क्या Openframeworks सुरक्षित है?
Openframeworks — Nerq Trust Score 72.2/100 (B ग्रेड). 5 विश्वास आयामों के विश्लेषण के आधार पर, इसे आम तौर पर सुरक्षित लेकिन कुछ चिंताएं हैं माना जाता है। अंतिम अपडेट: 2026-04-23।
हां, Openframeworks उपयोग के लिए सुरक्षित है। Openframeworks एक software tool है Nerq विश्वास स्कोर के साथ 72.2/100 (B), based on 5 स्वतंत्र डेटा आयाम. उपयोग के लिए अनुशंसित. सुरक्षा: 0/100. रखरखाव: 0/100. लोकप्रियता: 0/100. डेटा स्रोत: पैकेज रजिस्ट्री, GitHub, NVD, OSV.dev और OpenSSF Scorecard सहित कई सार्वजनिक स्रोत. अंतिम अपडेट: 2026-04-23. मशीन पठनीय डेटा (JSON).
क्या Openframeworks सुरक्षित है?
YES — Openframeworks has a Nerq Trust Score of 72.2/100 (B). सुरक्षा, रखरखाव और सामुदायिक स्वीकृति में मजबूत संकेतों के साथ Nerq विश्वास सीमा को पूरा करता है. उपयोग के लिए अनुशंसित — विशिष्ट विचारों के लिए नीचे पूरी रिपोर्ट देखें.
Openframeworks का विश्वास स्कोर क्या है?
Openframeworks का Nerq Trust Score 72.2/100 है, ग्रेड B। यह स्कोर सुरक्षा, रखरखाव और सामुदायिक अपनाने सहित 5 स्वतंत्र रूप से मापे गए आयामों पर आधारित है।
Openframeworks के प्रमुख सुरक्षा निष्कर्ष क्या हैं?
Openframeworks का सबसे मजबूत संकेत अनुपालन है 100/100 पर। कोई ज्ञात भेद्यता नहीं पाई गई। It meets the Nerq Verified threshold of 70+.
Openframeworks क्या है और इसका रखरखाव कौन करता है?
| डेवलपर | Unknown |
| श्रेणी | Other |
| स्टार्स | 10,331 |
| स्रोत | https://github.com/openframeworks/openFrameworks |
नियामक अनुपालन
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
other में लोकप्रिय विकल्प
What Is Openframeworks?
Openframeworks is a software tool in the other category: openFrameworks is a community-developed cross platform toolkit for creative coding in C++.. It has 10,331 GitHub stars. Nerq Trust Score: 72/100 (B).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including सुरक्षा vulnerabilities, रखरखाव activity, license अनुपालन, and सामुदायिक स्वीकृति.
How Nerq Assesses Openframeworks's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five आयाम. Here is how Openframeworks performs in each:
- सुरक्षा (0/100): Openframeworks's सुरक्षा posture is poor. This score factors in known CVEs, dependency vulnerabilities, सुरक्षा policy presence, and code signing practices.
- रखरखाव (0/100): Openframeworks 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 दस्तावेज़ीकरण, usage examples, and contribution guidelines.
- Compliance (100/100): Openframeworks is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. आधारित GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 72.2/100 (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 Openframeworks?
Openframeworks is designed for:
- Developers and teams working with other tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Openframeworks meets the minimum threshold for production use, but we recommend monitoring for सुरक्षा advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.
How to Verify Openframeworks's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — जांचें repository's सुरक्षा policy, open issues, and recent commits for signs of active रखरखाव.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Openframeworks's dependency tree. - समीक्षा permissions — Understand what access Openframeworks requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Openframeworks 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=openframeworks/openFrameworks - जांचें license — Confirm that Openframeworks'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 सुरक्षा concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Openframeworks
When evaluating whether Openframeworks is safe, consider these category-specific risks:
Understand how Openframeworks processes, stores, and transmits your data. जांचें tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Openframeworks's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher सुरक्षा risk.
Regularly check for updates to Openframeworks. सुरक्षा patches and bug fixes are only effective if you're running the latest version.
If Openframeworks 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 Openframeworks's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Openframeworks in violation of its license can expose your organization to legal liability.
Best Practices for Using Openframeworks Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Openframeworks while minimizing risk:
Periodically review how Openframeworks is used in your workflow. Check for unexpected behavior, permissions drift, and अनुपालन with your सुरक्षा policies.
Ensure Openframeworks and all its dependencies are running the latest stable versions to benefit from सुरक्षा patches.
Grant Openframeworks only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Openframeworks's सुरक्षा advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Openframeworks is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Openframeworks?
