Is Llm Projects Safe?
Llm Projects — Nerq Trust Score 49.4/100 (D grade). Based on analysis of 1 trust dimensions, it is has notable safety concerns. Last updated: 2026-05-20.
Exercise caution with Llm Projects. Llm Projects is a software tool with a Nerq Trust Score of 49.4/100 (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: 2026-05-20. Machine-readable data (JSON).
Is Llm Projects safe?
NO — USE WITH CAUTION — Llm Projects has a Nerq Trust Score of 49.4/100 (D). 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 Llm Projects's trust score?
Llm Projects has a Nerq Trust Score of 49.4/100, earning a D grade. This score is based on 1 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Llm Projects?
Llm Projects's strongest signal is compliance at 100/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Llm Projects and who maintains it?
| Author | product-rollcall |
| Category | Uncategorized |
| Source | https://huggingface.co/spaces/product-rollcall/LLM-projects |
| Protocols | huggingface_hub |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
What Is Llm Projects?
Llm Projects is a software tool in the uncategorized category available on huggingface_space_full. Nerq Trust Score: 49/100 (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 Llm Projects's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Llm Projects performs in each:
- Compliance (100/100): Llm Projects is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
The overall Trust Score of 49.4/100 (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 Llm Projects?
Llm Projects is designed for:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Llm Projects. 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 Llm Projects'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 Llm Projects's dependency tree. - Review permissions — Understand what access Llm Projects requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Llm Projects 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=LLM-projects - Review the license — Confirm that Llm Projects'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 Llm Projects
When evaluating whether Llm Projects is safe, consider these category-specific risks:
Understand how Llm Projects processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Llm Projects's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Llm Projects. Security patches and bug fixes are only effective if you're running the latest version.
If Llm Projects 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 Llm Projects's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Llm Projects in violation of its license can expose your organization to legal liability.
Best Practices for Using Llm Projects Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Llm Projects while minimizing risk:
Periodically review how Llm Projects is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Llm Projects and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Llm Projects only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Llm Projects's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Llm Projects is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Llm Projects?
Even promising tools aren't right for every situation. Consider avoiding Llm Projects 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 Llm Projects's trust score of 49.4/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Llm Projects 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. Llm Projects's score of 49.4/100 is below the category average of 62/100.
This suggests that Llm Projects 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 Llm Projects 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, Llm Projects'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 Llm Projects's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=LLM-projects&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 Llm Projects are strengthening or weakening over time.
Key Takeaways
- Llm Projects has a Trust Score of 49.4/100 (D) and is not yet Nerq Verified.
- Llm Projects has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among uncategorized tools, Llm Projects 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.
What data does Llm Projects collect?
Privacy assessment for Llm Projects is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Llm Projects secure?
Security score: under assessment. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
Full analysis: Llm Projects Security Report
How we calculated this score
Llm Projects's trust score of 49.4/100 (D) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 0 independent dimensions: . Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on May 20, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
Is Llm Projects Safe?
What is Llm Projects's trust score?
What are safer alternatives to Llm Projects?
How often is Llm Projects's safety score updated?
Can I use Llm Projects in a regulated environment?
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.