered. Twitter: @value_extract. Nerq Trust Score: 38/100 (E).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including keamanan vulnerabilities, pemeliharaan activity, license kepatuhan, and adopsi komunitas.
How Nerq Assesses Value Extraction's Safety
Nerq evaluates every software tool across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core dimensi: Keamanan (known CVEs, dependency vulnerabilities, keamanan policies), Pemeliharaan (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 jurisdictions), and Community (stars, forks, downloads, ecosystem integrations).
Value Extraction receives an overall Trust Score of 37.9/100 (E), which Nerq considers low. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=Value Extraction
Each dimension is weighted according to its importance for the tool's category. For example, Keamanan and Pemeliharaan carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Value Extraction's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five dimensi, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).
Who Should Use Value Extraction?
Value Extraction is designed for:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Value Extraction. The low trust score suggests potential risks in keamanan, pemeliharaan, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Value Extraction's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Tinjau repository keamanan policy, open issues, and recent commits for signs of active pemeliharaan.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Value Extraction's dependency tree. - Ulasan permissions — Understand what access Value Extraction requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Value Extraction 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=Value Extraction - Tinjau license — Confirm that Value Extraction'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 keamanan concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Value Extraction
When evaluating whether Value Extraction is safe, consider these category-specific risks:
Understand how Value Extraction processes, stores, and transmits your data. Tinjau tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Value Extraction's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher keamanan risk.
Regularly check for updates to Value Extraction. Keamanan patches and bug fixes are only effective if you're running the latest version.
If Value Extraction 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 Value Extraction's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Value Extraction in violation of its license can expose your organization to legal liability.
Best Practices for Using Value Extraction Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Value Extraction while minimizing risk:
Periodically review how Value Extraction is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.
Ensure Value Extraction and all its dependencies are running the latest stable versions to benefit from keamanan patches.
Grant Value Extraction only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Value Extraction's keamanan advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Value Extraction is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Value Extraction?
Even promising tools aren't right for every situation. Consider avoiding Value Extraction in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional kepatuhan review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Value Extraction sebesar 37.9/100 meets your organization's risk tolerance. We recommend running a manual keamanan assessment alongside the automated Nerq score.
How Value Extraction 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. Value Extraction's score of 37.9/100 is below the category average of 62/100.
This suggests that Value Extraction trails behind many comparable uncategorized tools. Organizations with strict keamanan 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 sedang 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 Value Extraction 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 pemeliharaan patterns change, Value Extraction'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 keamanan and quality. Conversely, a downward trend may signal reduced pemeliharaan, growing technical debt, or unresolved vulnerabilities. To track Value Extraction's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Value Extraction&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 — keamanan, pemeliharaan, dokumentasi, kepatuhan, and community — has evolved independently, providing granular visibility into which aspects of Value Extraction are strengthening or weakening over time.
Kesimpulan Utama
- Value Extraction memiliki Skor Kepercayaan sebesar 37.9/100 (E) and is not yet Nerq Verified.
- Value Extraction has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among uncategorized tools, Value Extraction scores below the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Pertanyaan yang Sering Diajukan
Apakah Value Extraction aman digunakan?
Berapa skor kepercayaan Value Extraction?
Apa alternatif yang lebih aman dari Value Extraction?
How often is Value Extraction's safety score updated?
Bisakah saya menggunakan Value Extraction di lingkungan teregulasi?
Disclaimer: Skor kepercayaan Nerq adalah penilaian otomatis berdasarkan sinyal yang tersedia secara publik. Ini bukan rekomendasi atau jaminan. Selalu lakukan verifikasi mandiri Anda sendiri.