Is Open Autoglm Android Safe? — Trust Score: 80.0/100

Why This Score

• Security score: 0/100 (weak)
• Maintenance: 1/100 — low maintenance activity
• Compliance: 82/100 — covers 42 of 52 jurisdictions
• Documentation: 1/100 — limited documentation
• Popularity: 0/100 — 1 stars on github

What Is Open Autoglm Android?

Open Autoglm Android is a automation platform that connects AI capabilities with workflow orchestration. Automate Android phone tasks with AI for seamless local control.

As of March 2026, Open Autoglm Android is available on github, making it an emerging tool 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 Open Autoglm Android's Safety

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

• Security (0/100): Open Autoglm Android's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
• Maintenance (1/100): Open Autoglm Android 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 (82/100): Open Autoglm Android 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 80.0/100 (A) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.

Who Should Use Open Autoglm Android?

Open Autoglm Android is designed for:

• Teams automating repetitive workflows
• Organizations connecting multiple tools and services
• Developers building event-driven AI pipelines

Risk guidance: Open Autoglm Android is well-suited for production environments. Its high trust score indicates robust security, active maintenance, and strong community support. Standard security practices (dependency pinning, access controls, monitoring) are still recommended.

How to Verify Open Autoglm Android's Safety Yourself

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

1. Check the source code — Review the repository's 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 Open Autoglm Android's dependency tree.
3. Review permissions — Understand what access Open Autoglm Android requires. AI tools should follow the principle of least privilege.
4. Test in isolation — Run Open Autoglm Android 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=Open-AutoGLM-Android
6. Review the license — Confirm that Open Autoglm Android'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 Open Autoglm Android

When evaluating whether Open Autoglm Android is safe, consider these category-specific risks:

Open Autoglm Android and the EU AI Act

Open Autoglm Android 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 Open Autoglm Android Safely

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

When Should You Avoid Open Autoglm Android?

Even well-trusted tools aren't right for every situation. Consider avoiding Open Autoglm Android in these scenarios:

• Scenarios where Open Autoglm Android'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 Open Autoglm Android's trust score of 80.0/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Open Autoglm Android Compares to Industry Standards

Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among automation tools, the average Trust Score is 64/100. Open Autoglm Android's score of 80.0/100 is significantly above the category average of 64/100.

This places Open Autoglm Android in the top tier of automation 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 Open Autoglm Android 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, Open Autoglm Android'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 Open Autoglm Android's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Open-AutoGLM-Android&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 Open Autoglm Android are strengthening or weakening over time.

Open Autoglm Android vs Alternatives

In the automation category, Open Autoglm Android scores 80.0/100. It ranks among the top tools in its category. For a detailed comparison, see:

• Open Autoglm Android vs Windows Desktop Control — Trust Score: 46.2/100
• Open Autoglm Android vs baserow — Trust Score: 82.1/100
• Open Autoglm Android vs gemma-7b — Trust Score: 62.2/100

Key Takeaways

• Open Autoglm Android has a Trust Score of 80.0/100 (A) and is Nerq Verified.
• Open Autoglm Android demonstrates strong trust signals and is well-suited for production use with standard security precautions.
• Among automation tools, Open Autoglm Android scores significantly above the category average of 64/100, demonstrating above-average reliability.
• Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.

Related Safety Checks