Is Zcagent Safe?
Zcagent — Nerq Trust Score 57.7/100 (D grade). Based on analysis of 5 trust dimensions, it is has notable safety concerns. Last updated: 2026-03-31.
Use Zcagent with some caution. Zcagent is a software tool with a Nerq Trust Score of 57.7/100 (D), 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: 2026-03-31. Machine-readable data (JSON).
Is Zcagent safe?
CAUTION — Zcagent has a Nerq Trust Score of 57.7/100 (D). 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 Zcagent's trust score?
Zcagent has a Nerq Trust Score of 57.7/100, earning a D grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Zcagent?
Zcagent'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 Zcagent and who maintains it?
| Author | gqhhhhh |
| Category | coding |
| Source | https://github.com/gqhhhhh/ZCAgent |
| Frameworks | langchain · autogen · openai · anthropic |
| Protocols | mcp · rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
What Is Zcagent?
Zcagent is a software tool in the coding category: ZCAgent 是一个基于 LLM+RAG 的智能座舱一体化语义 Agent 系统。. Nerq Trust Score: 58/100 (D).
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 Zcagent's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Zcagent performs in each:
- Security (0/100): Zcagent's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Zcagent 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): Zcagent 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 57.7/100 (D) 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 Zcagent?
Zcagent 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: Zcagent 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 Zcagent'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 Zcagent's dependency tree. - Review permissions — Understand what access Zcagent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Zcagent 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=ZCAgent - Review the license — Confirm that Zcagent'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 Zcagent
When evaluating whether Zcagent is safe, consider these category-specific risks:
Understand how Zcagent processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Zcagent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Zcagent. Security patches and bug fixes are only effective if you're running the latest version.
If Zcagent 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 Zcagent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Zcagent in violation of its license can expose your organization to legal liability.
Zcagent and the EU AI Act
Zcagent 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 Zcagent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Zcagent while minimizing risk:
Periodically review how Zcagent is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Zcagent and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Zcagent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Zcagent's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Zcagent is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Zcagent?
Even promising tools aren't right for every situation. Consider avoiding Zcagent 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 Zcagent's trust score of 57.7/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Zcagent 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. Zcagent's score of 57.7/100 is near the category average of 62/100.
This places Zcagent 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 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 Zcagent 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, Zcagent'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 Zcagent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=ZCAgent&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 Zcagent are strengthening or weakening over time.
Zcagent vs Alternatives
In the coding category, Zcagent scores 57.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Zcagent vs AutoGPT — Trust Score: 74.7/100
- Zcagent vs ollama — Trust Score: 73.8/100
- Zcagent vs langchain — Trust Score: 86.4/100
Key Takeaways
- Zcagent has a Trust Score of 57.7/100 (D) and is not yet Nerq Verified.
- Zcagent shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Zcagent 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.
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.