Är Langgraph Coding Team säker?
Langgraph Coding Team — Nerq Trust Score 44.7/100 (Betyg E). Baserat på analys av 3 tillitsdimensioner bedöms det som har anmärkningsvärda säkerhetsproblem. Senast uppdaterad: 2026-07-15.
Var försiktig med Langgraph Coding Team. Langgraph Coding Team är en programvara med ett Nerq-förtroendepoäng på 44.7/100 (E), baserat på 3 oberoende datadimensioner. Under Nerqs verifierade tröskel Underhåll: 0/100. Popularitet: 0/100. Data hämtad från flera offentliga källor inklusive paketregister, GitHub, NVD, OSV.dev och OpenSSF Scorecard. Senast uppdaterad: 2026-07-15. Maskinläsbar data (JSON).
Är Langgraph Coding Team säker?
NO — USE WITH CAUTION — Langgraph Coding Team has a Nerq Trust Score of 44.7/100 (E). Har lägre än genomsnittliga förtroendesignaler med betydande luckor in säkerhet, underhåll, or dokumentation. Not recommended for production use without thorough manual review and additional säkerhet measures.
Vad är Langgraph Coding Teams förtroendepoäng?
Langgraph Coding Team har ett Nerq-förtroendepoäng på 44.7/100 med betyget E. Denna poäng baseras på 3 oberoende mätta dimensioner inklusive säkerhet, underhåll och communityanvändning.
Vilka är de viktigaste säkerhetsresultaten för Langgraph Coding Team?
Langgraph Coding Teams starkaste signal är underhåll på 0/100. Inga kända sårbarheter har upptäckts. Har ännu inte nått Nerqs verifieringströskel på 70+.
Vad är Langgraph Coding Team och vem underhåller det?
| Utvecklare | https://github.com/danmas0n/multi-agent-with-mcp |
| Kategori | Coding |
| Stjärnor | 38 |
| Källa | https://github.com/danmas0n/multi-agent-with-mcp |
Populära alternativ inom coding
What Is Langgraph Coding Team?
Langgraph Coding Team is a programvara in the coding category: Create coding agents to generate implementation options.. It has 38 GitHub-stjärnor. Nerq Trust Score: 45/100 (E).
Nerq independently analyzes every programvara, app, and extension across multiple trust signals including säkerhet vulnerabilities, underhåll activity, license regelefterlevnad, and communityanvändning.
How Nerq Assesses Langgraph Coding Team's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensioner. Here is how Langgraph Coding Team performs in each:
- Underhåll (0/100): Langgraph Coding Team is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API dokumentation, usage examples, and contribution guidelines.
- Community (0/100): Community adoption is limited. Baserad på GitHub-stjärnor, forks, download counts, and ecosystem integrations.
The overall Trust Score of 44.7/100 (E) 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 Langgraph Coding Team?
Langgraph Coding Team is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Langgraph Coding Team. The low trust score suggests potential risks in säkerhet, underhåll, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Langgraph Coding Team's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any programvara:
- Check the source code — Granska repository säkerhet policy, open issues, and recent commits for signs of active underhåll.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Langgraph Coding Team's dependency tree. - Recension permissions — Understand what access Langgraph Coding Team requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Langgraph Coding Team 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 Coding Team - Granska license — Confirm that Langgraph Coding Team'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 säkerhet concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Langgraph Coding Team
When evaluating whether Langgraph Coding Team is safe, consider these category-specific risks:
Understand how Langgraph Coding Team processes, stores, and transmits your data. Granska tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Langgraph Coding Team's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher säkerhet risk.
Regularly check for updates to Langgraph Coding Team. Säkerhet patches and bug fixes are only effective if you're running the latest version.
If Langgraph Coding Team 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 Coding Team'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 Coding Team in violation of its license can expose your organization to legal liability.
Best Practices for Using Langgraph Coding Team Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Langgraph Coding Team while minimizing risk:
Periodically review how Langgraph Coding Team is used in your workflow. Check for unexpected behavior, permissions drift, and regelefterlevnad with your säkerhet policies.
Ensure Langgraph Coding Team and all its dependencies are running the latest stable versions to benefit from säkerhet patches.
Grant Langgraph Coding Team only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Langgraph Coding Team's säkerhet advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Langgraph Coding Team is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Langgraph Coding Team?
Even promising tools aren't right for every situation. Consider avoiding Langgraph Coding Team in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional regelefterlevnad review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Langgraph Coding Team's trust score of 44.7/100 meets your organization's risk tolerance. We recommend running a manual säkerhet assessment alongside the automated Nerq score.
How Langgraph Coding Team Compares to Industry Standards
Nerq indexes over 6 million programvaras, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Langgraph Coding Team's score of 44.7/100 is below the category average of 62/100.
This suggests that Langgraph Coding Team trails behind many comparable coding tools. Organizations with strict säkerhet 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 måttlig 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 Coding Team 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 underhåll patterns change, Langgraph Coding Team'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 säkerhet and quality. Conversely, a downward trend may signal reduced underhåll, growing technical debt, or unresolved vulnerabilities. To track Langgraph Coding Team's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=LangGraph Coding Team&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 — säkerhet, underhåll, dokumentation, regelefterlevnad, and community — has evolved independently, providing granular visibility into which aspects of Langgraph Coding Team are strengthening or weakening over time.
Langgraph Coding Team vs Alternativ
In the coding category, Langgraph Coding Team scores 44.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Langgraph Coding Team vs AutoGPT — Trust Score: 61.8/100
- Langgraph Coding Team vs ollama — Trust Score: 56.5/100
- Langgraph Coding Team vs langchain — Trust Score: 69.8/100
Viktigaste slutsatser
- Langgraph Coding Team has a Trust Score of 44.7/100 (E) and is not yet Nerq Verified.
- Langgraph Coding Team has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among coding tools, Langgraph Coding Team 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.
Vanliga frågor
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Vad är Langgraph Coding Teams förtroendepoäng?
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Disclaimer: Nerqs förtroendepoäng är automatiserade bedömningar baserade på offentligt tillgängliga signaler. De utgör inte rekommendationer eller garantier. Gör alltid din egen verifiering.