Is Ragflow Safe?
Ragflow — Nerq Trust Score 67.4/100 (B- grade). Based on analysis of 5 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-05-20.
Use Ragflow with some caution. Ragflow is a software tool with a Nerq Trust Score of 67.4/100 (B-), based on 5 independent data dimensions. Below the recommended threshold of 70. Security: 1/100. Maintenance: 1/100. Popularity: 1/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-05-20. Machine-readable data (JSON).
Is Ragflow safe?
CAUTION — Ragflow has a Nerq Trust Score of 67.4/100 (B-). 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.
What is Ragflow's trust score?
Ragflow has a Nerq Trust Score of 67.4/100, earning a B- grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Ragflow?
Ragflow's strongest signal is compliance at 100/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Ragflow and who maintains it?
| Author | infiniflow |
| Category | Infrastructure |
| Stars | 73,683 |
| Source | https://github.com/infiniflow/ragflow |
| Frameworks | openai · anthropic · ollama |
| Protocols | mcp · rest |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in infrastructure
Deep Analysis: infiniflow/ragflow
Executive Summary
infiniflow/ragflow is a infrastructure tool with a Nerq Trust Score of 67.4/100 (B-). No known vulnerabilities. 73,683 GitHub stars. RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Security
No known CVEs. infiniflow/ragflow has a clean security record in the Nerq database.
Maintenance Health
- GitHub stars: 73,683
- Activity score: 1/100
Ecosystem Position
- Compatible frameworks: haystack, openai
Cost Analysis
- Cost per code_review: $0.0300
- Cost per code_generation: $0.0450
- Cost per chat_response: $0.0075
- Cost per document_analysis: $0.0450
- Cost per data_extraction: $0.0225
Trust Score Breakdown
Strongest: Compliance (100/100). Weakest: Documentation (1/100).
How to Improve This Score
Frequently Asked Questions
Is ragflow safe to use in production?
Caution advised. ragflow has a Nerq Trust Score of 67.4/100 (B-). This is below the Nerq Verified threshold of 70. Consider alternatives or perform additional due diligence.
Does ragflow have any known vulnerabilities?
As of May 2026, ragflow has no known CVEs in the Nerq database.
What license does ragflow use?
License information is not yet available in the Nerq database.
How does ragflow compare to alternatives?
In the infrastructure category, ragflow scores 67.4/100. Use the Nerq comparison API to compare directly: curl nerq.ai/v1/compare/ragflow/vs/[alternative]
How often is ragflow updated?
Check the maintenance health section above for the latest activity data. Nerq tracks commit frequency, release cadence, and issue response times.
What Is Ragflow?
Ragflow is a software tool in the infrastructure category: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It has 73,683 GitHub stars. Nerq Trust Score: 67/100 (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 Ragflow's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Ragflow performs in each:
- Security (1/100): Ragflow's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Ragflow is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (100/100): Ragflow is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (1/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 67.4/100 (B-) 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 Ragflow?
Ragflow is designed for:
- Developers and teams working with infrastructure tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Ragflow 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 Ragflow'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 Ragflow's dependency tree. - Review permissions — Understand what access Ragflow requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Ragflow 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=infiniflow/ragflow - Review the license — Confirm that Ragflow'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 Ragflow
When evaluating whether Ragflow is safe, consider these category-specific risks:
Understand how Ragflow processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Ragflow's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Ragflow. Security patches and bug fixes are only effective if you're running the latest version.
If Ragflow 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 Ragflow's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Ragflow in violation of its license can expose your organization to legal liability.
Best Practices for Using Ragflow Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Ragflow while minimizing risk:
Periodically review how Ragflow is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Ragflow and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Ragflow only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Ragflow's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Ragflow is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Ragflow?
Even promising tools aren't right for every situation. Consider avoiding Ragflow 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 Ragflow's trust score of 67.4/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Ragflow Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among infrastructure tools, the average Trust Score is 62/100. Ragflow's score of 67.4/100 is above the category average of 62/100.
This positions Ragflow favorably among infrastructure 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 Ragflow 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, Ragflow'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 Ragflow's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=infiniflow/ragflow&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 Ragflow are strengthening or weakening over time.
Ragflow vs Alternatives
In the infrastructure category, Ragflow scores 67.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Ragflow vs n8n — Trust Score: 52.2/100
- Ragflow vs langflow — Trust Score: 66.1/100
- Ragflow vs dify — Trust Score: 65.5/100
Key Takeaways
- Ragflow has a Trust Score of 67.4/100 (B-) and is not yet Nerq Verified.
- Ragflow shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among infrastructure tools, Ragflow 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.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 1/100 |
| Maintenance | 1/100 |
| Popularity | 1/100 |
Based on 3 dimensions. Data from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Ragflow collect?
Privacy assessment for Ragflow is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Ragflow secure?
Security score: 1/100. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
Full analysis: Ragflow Security Report
How we calculated this score
Ragflow's trust score of 67.4/100 (B-) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 3 independent dimensions: security (1/100), maintenance (1/100), popularity (1/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on May 20, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
Is Ragflow Safe?
What is Ragflow's trust score?
What are safer alternatives to Ragflow?
How often is Ragflow's safety score updated?
Can I use Ragflow in a regulated environment?
See Also
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.