Is Hivemind Safe?
Hivemind — Nerq Trust Score 42.5/100 (E grade). Based on analysis of 3 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-01.
Exercise caution with Hivemind. Hivemind is a software tool with a Nerq Trust Score of 42.5/100 (E), based on 3 independent data dimensions. It is below the recommended threshold of 70. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-01. Machine-readable data (JSON).
Is Hivemind safe?
NO — USE WITH CAUTION — Hivemind has a Nerq Trust Score of 42.5/100 (E). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.
What is Hivemind's trust score?
Hivemind has a Nerq Trust Score of 42.5/100, earning a E grade. This score is based on 3 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Hivemind?
Hivemind's strongest signal is maintenance at 0/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Hivemind and who maintains it?
| Author | https://github.com/quantulabs/hivemind |
| Category | AI tool |
| Stars | 1 |
| Source | https://github.com/quantulabs/hivemind |
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What Is Hivemind?
Hivemind is a software tool in the AI tool category: Queries multiple AI models for consensus responses.. It has 1 GitHub stars. Nerq Trust Score: 42/100 (E).
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 Hivemind's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Hivemind performs in each:
- Maintenance (0/100): Hivemind 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 documentation, usage examples, and contribution guidelines.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 42.5/100 (E) 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 Hivemind?
Hivemind is designed for:
- Developers and teams working with AI tool tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Hivemind. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Hivemind'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 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 Hivemind's dependency tree. - Review permissions — Understand what access Hivemind requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Hivemind 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=io.github.QuantuLabs/hivemind - Review the license — Confirm that Hivemind'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 Hivemind
When evaluating whether Hivemind is safe, consider these category-specific risks:
Understand how Hivemind processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Hivemind's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Hivemind. Security patches and bug fixes are only effective if you're running the latest version.
If Hivemind 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 Hivemind's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Hivemind in violation of its license can expose your organization to legal liability.
Best Practices for Using Hivemind Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Hivemind while minimizing risk:
Periodically review how Hivemind is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Hivemind and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Hivemind only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Hivemind's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Hivemind is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Hivemind?
Even promising tools aren't right for every situation. Consider avoiding Hivemind 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 Hivemind's trust score of 42.5/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Hivemind Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among AI tool tools, the average Trust Score is 62/100. Hivemind's score of 42.5/100 is below the category average of 62/100.
This suggests that Hivemind trails behind many comparable AI tool tools. Organizations with strict security requirements should evaluate whether higher-scoring alternatives better meet their needs.
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 Hivemind 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, Hivemind'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 Hivemind's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=io.github.QuantuLabs/hivemind&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 Hivemind are strengthening or weakening over time.
Hivemind vs Alternatives
In the AI tool category, Hivemind scores 42.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Hivemind vs openclaw — Trust Score: 84.3/100
- Hivemind vs stable-diffusion-webui — Trust Score: 69.3/100
- Hivemind vs prompts.chat — Trust Score: 69.3/100
Key Takeaways
- Hivemind has a Trust Score of 42.5/100 (E) and is not yet Nerq Verified.
- Hivemind has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among AI tool tools, Hivemind scores below 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.