Je Ddddocr bezpečný?
Ddddocr — Nerq Trust Score 55.9/100 (Stupeň C). Na základě analýzy 5 dimenzí důvěryhodnosti je má pozoruhodné bezpečnostní obavy. Naposledy aktualizováno: 2026-04-25.
Používejte Ddddocr s opatrností. Ddddocr je software tool (一个基于 Rust 的 OCR API 服务器,用于验证码识别。) se skóre důvěryhodnosti Nerq 55.9/100 (C), based on 5 nezávislých datových dimenzích. Pod ověřeným prahem Nerq Bezpečnost: 0/100. Údržba: 1/100. Popularita: 0/100. Data pocházejí z více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard. Naposledy aktualizováno: 2026-04-25. Strojově čitelná data (JSON).
Je Ddddocr bezpečný?
CAUTION — Ddddocr has a Nerq Trust Score of 55.9/100 (C). Má střední signály důvěryhodnosti, ale vykazuje některé oblasti k pozornosti that warrant attention. Suitable for development use — review bezpečnost and údržba signals before production deployment.
Jaké je skóre důvěryhodnosti Ddddocr?
Ddddocr má Nerq skóre důvěryhodnosti 55.9/100 se stupněm C. Toto skóre je založeno na 5 nezávisle měřených dimenzích.
Jaká jsou klíčová bezpečnostní zjištění pro Ddddocr?
Nejsilnější signál Ddddocr je shoda na 100/100. Nebyly zjištěny žádné známé zranitelnosti. Dosud nedosáhl ověřeného prahu Nerq 70+.
Co je Ddddocr a kdo jej spravuje?
| Autor | 86maid |
| Kategorie | Coding |
| Hvězdičky | 282 |
| Zdroj | https://github.com/86maid/ddddocr |
| Protocols | mcp · rest |
Regulační shoda
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Populární alternativy v coding
What Is Ddddocr?
Ddddocr is a software tool in the coding category: 一个基于 Rust 的 OCR API 服务器,用于验证码识别。. It has 282 GitHub stars. Nerq Trust Score: 56/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpečnost vulnerabilities, údržba activity, license shoda, and přijetí komunitou.
How Nerq Assesses Ddddocr's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimenzích. Here is how Ddddocr performs in each:
- Bezpečnost (0/100): Ddddocr's bezpečnost posture is poor. This score factors in known CVEs, dependency vulnerabilities, bezpečnost policy presence, and code signing practices.
- Údržba (1/100): Ddddocr 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 dokumentace, usage examples, and contribution guidelines.
- Compliance (100/100): Ddddocr is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Založeno na GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 55.9/100 (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 Ddddocr?
Ddddocr 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: Ddddocr is suitable for development and testing environments. Before production deployment, conduct a thorough review of its bezpečnost posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Ddddocr's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Zkontrolujte repository's bezpečnost policy, open issues, and recent commits for signs of active údržba.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Ddddocr's dependency tree. - Recenze permissions — Understand what access Ddddocr requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Ddddocr 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=ddddocr - Zkontrolujte license — Confirm that Ddddocr'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 bezpečnost concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Ddddocr
When evaluating whether Ddddocr is safe, consider these category-specific risks:
Understand how Ddddocr processes, stores, and transmits your data. Zkontrolujte tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Ddddocr's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher bezpečnost risk.
Regularly check for updates to Ddddocr. Bezpečnost patches and bug fixes are only effective if you're running the latest version.
If Ddddocr 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 Ddddocr's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Ddddocr in violation of its license can expose your organization to legal liability.
Ddddocr and the EU AI Act
Ddddocr 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 shoda assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal shoda.
Best Practices for Using Ddddocr Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Ddddocr while minimizing risk:
Periodically review how Ddddocr is used in your workflow. Check for unexpected behavior, permissions drift, and shoda with your bezpečnost policies.
Ensure Ddddocr and all its dependencies are running the latest stable versions to benefit from bezpečnost patches.
Grant Ddddocr only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Ddddocr's bezpečnost advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Ddddocr is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Ddddocr?
Even promising tools aren't right for every situation. Consider avoiding Ddddocr in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional shoda review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Ddddocr's trust score of 55.9/100 meets your organization's risk tolerance. We recommend running a manual bezpečnost assessment alongside the automated Nerq score.
How Ddddocr 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. Ddddocr's score of 55.9/100 is near the category average of 62/100.
This places Ddddocr 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 střední 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 Ddddocr 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 údržba patterns change, Ddddocr'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 bezpečnost and quality. Conversely, a downward trend may signal reduced údržba, growing technical debt, or unresolved vulnerabilities. To track Ddddocr's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=ddddocr&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 — bezpečnost, údržba, dokumentace, shoda, and community — has evolved independently, providing granular visibility into which aspects of Ddddocr are strengthening or weakening over time.
Ddddocr vs Alternativy
In the coding category, Ddddocr scores 55.9/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Ddddocr vs AutoGPT — Trust Score: 74.7/100
- Ddddocr vs ollama — Trust Score: 73.8/100
- Ddddocr vs langchain — Trust Score: 71.3/100
Hlavní závěry
- Ddddocr has a Trust Score of 55.9/100 (C) and is not yet Nerq Verified.
- Ddddocr shows střední trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Ddddocr scores near 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.
Podrobná analýza skóre
| Dimension | Score |
|---|---|
| Bezpečnost | 0/100 |
| Údržba | 1/100 |
| Popularita | 0/100 |
Založeno na 3 dimenzích. Data from více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard.
Jaká data Ddddocr shromažďuje?
Soukromí assessment for Ddddocr is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Je Ddddocr bezpečný?
Bezpečnost score: 0/100. Review bezpečnost practices and consider alternatives with higher bezpečnost scores for sensitive use cases.
Nerq monitoruje tuto entitu oproti NVD, OSV.dev a databázím zranitelností specifickým pro registry pro průběžné bezpečnostní hodnocení.
Úplná analýza: Bezpečnostní zpráva Ddddocr
Jak jsme vypočítali toto skóre
Ddddocr's trust score of 55.9/100 (C) je vypočítáno z více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard. Skóre odráží 3 nezávislých dimenzí: bezpečnost (0/100), údržba (1/100), popularita (0/100). Každá dimenze má stejnou váhu pro vytvoření souhrnného skóre důvěryhodnosti.
Nerq analyzuje více než 7,5 milionu entit ve 26 registrech pomocí stejné metodologie, což umožňuje přímé srovnání mezi entitami. Skóre jsou průběžně aktualizována, jakmile jsou k dispozici nová data.
Tato stránka byla naposledy zkontrolována April 25, 2026. Verze dat: 1.0.
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Často kladené otázky
Je Ddddocr bezpečný?
Jaké je skóre důvěryhodnosti Ddddocr?
Jaké jsou bezpečnější alternativy k Ddddocr?
Jak často se aktualizuje bezpečnostní skóre Ddddocr?
Mohu používat Ddddocr v regulovaném prostředí?
Viz také
Disclaimer: Skóre důvěryhodnosti Nerq jsou automatizovaná hodnocení založená na veřejně dostupných signálech. Nejsou doporučením ani zárukou. Vždy proveďte vlastní ověření.