Agentlisa est-il sûr ?
Agentlisa — Nerq Trust Score 41.5/100 (Note E). Score basé sur 3 independent trust signals.
Agentlisa est un software tool avec un Nerq Trust Score de 41.5/100 (E), basé sur 3 dimensions de données indépendantes. Maintenance: 0/100. Popularité: 0/100. Données de plusieurs sources publiques dont les registres de paquets, GitHub, NVD, OSV.dev et OpenSSF Scorecard. Dernière mise à jour: n/a. Données lisibles par machine (JSON).
Agentlisa est-il sûr ?
Détail du score de confiance — Agentlisa has a Nerq Trust Score of 41.5/100 (E). Measured across 3 independent trust signals.
Quel est le score de confiance de Agentlisa ?
Agentlisa a un Score de Confiance Nerq de 41.5/100, obtenant la note E. Ce score est basé sur 3 dimensions mesurées indépendamment.
Quels sont les résultats de sécurité clés pour Agentlisa ?
Le signal le plus fort de Agentlisa est maintenance à 0/100. Aucune vulnérabilité connue n'a été détectée.
Qu'est-ce que Agentlisa et qui le maintient ?
| Auteur | 0xb5051843ea5de8815d16c40fdfdeecd8c7afa677 |
| Catégorie | Sécurité |
| Étoiles | 1 |
| Source | https://8004scan.io/agents/agentlisa |
| Protocols | x402 |
Alternatives populaires dans sécurité
What Is Agentlisa?
Agentlisa is a sécurité tool: AgentLISA secures smart contracts at the speed of modern development.. It has 1 GitHub stars. Nerq Trust Score: 42/100 (E).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including sécurité vulnerabilities, maintenance activity, license conformité, and adoption par la communauté.
How Nerq Assesses Agentlisa's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Agentlisa performs in each:
- Maintenance (0/100): Agentlisa 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 documentation, usage examples, and contribution guidelines.
- Community (0/100): Community adoption is limited. Basé sur GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 41.5/100 (E) 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 Agentlisa?
Agentlisa is commonly evaluated by:
- Developers and teams working with sécurité tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Agentlisa's measured signals (maintenance 0/100, documentation 0/100, 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 Agentlisa's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Examiner le/la repository sécurité 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 Agentlisa's dependency tree. - Avis permissions — Understand what access Agentlisa requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Agentlisa 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=AgentLISA - Examiner le/la license — Confirm that Agentlisa'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 sécurité concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Agentlisa
When evaluating whether Agentlisa is safe, consider these category-specific risks:
Understand how Agentlisa processes, stores, and transmits your data. Examiner le/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Agentlisa's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher sécurité risk.
Regularly check for updates to Agentlisa. Sécurité patches and bug fixes are only effective if you're running the latest version.
If Agentlisa 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 Agentlisa's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Agentlisa in violation of its license can expose your organization to legal liability.
Best Practices for Using Agentlisa Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Agentlisa while minimizing risk:
Periodically review how Agentlisa is used in your workflow. Check for unexpected behavior, permissions drift, and conformité with your sécurité policies.
Ensure Agentlisa and all its dependencies are running the latest stable versions to benefit from sécurité patches.
Grant Agentlisa only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Agentlisa's sécurité advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Agentlisa is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Agentlisa
Nerq's signals are one input. In the following situations, evaluate Agentlisa'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 Agentlisa's measured trust score of 41.5/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Agentlisa is suitable for any particular use.
How Agentlisa Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among sécurité tools, the average Trust Score is 67/100. Agentlisa's score of 41.5/100 is below the category average of 67/100.
This suggests that Agentlisa trails behind many comparable sécurité tools. Organizations with strict sécurité 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 modéré 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 Agentlisa 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, Agentlisa'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 sécurité and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Agentlisa's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=AgentLISA&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 — sécurité, maintenance, documentation, conformité, and community — has evolved independently, providing granular visibility into which aspects of Agentlisa are strengthening or weakening over time.
Agentlisa vs Alternatives
In the sécurité category, Agentlisa scores 41.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Agentlisa vs Ciphey — Trust Score: 63.4/100
- Agentlisa vs strix — Trust Score: 64.4/100
- Agentlisa vs SWE-agent — Trust Score: 76.9/100
Points Essentiels
- Agentlisa has a measured Nerq Trust Score of 41.5/100 (E) — a composite of independent signals, not a suitability judgment.
- Among sécurité tools, Agentlisa scores below the category average of 67/100 (a positional measurement relative to peers).
- The individual signals — sécurité, maintenance, documentation, conformité, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Questions fréquentes
Agentlisa est-il sûr ?
Quel est le score de confiance de Agentlisa ?
Quelles sont les alternatives plus sûres à Agentlisa ?
À quelle fréquence le score de sécurité de Agentlisa est-il mis à jour ?
Puis-je utiliser Agentlisa dans un environnement réglementé ?
Voir aussi
Disclaimer: Les scores de confiance Nerq sont des évaluations automatisées basées sur des signaux publiquement disponibles. Ce ne sont pas des recommandations ou des garanties. Effectuez toujours votre propre vérification.