Is Dingtalk Moltbot Connector Safe? — Trust Score: 85.5/100
According to Nerq's independent analysis of dingtalk-moltbot-connector, this communication has a trust score of 85.5 out of 100, earning a A grade. With 1,237 stars on github, it is recommended for production use. Security score: 1/100. Compliance: 96/100 across 52 jurisdictions. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-19. Machine-readable data (JSON).
Is Dingtalk Moltbot Connector safe?
YES — Dingtalk Moltbot Connector has a Nerq Trust Score of 85.5/100 (A). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
Trust Assessment
Highly Trusted — dingtalk-moltbot-connector ranks among the top AI agents with exceptional trust signals across security, maintenance, and ecosystem metrics. It has been independently assessed by Nerq and demonstrates consistently strong quality indicators.
Trust Signal Breakdown
Details
| Author | DingTalk-Real-AI |
| Category | communication |
| Stars | 1,237 |
| Source | https://github.com/DingTalk-Real-AI/dingtalk-moltbot-connector |
| Frameworks | openai |
| Protocols | mcp · a2a · rest · websocket |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 96/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
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What Is Dingtalk Moltbot Connector?
Dingtalk Moltbot Connector is a AI tool in the communication category. 连接钉钉机器人和DEAP Agent到OpenClaw Gateway，支持流式AI响应
As of March 2026, Dingtalk Moltbot Connector has 1,237 stars on github, making it a notable tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.
How Nerq Assesses Dingtalk Moltbot Connector's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Dingtalk Moltbot Connector performs in each:
- Security (1/100): Dingtalk Moltbot Connector's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Dingtalk Moltbot Connector 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 (96/100): Dingtalk Moltbot Connector 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 85.5/100 (A) 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 Dingtalk Moltbot Connector?
Dingtalk Moltbot Connector is designed for:
- Developers and teams working with communication tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Dingtalk Moltbot Connector is well-suited for production environments. Its high trust score indicates robust security, active maintenance, and strong community support. Standard security practices (dependency pinning, access controls, monitoring) are still recommended.
How to Verify Dingtalk Moltbot Connector's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI 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 Dingtalk Moltbot Connector's dependency tree. - Review permissions — Understand what access Dingtalk Moltbot Connector requires. AI tools should follow the principle of least privilege.
- Test in isolation — Run Dingtalk Moltbot Connector 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=dingtalk-moltbot-connector - Review the license — Confirm that Dingtalk Moltbot Connector'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 Dingtalk Moltbot Connector
When evaluating whether Dingtalk Moltbot Connector is safe, consider these category-specific risks:
Understand how Dingtalk Moltbot Connector processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Dingtalk Moltbot Connector's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Dingtalk Moltbot Connector. Security patches and bug fixes are only effective if you're running the latest version.
If Dingtalk Moltbot Connector 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 Dingtalk Moltbot Connector's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Dingtalk Moltbot Connector in violation of its license can expose your organization to legal liability.
Best Practices for Using Dingtalk Moltbot Connector Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Dingtalk Moltbot Connector while minimizing risk:
Periodically review how Dingtalk Moltbot Connector is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Dingtalk Moltbot Connector and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Dingtalk Moltbot Connector only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Dingtalk Moltbot Connector's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Dingtalk Moltbot Connector is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Dingtalk Moltbot Connector?
Even well-trusted tools aren't right for every situation. Consider avoiding Dingtalk Moltbot Connector in these scenarios:
- Scenarios where Dingtalk Moltbot Connector's specific capabilities exceed your actual needs — simpler tools may be safer
- Air-gapped environments where the tool cannot receive security updates
- Projects with strict regulatory requirements that haven't been explicitly validated
For each scenario, evaluate whether Dingtalk Moltbot Connector's trust score of 85.5/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.
How Dingtalk Moltbot Connector Compares to Industry Standards
Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among communication tools, the average Trust Score is 62/100. Dingtalk Moltbot Connector's score of 85.5/100 is significantly above the category average of 62/100.
This places Dingtalk Moltbot Connector in the top tier of communication tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature security practices, consistent release cadence, and broad community adoption.
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 Dingtalk Moltbot Connector 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, Dingtalk Moltbot Connector'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 Dingtalk Moltbot Connector's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=dingtalk-moltbot-connector&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 Dingtalk Moltbot Connector are strengthening or weakening over time.
Dingtalk Moltbot Connector vs Alternatives
In the communication category, Dingtalk Moltbot Connector scores 85.5/100. It ranks among the top tools in its category. For a detailed comparison, see:
- Dingtalk Moltbot Connector vs Real-Time-Voice-Cloning — Trust Score: 71.3/100
- Dingtalk Moltbot Connector vs ChatGPT — Trust Score: 73.8/100
- Dingtalk Moltbot Connector vs chatgpt-on-wechat — Trust Score: 80.7/100
Key Takeaways
- Dingtalk Moltbot Connector has a Trust Score of 85.5/100 (A) and is Nerq Verified.
- Dingtalk Moltbot Connector demonstrates strong trust signals and is well-suited for production use with standard security precautions.
- Among communication tools, Dingtalk Moltbot Connector 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.
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.