Apakah Ralphy Aman?

Ralphy — Nerq Trust Score 60.9/100 (Nilai C). Berdasarkan analisis 5 dimensi kepercayaan, dianggap umumnya aman tetapi memiliki beberapa kekhawatiran. Terakhir diperbarui: 2026-04-23.

Gunakan Ralphy dengan hati-hati. Ralphy adalah software tool dengan Skor Kepercayaan Nerq sebesar 60.9/100 (C), based on 5 dimensi data independen. Di bawah ambang batas terverifikasi Nerq Keamanan: 0/100. Pemeliharaan: 1/100. Popularitas: 0/100. Data bersumber dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Terakhir diperbarui: 2026-04-23. Data yang dapat dibaca mesin (JSON).

Apakah Ralphy Aman?

CAUTION — Ralphy has a Nerq Trust Score of 60.9/100 (C). Memiliki sinyal kepercayaan sedang tetapi menunjukkan beberapa area perhatian that warrant attention. Suitable for development use — review keamanan and pemeliharaan signals before production deployment.

Analisis Keamanan → Laporan Privasi Ralphy →

Berapa skor kepercayaan Ralphy?

Ralphy memiliki Skor Kepercayaan Nerq 60.9/100 dengan nilai C. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.

Keamanan
0
Kepatuhan
87
Pemeliharaan
1
Dokumentasi
1
Popularitas
0

Apa temuan keamanan utama untuk Ralphy?

Sinyal terkuat Ralphy adalah kepatuhan pada 87/100. Tidak ada kerentanan yang diketahui terdeteksi. Belum mencapai ambang verifikasi Nerq 70+.

Skor keamanan: 0/100 (lemah)
Pemeliharaan: 1/100 — aktivitas pemeliharaan rendah
Kepatuhan: 87/100 — covers 45 of 52 jurisdictions
Dokumentasi: 1/100 — dokumentasi terbatas
Popularitas: 0/100 — 1 bintang di github

Apa itu Ralphy dan siapa yang mengelolanya?

PembuatCaptnBook4Git
KategoriCoding
Bintang1
Sumberhttps://github.com/CaptnBook4Git/ralphy
Frameworksopenai · anthropic
Protocolsrest

Kepatuhan Regulasi

EU AI Act Risk ClassMINIMAL
Compliance Score87/100
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
71.3/100 · B
github
x1xhlol/system-prompts-and-models-of-ai-tools
73.8/100 · B
github
anomalyco/opencode
64.1/100 · C+
github

What Is Ralphy?

Ralphy is a software tool in the coding category: Ralphy is an autonomous AI coding agent that continuously plans, codes, tests, documents, and commits using Claude Code, OpenCode & CCS.. It has 1 GitHub stars. Nerq Trust Score: 61/100 (C).

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 Ralphy's Safety

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

The overall Trust Score of 60.9/100 (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 Ralphy?

Ralphy is designed for:

Risk guidance: Ralphy is suitable for development and testing environments. Before production deployment, conduct a thorough review of its keamanan posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Ralphy's Safety Yourself

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

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

Common Safety Concerns with Ralphy

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

Data handling

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

Dependency keamanan

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

Update frequency

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

Third-party integrations

If Ralphy 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 kepatuhan

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

Ralphy and the EU AI Act

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

Best Practices for Using Ralphy Safely

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

Conduct regular audits

Periodically review how Ralphy is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.

Keep dependencies updated

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

Follow least privilege

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

Monitor for keamanan advisories

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

When Should You Avoid Ralphy?

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

For each scenario, evaluate whether Ralphy's trust score of 60.9/100 meets your organization's risk tolerance. We recommend running a manual keamanan assessment alongside the automated Nerq score.

How Ralphy 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. Ralphy's score of 60.9/100 is near the category average of 62/100.

This places Ralphy in line with the typical coding tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

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 Ralphy 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, Ralphy'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 Ralphy's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=ralphy&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 Ralphy are strengthening or weakening over time.

Ralphy vs Alternatif

In the coding category, Ralphy scores 60.9/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Analisis Skor Terperinci

DimensionScore
Keamanan0/100
Pemeliharaan1/100
Popularitas0/100

Berdasarkan 3 dimensi. Data from berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard.

Data apa yang dikumpulkan Ralphy?

Privasi assessment for Ralphy is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.

Apakah Ralphy aman?

Keamanan score: 0/100. Review keamanan practices and consider alternatives with higher keamanan scores for sensitive use cases.

Nerq memantau entitas ini terhadap NVD, OSV.dev, dan database kerentanan khusus registry untuk penilaian keamanan berkelanjutan.

Analisis lengkap: Laporan Keamanan Ralphy

Cara kami menghitung skor ini

Ralphy's trust score of 60.9/100 (C) dihitung dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Skor ini mencerminkan 3 dimensi independen: keamanan (0/100), pemeliharaan (1/100), popularitas (0/100). Setiap dimensi diberi bobot yang sama untuk menghasilkan skor kepercayaan komposit.

Nerq menganalisis lebih dari 7,5 juta entitas di 26 registry menggunakan metodologi yang sama, memungkinkan perbandingan langsung antar entitas. Skor diperbarui secara berkelanjutan saat data baru tersedia.

Halaman ini terakhir ditinjau pada April 23, 2026. Versi data: 1.0.

Dokumentasi metodologi lengkap · Data yang dapat dibaca mesin (API JSON)

Pertanyaan yang Sering Diajukan

Apakah Ralphy Aman?
Gunakan dengan hati-hati. ralphy dengan Skor Kepercayaan Nerq sebesar 60.9/100 (C). Sinyal terkuat: kepatuhan (87/100). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100).
Berapa skor kepercayaan Ralphy?
ralphy: 60.9/100 (C). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100). Compliance: 87/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=ralphy
Apa alternatif yang lebih aman dari Ralphy?
Dalam kategori Coding, higher-rated alternatives include Significant-Gravitas/AutoGPT (75/100), ollama/ollama (74/100), langchain-ai/langchain (71/100). ralphy scores 60.9/100.
Seberapa sering skor keamanan Ralphy diperbarui?
Nerq continuously monitors Ralphy and updates its trust score as new data becomes available. Current: 60.9/100 (C), last terverifikasi 2026-04-23. API: GET nerq.ai/v1/preflight?target=ralphy
Bisakah saya menggunakan Ralphy di lingkungan yang diatur?
Ralphy belum mencapai ambang verifikasi Nerq 70. Tinjauan tambahan disarankan.
API: /v1/preflight Trust Badge API Docs

Lihat juga

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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