Is Adal Safe?
According to Nerq's independent analysis of adal, this pypi has a trust score of 73.5 out of 100, earning a B grade. With 8,992,743 stars on pypi, it is recommended for production use. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Adal safe?
YES — Adal has a Nerq Trust Score of 73.5/100 (B). 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 Score Breakdown
Key Findings
Details
| Author | Microsoft Corporation |
| Category | pypi |
| Stars | 8,992,743 |
| Source | N/A |
What Is Adal?
Adal is a AI tool in the pypi category. Note: This library is already replaced by MSAL Python, available here: https://pypi.org/project/msal/ .ADAL Python remains available here as a legacy. The ADAL for Python library makes it easy for python application to authenticate to Azure Active Directory (AAD) in order to access AAD protected web
As of March 2026, Adal has 8,992,743 stars on pypi, making it one of the most popular tools in its category 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 Adal's Safety
Nerq evaluates every AI 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).
Adal receives an overall Trust Score of 73.5/100 (B), which Nerq considers good. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use. With 8,992,743 GitHub stars, Adal benefits from a large community that can identify and report issues quickly.
Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=adal
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 Adal'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 Should Use Adal?
Adal is designed for:
- Developers and teams working with pypi tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Adal meets the minimum threshold for production use, but we recommend monitoring for security advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.
How to Verify Adal'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 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 Adal's dependency tree. - Review permissions — Understand what access Adal requires. AI tools should follow the principle of least privilege.
- Test in isolation — Run Adal 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=adal - Review the license — Confirm that Adal'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 Adal
When evaluating whether Adal is safe, consider these category-specific risks:
Understand how Adal processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Adal's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Adal. Security patches and bug fixes are only effective if you're running the latest version.
If Adal 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 Adal's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Adal in violation of its license can expose your organization to legal liability.
Best Practices for Using Adal Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Adal while minimizing risk:
Periodically review how Adal is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Adal and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Adal only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Adal's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Adal is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Adal?
Even well-trusted tools aren't right for every situation. Consider avoiding Adal in these scenarios:
- Scenarios where Adal'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 Adal's trust score of 73.5/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.
How Adal Compares to Industry Standards
Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among pypi tools, the average Trust Score is 62/100. Adal's score of 73.5/100 is significantly above the category average of 62/100.
This places Adal in the top tier of pypi 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 Adal 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, Adal'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 Adal's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=adal&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 Adal are strengthening or weakening over time.
Key Takeaways
- Adal has a Trust Score of 73.5/100 (B) and is Nerq Verified.
- Adal meets the minimum threshold for production deployment, though monitoring and additional guardrails are recommended.
- Among pypi tools, Adal 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.