Is Maiat Safe?

Maiat — Nerq Trust Score 37.9/100 (E grade). Score based on 5 independent trust signals.

Maiat is a software tool with a Nerq Trust Score of 37.9/100 (E). Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: n/a. Machine-readable data (JSON).

Is Maiat safe?

Trust Score Breakdown — Maiat has a Nerq Trust Score of 37.9/100 (E). Measured across 1 independent trust signal.

Security Analysis → Maiat Privacy Report →

What is Maiat's trust score?

Maiat has a Nerq Trust Score of 37.9/100, earning a E grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.

Overall Trust
37.9

What are the key security findings for Maiat?

Maiat's strongest signal is overall trust at 37.9/100. No known vulnerabilities have been detected.

Composite trust score: 37.9/100 across all available signals

What is Maiat and who maintains it?

Author0x5f725b18e3a783a1d7157543af1a9814753fa788
CategoryUncategorized
Sourcehttps://8004scan.io/agents/maiat

What Is Maiat?

Maiat is a software tool in the uncategorized category: The trust oracle for the onchain agent economy. Scores AI agent behavior using ACP job history (completion rate, payment rate, expiry rate). Provides trust scores 0-100 for 449+ Virtuals agents.. Nerq Trust Score: 38/100 (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 Maiat's Safety

Nerq evaluates every software tool across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core dimensions: Security (known CVEs, dependency vulnerabilities, security policies), Maintenance (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 jurisdictions), and Community (stars, forks, downloads, ecosystem integrations).

Maiat receives an overall Trust Score of 37.9/100 (E). This is a measured composite, not a suitability judgment.

Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=Maiat

Each dimension is weighted according to its importance for the tool's category. For example, Security and Maintenance carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Maiat's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five dimensions, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).

Who Typically Evaluates Maiat?

Maiat is commonly evaluated by:

How to read the signals: Maiat's measured signals (the trust signals above) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.

How to Verify Maiat's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Maiat's dependency tree.
  3. Review permissions — Understand what access Maiat requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Maiat in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=Maiat
  6. Review the license — Confirm that Maiat'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.
  7. 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 Maiat

When evaluating whether Maiat is safe, consider these category-specific risks:

Data handling

Understand how Maiat processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Maiat's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Maiat. Security patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Maiat 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.

License and IP compliance

Verify that Maiat's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Maiat in violation of its license can expose your organization to legal liability.

Best Practices for Using Maiat Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Maiat while minimizing risk:

Conduct regular audits

Periodically review how Maiat is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Maiat and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

Grant Maiat only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for security advisories

Subscribe to Maiat's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Maiat is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Maiat

Nerq's signals are one input. In the following situations, evaluate Maiat's measured signals against your own requirements before making a decision:

For each situation, compare Maiat's measured trust score of 37.9/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Maiat is suitable for any particular use.

How Maiat Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Maiat's score of 37.9/100 is below the category average of 62/100.

This suggests that Maiat trails behind many comparable uncategorized 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 Maiat 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, Maiat'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 Maiat's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Maiat&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 Maiat are strengthening or weakening over time.

Key Takeaways

Frequently Asked Questions

Is Maiat Safe?
Maiat with a Nerq Trust Score of 37.9/100 (E). Strongest signal: overall trust (37.9/100). Score based on multiple trust dimensions.
What is Maiat's trust score?
Maiat: 37.9/100 (E). Score based on multiple trust dimensions. Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=Maiat
What are safer alternatives to Maiat?
In the Uncategorized category, more software tools are being analyzed — check back soon. Maiat scores 37.9/100.
How often is Maiat's safety score updated?
Nerq recomputes Maiat's trust score as new data becomes available. Current: 37.9/100 (E). API: GET nerq.ai/v1/preflight?target=Maiat
Can I use Maiat in a regulated environment?
Maiat: 37.9/100 (E). Compliance signals are shown in the breakdown above. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

See Also

Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.

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