Even well-trusted tools aren't right for every situation. Consider avoiding Openframeworks in these scenarios:
- Scenarios where Openframeworks's specific capabilities exceed your actual needs — simpler tools may be safer
- Air-gapped environments where the tool cannot receive सुरक्षा updates
- Projects with strict regulatory requirements that haven't been explicitly validated
For each scenario, evaluate whether Openframeworks's trust score of 72.2/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.
How Openframeworks Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among other tools, the average Trust Score is 62/100. Openframeworks's score of 72.2/100 is significantly above the category average of 62/100.
This places Openframeworks in the top tier of other tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature सुरक्षा practices, consistent release cadence, and broad सामुदायिक स्वीकृति.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks मध्यम 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 Openframeworks 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 रखरखाव patterns change, Openframeworks'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 सुरक्षा and quality. Conversely, a downward trend may signal reduced रखरखाव, growing technical debt, or unresolved vulnerabilities. To track Openframeworks's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=openframeworks/openFrameworks&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 — सुरक्षा, रखरखाव, दस्तावेज़ीकरण, अनुपालन, and community — has evolved independently, providing granular visibility into which aspects of Openframeworks are strengthening or weakening over time.
Openframeworks vs विकल्प
In the other category, Openframeworks scores 72.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Openframeworks vs cs-video-courses — Trust Score: 69.3/100
- Openframeworks vs awesome-scalability — Trust Score: 71.8/100
- Openframeworks vs superpowers — Trust Score: 71.8/100
मुख्य निष्कर्ष
- Openframeworks has a Trust Score of 72.2/100 (B) and is Nerq Verified.
- Openframeworks meets the minimum threshold for production deployment, though monitoring and additional guardrails are recommended.
- Among other tools, Openframeworks scores significantly 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.
विस्तृत स्कोर विश्लेषण
| Dimension | Score |
|---|---|
| सुरक्षा | 0/100 |
| रखरखाव | 0/100 |
| लोकप्रियता | 0/100 |
आधारित 3 आयाम. Data from पैकेज रजिस्ट्री, GitHub, NVD, OSV.dev और OpenSSF Scorecard सहित कई सार्वजनिक स्रोत.
Openframeworks कौन सा डेटा एकत्र करता है?
गोपनीयता assessment for Openframeworks is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
क्या Openframeworks सुरक्षित है?
सुरक्षा score: 0/100. Review सुरक्षा practices and consider alternatives with higher सुरक्षा scores for sensitive use cases.
Nerq इस इकाई को NVD, OSV.dev और रजिस्ट्री-विशिष्ट कमजोरी डेटाबेस के विरुद्ध मॉनिटर करता है निरंतर सुरक्षा मूल्यांकन के लिए.
पूर्ण विश्लेषण: Openframeworks सुरक्षा रिपोर्ट
हमने इस स्कोर की गणना कैसे की
Openframeworks's trust score of 72.2/100 (B) से गणना की गई है पैकेज रजिस्ट्री, GitHub, NVD, OSV.dev और OpenSSF Scorecard सहित कई सार्वजनिक स्रोत. स्कोर प्रतिबिंबित करता है 3 स्वतंत्र आयाम: सुरक्षा (0/100), रखरखाव (0/100), लोकप्रियता (0/100). समग्र विश्वास स्कोर बनाने के लिए प्रत्येक आयाम को समान भार दिया गया है.
Nerq 26 रजिस्ट्री में 7.5 मिलियन से अधिक इकाइयों का विश्लेषण करता है एक ही कार्यप्रणाली का उपयोग करके, इकाइयों के बीच सीधी तुलना संभव बनाता है. नया डेटा उपलब्ध होने पर स्कोर लगातार अपडेट किए जाते हैं.
इस पेज की अंतिम समीक्षा की गई: April 23, 2026. डेटा संस्करण: 1.0.
अक्सर पूछे जाने वाले प्रश्न
क्या Openframeworks सुरक्षित है?
Openframeworks का विश्वास स्कोर क्या है?
Openframeworks के अधिक सुरक्षित विकल्प क्या हैं?
Openframeworks का सुरक्षा स्कोर कितनी बार अपडेट होता है?
क्या मैं विनियमित वातावरण में Openframeworks उपयोग कर सकता हूँ?
यह भी देखें
Disclaimer: Nerq विश्वास स्कोर सार्वजनिक रूप से उपलब्ध संकेतों पर आधारित स्वचालित मूल्यांकन हैं। ये सिफारिश या गारंटी नहीं हैं। हमेशा अपना स्वयं का सत्यापन करें।