Apakah Agentlisa Aman?

Agentlisa — Nerq Trust Score 41.5/100 (Nilai E). Skor berdasarkan 3 independent trust signals.

Agentlisa adalah software tool dengan Skor Kepercayaan Nerq sebesar 41.5/100 (E), based on 3 dimensi data independen. Pemeliharaan: 0/100. Popularitas: 0/100. Data bersumber dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Terakhir diperbarui: n/a. Data yang dapat dibaca mesin (JSON).

Apakah Agentlisa Aman?

Rincian Skor Kepercayaan — Agentlisa has a Nerq Trust Score of 41.5/100 (E). Measured across 3 independent trust signals.

Analisis Keamanan → Laporan Privasi Agentlisa →

Berapa skor kepercayaan Agentlisa?

Agentlisa memiliki Skor Kepercayaan Nerq 41.5/100 dengan nilai E. Skor ini didasarkan pada 3 dimensi yang diukur secara independen.

Pemeliharaan
0
Dokumentasi
0
Popularitas
0

Apa temuan keamanan utama untuk Agentlisa?

Sinyal terkuat Agentlisa adalah pemeliharaan pada 0/100. Tidak ada kerentanan yang diketahui terdeteksi.

⚠Pemeliharaan: 0/100 — aktivitas pemeliharaan rendah
⚠Dokumentasi: 0/100 — dokumentasi terbatas
⚠Popularitas: 0/100 — 1 bintang di erc8004

Apa itu Agentlisa dan siapa yang mengelolanya?

Pembuat0xb5051843ea5de8815d16c40fdfdeecd8c7afa677
KategoriKeamanan
Bintang1
Sumberhttps://8004scan.io/agents/agentlisa
Protocolsx402

Alternatif Populer di keamanan

bee-san/Ciphey
63.4/100 · C
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SWE-agent/SWE-agent
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promptfoo/promptfoo
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TecharoHQ/anubis
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What Is Agentlisa?

Agentlisa is a keamanan 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 keamanan vulnerabilities, pemeliharaan activity, license kepatuhan, and adopsi komunitas.

How Nerq Assesses Agentlisa's Safety

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

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:

How to read the signals: Agentlisa's measured signals (pemeliharaan 0/100, dokumentasi 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:

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

Data handling

Understand how Agentlisa processes, stores, and transmits your data. Tinjau tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency keamanan

Check Agentlisa's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher keamanan risk.

Update frequency

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

Third-party integrations

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.

License and IP kepatuhan

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:

Conduct regular audits

Periodically review how Agentlisa is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.

Keep dependencies updated

Ensure Agentlisa and all its dependencies are running the latest stable versions to benefit from keamanan patches.

Follow least privilege

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

Monitor for keamanan advisories

Subscribe to Agentlisa's keamanan 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 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:

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 keamanan 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 keamanan tools. Organizations with strict keamanan 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 sedang 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 pemeliharaan 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 keamanan and quality. Conversely, a downward trend may signal reduced pemeliharaan, 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 — keamanan, pemeliharaan, dokumentasi, kepatuhan, and community — has evolved independently, providing granular visibility into which aspects of Agentlisa are strengthening or weakening over time.

Agentlisa vs Alternatif

In the keamanan category, Agentlisa scores 41.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Agentlisa Aman?
AgentLISA dengan Skor Kepercayaan Nerq sebesar 41.5/100 (E). Sinyal terkuat: pemeliharaan (0/100). Skor berdasarkan Pemeliharaan (0/100), Popularitas (0/100), Dokumentasi (0/100).
Berapa skor kepercayaan Agentlisa?
AgentLISA: 41.5/100 (E). Skor berdasarkan Pemeliharaan (0/100), Popularitas (0/100), Dokumentasi (0/100). Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=AgentLISA
Apa alternatif yang lebih aman dari Agentlisa?
Dalam kategori Keamanan, higher-rated alternatives include bee-san/Ciphey (63/100), usestrix/strix (64/100), SWE-agent/SWE-agent (77/100). AgentLISA scores 41.5/100.
Seberapa sering skor keamanan Agentlisa diperbarui?
Nerq recomputes Agentlisa's trust score as new data becomes available. Current: 41.5/100 (E). API: GET nerq.ai/v1/preflight?target=AgentLISA
Bisakah saya menggunakan Agentlisa di lingkungan yang diatur?
Agentlisa: 41.5/100 (E). Compliance signals are shown in the breakdown above. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Lihat juga

Disclaimer: Skor kepercayaan Nerq adalah penilaian otomatis berdasarkan sinyal yang tersedia secara publik. Ini bukan rekomendasi atau jaminan. Selalu lakukan verifikasi mandiri Anda sendiri.

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