Is Langgraph Agents Safe?
Yes, Langgraph Agents is safe to use. Langgraph Agents is a software tool with a Nerq Trust Score of 73.8/100 (B), based on 5 independent data dimensions. It is recommended for use. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Langgraph Agents safe?
YES — Langgraph Agents has a Nerq Trust Score of 73.8/100 (B). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for use — review the full report below for specific considerations.
Trust Score Breakdown
Key Findings
Details
| Author | pareshraut |
| Category | communication |
| Stars | 1 |
| Source | https://github.com/pareshraut/Langgraph-agents |
| Frameworks | langchain · crewai · autogen · openai |
| Protocols | rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 73/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in communication
What Is Langgraph Agents?
Langgraph Agents is a software tool in the communication category: Multi-Agent Chatbot Examples using LangGraph and LangChain for voice support, appointment scheduling, and booking workflows.. It has 1 GitHub stars. Nerq Trust Score: 74/100 (B).
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 Langgraph Agents's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Langgraph Agents performs in each:
- Security (0/100): Langgraph Agents's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Langgraph Agents 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 (73/100): Langgraph Agents 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 73.8/100 (B) 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 Langgraph Agents?
Langgraph Agents is designed for:
- Developers and teams working with communication tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Langgraph Agents 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 Langgraph Agents'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's 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 Langgraph Agents's dependency tree. - Review permissions — Understand what access Langgraph Agents requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Langgraph Agents 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=Langgraph-agents - Review the license — Confirm that Langgraph Agents'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 Langgraph Agents
When evaluating whether Langgraph Agents is safe, consider these category-specific risks:
Understand how Langgraph Agents processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Langgraph Agents's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Langgraph Agents. Security patches and bug fixes are only effective if you're running the latest version.
If Langgraph Agents 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 Langgraph Agents's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Langgraph Agents in violation of its license can expose your organization to legal liability.
Langgraph Agents and the EU AI Act
Langgraph Agents 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 Langgraph Agents Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Langgraph Agents while minimizing risk:
Periodically review how Langgraph Agents is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Langgraph Agents and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Langgraph Agents only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Langgraph Agents's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Langgraph Agents is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Langgraph Agents?
Even well-trusted tools aren't right for every situation. Consider avoiding Langgraph Agents in these scenarios:
- Scenarios where Langgraph Agents'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 Langgraph Agents's trust score of 73.8/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.
How Langgraph Agents Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among communication tools, the average Trust Score is 62/100. Langgraph Agents's score of 73.8/100 is significantly above the category average of 62/100.
This places Langgraph Agents in the top tier of communication 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 Langgraph Agents 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, Langgraph Agents'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 Langgraph Agents's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Langgraph-agents&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 Langgraph Agents are strengthening or weakening over time.
Langgraph Agents vs Alternatives
In the communication category, Langgraph Agents scores 73.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Langgraph Agents vs Real-Time-Voice-Cloning — Trust Score: 71.3/100
- Langgraph Agents vs ChatGPT — Trust Score: 73.8/100
- Langgraph Agents vs jan — Trust Score: 73.8/100
Key Takeaways
- Langgraph Agents has a Trust Score of 73.8/100 (B) and is Nerq Verified.
- Langgraph Agents meets the minimum threshold for production deployment, though monitoring and additional guardrails are recommended.
- Among communication tools, Langgraph Agents 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.