Ist Conversationalagent sicher?
Conversationalagent — Nerq Trust Score 55.6/100 (Note D). Bewertung basierend auf 5 independent trust signals.
Conversationalagent ist ein software tool mit einem Nerq-Vertrauenswert von 55.6/100 (D), basierend auf 5 unabhängigen Datendimensionen. Sicherheit: 0/100. Wartung: 1/100. Beliebtheit: 0/100. Daten von mehreren öffentlichen Quellen einschließlich Paketregistern, GitHub, NVD, OSV.dev und OpenSSF Scorecard. Zuletzt aktualisiert: n/a. Maschinenlesbare Daten (JSON).
Ist Conversationalagent sicher?
Vertrauensbewertung im Detail — Conversationalagent has a Nerq Trust Score of 55.6/100 (D). Measured across 5 independent trust signals.
Was ist die Vertrauensbewertung von Conversationalagent?
Conversationalagent hat eine Nerq-Vertrauensbewertung von 55.6/100 und erhält die Note D. Diese Bewertung basiert auf 5 unabhängig gemessenen Dimensionen.
Was sind die wichtigsten Sicherheitsergebnisse für Conversationalagent?
Das stärkste Signal von Conversationalagent ist konformität mit 82/100. Es wurden keine bekannten Schwachstellen erkannt.
Was ist Conversationalagent und wer pflegt es?
| Autor | vlada270 |
| Kategorie | Education |
| Quelle | https://github.com/vlada270/ConversationalAgent |
| Protocols | rest · websocket |
Regulatorische Konformität
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 82/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Beliebte Alternativen in education
What Is Conversationalagent?
Conversationalagent is a software tool in the education category: A Unity-based conversational negotiation agent for training simulations.. Nerq Trust Score: 56/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including Sicherheit vulnerabilities, Wartung activity, license Konformität, and Community-Akzeptanz.
How Nerq Assesses Conversationalagent's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five Dimensionen. Here is how Conversationalagent performs in each:
- Sicherheit (0/100): Conversationalagent's Sicherheit posture is poor. This score factors in known CVEs, dependency vulnerabilities, Sicherheit policy presence, and code signing practices.
- Wartung (1/100): Conversationalagent 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 Dokumentation, usage examples, and contribution guidelines.
- Compliance (82/100): Conversationalagent is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Basierend auf GitHub-Sternen, forks, download counts, and ecosystem integrations.
The overall Trust Score of 55.6/100 (D) 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 Conversationalagent?
Conversationalagent is commonly evaluated by:
- Developers and teams working with education tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Conversationalagent's measured signals (Sicherheit 0/100, Wartung 1/100, Dokumentation 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 Conversationalagent's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Überprüfen Sie das/die repository's Sicherheit policy, open issues, and recent commits for signs of active Wartung.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Conversationalagent's dependency tree. - Bewertung permissions — Understand what access Conversationalagent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Conversationalagent 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=ConversationalAgent - Überprüfen Sie das/die license — Confirm that Conversationalagent'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 Sicherheit concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Conversationalagent
When evaluating whether Conversationalagent is safe, consider these category-specific risks:
Understand how Conversationalagent processes, stores, and transmits your data. Überprüfen Sie das/die tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Conversationalagent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher Sicherheit risk.
Regularly check for updates to Conversationalagent. Sicherheit patches and bug fixes are only effective if you're running the latest version.
If Conversationalagent 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 Conversationalagent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Conversationalagent in violation of its license can expose your organization to legal liability.
Conversationalagent and the EU AI Act
Conversationalagent 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 Konformität assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal Konformität.
Best Practices for Using Conversationalagent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Conversationalagent while minimizing risk:
Periodically review how Conversationalagent is used in your workflow. Check for unexpected behavior, permissions drift, and Konformität with your Sicherheit policies.
Ensure Conversationalagent and all its dependencies are running the latest stable versions to benefit from Sicherheit patches.
Grant Conversationalagent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Conversationalagent's Sicherheit advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Conversationalagent is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Conversationalagent
Nerq's signals are one input. In the following situations, evaluate Conversationalagent's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Conversationalagent's measured trust score of 55.6/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Conversationalagent is suitable for any particular use.
How Conversationalagent Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among education tools, the average Trust Score is 62/100. Conversationalagent's score of 55.6/100 is near the category average of 62/100.
This places Conversationalagent in line with the typical education tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderat 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 Conversationalagent 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 Wartung patterns change, Conversationalagent'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 Sicherheit and quality. Conversely, a downward trend may signal reduced Wartung, growing technical debt, or unresolved vulnerabilities. To track Conversationalagent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=ConversationalAgent&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 — Sicherheit, Wartung, Dokumentation, Konformität, and community — has evolved independently, providing granular visibility into which aspects of Conversationalagent are strengthening or weakening over time.
Conversationalagent vs Alternativen
In the education category, Conversationalagent scores 55.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Conversationalagent vs Mr.-Ranedeer-AI-Tutor — Trust Score: 59.4/100
- Conversationalagent vs hello-agents — Trust Score: 70.1/100
- Conversationalagent vs owl — Trust Score: 60.9/100
Wichtigste Punkte
- Conversationalagent has a measured Nerq Trust Score of 55.6/100 (D) — a composite of independent signals, not a suitability judgment.
- Among education tools, Conversationalagent scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — Sicherheit, Wartung, Dokumentation, Konformität, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Häufig gestellte Fragen
Ist Conversationalagent sicher?
Was ist die Vertrauensbewertung von Conversationalagent?
Was sind sicherere Alternativen zu Conversationalagent?
Wie oft wird die Sicherheitsbewertung von Conversationalagent aktualisiert?
Kann ich Conversationalagent in einer regulierten Umgebung verwenden?
Siehe auch
Disclaimer: Nerq-Vertrauensbewertungen sind automatisierte Bewertungen basierend auf öffentlich verfügbaren Signalen. Sie sind keine Empfehlungen oder Garantien. Führen Sie immer Ihre eigene Sorgfaltsprüfung durch.