Is Ultradata Math Safe?

Ultradata Math — Nerq Trust Score 56.9/100 (D grade). Based on analysis of 1 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-10.

Use Ultradata Math with some caution. Ultradata Math is a software tool (openbmb/UltraData-Math) with a Nerq Trust Score of 56.9/100 (D), based on 3 independent data dimensions. Below the recommended threshold of 70. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-10. Machine-readable data (JSON).

Is Ultradata Math safe?

CAUTION — Ultradata Math has a Nerq Trust Score of 56.9/100 (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.

Security Analysis → Ultradata Math Privacy Report →

What is Ultradata Math's trust score?

Ultradata Math has a Nerq Trust Score of 56.9/100, earning a D grade. This score is based on 1 independently measured dimensions including security, maintenance, and community adoption.

Compliance
87

What are the key security findings for Ultradata Math?

Ultradata Math's strongest signal is compliance at 87/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.

Compliance: 87/100 — covers 45 of 52 jurisdictions

What is Ultradata Math and who maintains it?

Authoropenbmb
CategoryUncategorized
Stars236
Sourcehttps://huggingface.co/datasets/openbmb/UltraData-Math
Protocolshuggingface_api

Regulatory Compliance

EU AI Act Risk ClassNot assessed
Compliance Score87/100
JurisdictionsAssessed across 52 jurisdictions

Ultradata Math Across Platforms

Same developer/company in other registries:

bmcook
56/100 · pypi

What Is Ultradata Math?

Ultradata Math is a software tool in the uncategorized category: openbmb/UltraData-Math. It has 236 GitHub stars. Nerq Trust Score: 57/100 (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 Ultradata Math's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Ultradata Math performs in each:

The overall Trust Score of 56.9/100 (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 Ultradata Math?

Ultradata Math is designed for:

Risk guidance: Ultradata Math 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 Ultradata Math'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 Ultradata Math's dependency tree.
  3. Review permissions — Understand what access Ultradata Math requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Ultradata Math 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=UltraData-Math
  6. Review the license — Confirm that Ultradata Math'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 Ultradata Math

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

Data handling

Understand how Ultradata Math 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 Ultradata Math's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

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

Third-party integrations

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

Best Practices for Using Ultradata Math Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

Subscribe to Ultradata Math'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 Ultradata Math is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Ultradata Math?

Even promising tools aren't right for every situation. Consider avoiding Ultradata Math in these scenarios:

For each scenario, evaluate whether Ultradata Math's trust score of 56.9/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Ultradata Math 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. Ultradata Math's score of 56.9/100 is near the category average of 62/100.

This places Ultradata Math in line with the typical uncategorized 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 Ultradata Math 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, Ultradata Math'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 Ultradata Math's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=UltraData-Math&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 Ultradata Math are strengthening or weakening over time.

Key Takeaways

Frequently Asked Questions

Is Ultradata Math Safe?
Use with some caution. UltraData-Math with a Nerq Trust Score of 56.9/100 (D). Strongest signal: compliance (87/100). Score based on multiple trust dimensions.
What is Ultradata Math's trust score?
UltraData-Math: 56.9/100 (D). Score based on multiple trust dimensions. Compliance: 87/100. Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=UltraData-Math
What are safer alternatives to Ultradata Math?
In the Uncategorized category, more software tools are being analyzed — check back soon. UltraData-Math scores 56.9/100.
How often is Ultradata Math's safety score updated?
Nerq continuously monitors Ultradata Math and updates its trust score as new data becomes available. Current: 56.9/100 (D), last verified 2026-04-10. API: GET nerq.ai/v1/preflight?target=UltraData-Math
Can I use Ultradata Math in a regulated environment?
Ultradata Math has not reached the Nerq Verified threshold of 70. Additional due diligence is recommended.
API: /v1/preflight Trust Badge API Docs

See Also

Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.

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