Openfrog é seguro?
Openfrog — Nerq Trust Score 64.6/100 (Grau C). Com base na análise de 5 dimensões de confiança, é geralmente seguro, mas com algumas preocupações. Última atualização: 2026-04-01.
Use Openfrog com cautela. Openfrog is a software tool com uma Pontuação de Confiança Nerq de 64.6/100 (C), based on 5 independent data dimensions. It is below the recommended threshold of 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: 2026-04-01. Dados legíveis por máquina (JSON).
Openfrog é seguro?
CAUTION — Openfrog tem uma Pontuação de Confiança Nerq de 64.6/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
Qual é a pontuação de confiança de Openfrog?
Openfrog tem uma Pontuação de Confiança Nerq de 64.6/100, obtendo grau C. Esta pontuação é baseada em 5 dimensões medidas independentemente.
Quais são as principais descobertas de segurança de Openfrog?
O sinal mais forte de Openfrog é compliance com 100/100. Nenhuma vulnerabilidade conhecida foi detectada. Ainda não atingiu o limiar verificado Nerq de 70+.
O que é Openfrog e quem o mantém?
| Autor | xuwenhao |
| Categoria | coding |
| Source | https://github.com/xuwenhao/openfrog |
Conformidade Regulatória
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternativas Populares em coding
What Is Openfrog?
Openfrog is a software tool in the coding category: A collection of AI coding agents and SDKs for building autonomous agents.. Nerq Trust Score: 65/100 (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 Openfrog's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Openfrog performs in each:
- Segurança (0/100): Openfrog's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Manutenção (1/100): Openfrog 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): Openfrog 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 64.6/100 (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 Openfrog?
Openfrog is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Openfrog 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 Openfrog'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 Openfrog's dependency tree. - Avaliação permissions — Understand what access Openfrog requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Openfrog 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=openfrog - Revise o/a license — Confirm that Openfrog'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 Openfrog
When evaluating whether Openfrog is safe, consider these category-specific risks:
Understand how Openfrog processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Openfrog's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Openfrog. Security patches and bug fixes are only effective if you're running the latest version.
If Openfrog 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 Openfrog's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Openfrog in violation of its license can expose your organization to legal liability.
Openfrog and the EU AI Act
Openfrog 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 Openfrog Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Openfrog while minimizing risk:
Periodically review how Openfrog is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Openfrog and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Openfrog only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Openfrog's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Openfrog is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Openfrog?
Even promising tools aren't right for every situation. Consider avoiding Openfrog 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 Openfrog de 64.6/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Openfrog 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. Openfrog's score of 64.6/100 is above the category average of 62/100.
This positions Openfrog 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 Openfrog 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, Openfrog'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 Openfrog's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=openfrog&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 Openfrog are strengthening or weakening over time.
Openfrog vs Alternatives
In the coding category, Openfrog scores 64.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Openfrog vs AutoGPT — Trust Score: 74.7/100
- Openfrog vs ollama — Trust Score: 73.8/100
- Openfrog vs langchain — Trust Score: 86.4/100
Pontos Principais
- Openfrog tem uma Pontuação de Confiança de 64.6/100 (C) and is not yet Nerq Verified.
- Openfrog shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Openfrog 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.
Perguntas Frequentes
É Openfrog seguro para usar?
O que é Openfrog's trust score?
Quais são alternativas mais seguras a Openfrog?
How often is Openfrog's safety score updated?
Can I use Openfrog in a regulated environment?
Disclaimer: As pontuações de confiança da Nerq são avaliações automatizadas baseadas em sinais publicamente disponíveis. Não são endossos ou garantias. Sempre realize sua própria verificação.