Is Langgraph Agents veilig?

Langgraph Agents — Nerq Trust Score 64.8/100 (C-beoordeling). Score gebaseerd op 5 independent trust signals.

Langgraph Agents is een software tool met een Nerq Vertrouwensscore van 64.8/100 (C), based on 5 onafhankelijke gegevensdimensies. Beveiliging: 0/100. Onderhoud: 1/100. Populariteit: 0/100. Gegevens afkomstig van meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard. Laatst bijgewerkt: n/a. Machineleesbare gegevens (JSON).

Is Langgraph Agents veilig?

Vertrouwensscore details — Langgraph Agents has a Nerq Trust Score of 64.8/100 (C). Measured across 5 independent trust signals.

Beveiligingsanalyse → Langgraph Agents Privacyrapport →

Wat is de vertrouwensscore van Langgraph Agents?

Langgraph Agents heeft een Nerq Trust Score van 64.8/100 met het cijfer C. Deze score is gebaseerd op 5 onafhankelijk gemeten dimensies, waaronder beveiliging, onderhoud en community-adoptie.

Beveiliging
0
Naleving
73
Onderhoud
1
Documentatie
1
Populariteit
0

Wat zijn de belangrijkste beveiligingsbevindingen voor Langgraph Agents?

Het sterkste signaal van Langgraph Agents is naleving met 73/100. Er zijn geen bekende kwetsbaarheden gedetecteerd.

⚠Beveiligingsscore: 0/100 (zwak)
⚠Onderhoud: 1/100 — lage onderhoudsactiviteit
⚠Naleving: 73/100 — covers 37 of 52 jurisdicties
⚠Documentatie: 1/100 — beperkte documentatie
⚠Populariteit: 0/100 — 1 sterren op github

Wat is Langgraph Agents en wie onderhoudt het?

Ontwikkelaarpareshraut
CategorieCommunication
Sterren1
Bronhttps://github.com/pareshraut/Langgraph-agents
Frameworkslangchain · crewai · autogen · openai
Protocolsrest

Naleving van regelgeving

EU AI Act Risk ClassMINIMAL
Compliance Score73/100
JurisdictionsAssessed across 52 jurisdicties

Populaire alternatieven in communication

CorentinJ/Real-Time-Voice-Cloning
56.9/100 · D
github
lencx/ChatGPT
59.4/100 · D
github
janhq/jan
64.4/100 · C
github
2noise/ChatTTS
63.4/100 · C
github
chatboxai/chatbox
64.4/100 · C
github

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: 65/100 (C).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including beveiliging vulnerabilities, onderhoud activity, license naleving, and gemeenschapsacceptatie.

How Nerq Assesses Langgraph Agents's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensies. Here is how Langgraph Agents performs in each:

The overall Trust Score of 64.8/100 (C) is the weighted combination of these measured signals. It is a measurement, not a pass/fail or suitability judgment — weigh the individual signals against your own requirements.

Who Typically Evaluates Langgraph Agents?

Langgraph Agents is commonly evaluated by:

How to read the signals: Langgraph Agents's measured signals (beveiliging 0/100, onderhoud 1/100, documentatie 1/100, community 0/100) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.

How to Verify Langgraph Agents's Safety Yourself

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

  1. Check the source code — Bekijk de repository's beveiliging policy, open issues, and recent commits for signs of active onderhoud.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Langgraph Agents's dependency tree.
  3. Beoordeling permissions — Understand what access Langgraph Agents requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Langgraph Agents 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=Langgraph-agents
  6. Bekijk de 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.
  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 beveiliging 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:

Data handling

Understand how Langgraph Agents processes, stores, and transmits your data. Bekijk de tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency beveiliging

Check Langgraph Agents's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher beveiliging risk.

Update frequency

Regularly check for updates to Langgraph Agents. Beveiliging patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

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.

License and IP naleving

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 naleving assessment covers 52 jurisdicties worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal naleving.

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:

Conduct regular audits

Periodically review how Langgraph Agents is used in your workflow. Check for unexpected behavior, permissions drift, and naleving with your beveiliging policies.

Keep dependencies updated

Ensure Langgraph Agents and all its dependencies are running the latest stable versions to benefit from beveiliging patches.

Follow least privilege

Grant Langgraph Agents only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for beveiliging advisories

Subscribe to Langgraph Agents's beveiliging advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Langgraph Agents is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Langgraph Agents

Nerq's signals are one input. In the following situations, evaluate Langgraph Agents's measured signals against your own requirements before making a decision:

For each situation, compare Langgraph Agents's measured trust score of 64.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Langgraph Agents is suitable for any particular use.

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 64.8/100 is above the category average of 62/100.

This positions Langgraph Agents favorably among communication tools. While it outperforms the average, there is still room for improvement in certain trust dimensies.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks matig 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 onderhoud 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 beveiliging and quality. Conversely, a downward trend may signal reduced onderhoud, 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 — beveiliging, onderhoud, documentatie, naleving, and community — has evolved independently, providing granular visibility into which aspects of Langgraph Agents are strengthening or weakening over time.

Langgraph Agents vs Alternatieven

In the communication category, Langgraph Agents scores 64.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Belangrijkste conclusies

Veelgestelde vragen

Is Langgraph Agents veilig?
Langgraph-agents met een Nerq Vertrouwensscore van 64.8/100 (C). Sterkste signaal: naleving (73/100). Score gebaseerd op Beveiliging (0/100), Onderhoud (1/100), Populariteit (0/100), Documentatie (1/100).
Wat is de vertrouwensscore van Langgraph Agents?
Langgraph-agents: 64.8/100 (C). Score gebaseerd op Beveiliging (0/100), Onderhoud (1/100), Populariteit (0/100), Documentatie (1/100). Compliance: 73/100. Scores worden bijgewerkt wanneer nieuwe data beschikbaar komen. API: GET nerq.ai/v1/preflight?target=Langgraph-agents
Wat zijn veiligere alternatieven voor Langgraph Agents?
In de categorie Communication, higher-rated alternatives include CorentinJ/Real-Time-Voice-Cloning (57/100), lencx/ChatGPT (59/100), janhq/jan (64/100). Langgraph-agents scores 64.8/100.
Hoe vaak wordt de beveiligingsscore van Langgraph Agents bijgewerkt?
Nerq recomputes Langgraph Agents's trust score as new data becomes available. Current: 64.8/100 (C). API: GET nerq.ai/v1/preflight?target=Langgraph-agents
Kan ik Langgraph Agents gebruiken in een gereguleerde omgeving?
Langgraph Agents: 64.8/100 (C). Compliance: 37 of 52 jurisdicties. EU AI Act compliant. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Zie ook

Disclaimer: Nerq-vertrouwensscores zijn geautomatiseerde beoordelingen op basis van openbaar beschikbare signalen. Ze vormen geen aanbeveling of garantie. Voer altijd uw eigen verificatie uit.

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