Lucy 128K은(는) 안전한가요?

Lucy 128K — Nerq Trust Score 59.7/100 (D 등급). 4 independent trust signals 기반 점수.

Lucy 128K 은(는) software tool입니다 Nerq 신뢰 점수 59.7/100 (D), 4개의 독립적으로 측정된 데이터 차원 기반. 유지보수: 0/100. 인기도: 1/100. 패키지 레지스트리, GitHub, NVD, OSV.dev, OpenSSF Scorecard를 포함한 여러 공개 소스에서 수집된 데이터. 마지막 업데이트: n/a. 기계 판독 가능 데이터 (JSON).

Lucy 128K은(는) 안전한가요?

신뢰 점수 세부 정보 — Lucy 128K has a Nerq Trust Score of 59.7/100 (D). Measured across 4 independent trust signals.

보안 분석 → Lucy 128K 개인정보 보고서 →

Lucy 128K의 신뢰 점수는?

Lucy 128K의 Nerq 신뢰 점수는 59.7/100이며 D 등급입니다. 이 점수는 보안, 유지보수, 커뮤니티 채택을 포함한 4개의 독립적으로 측정된 차원을 기반으로 합니다.

규정 준수
87
유지보수
0
문서화
0
인기도
1

Lucy 128K의 주요 보안 발견 사항은?

Lucy 128K의 가장 강한 신호는 규정 준수이며 87/100입니다. 알려진 취약점이 감지되지 않았습니다.

⚠유지보수: 0/100 — 낮은 유지관리 활동
⚠규정 준수: 87/100 — covers 45 of 52 관할권s
⚠문서화: 0/100 — 제한적 문서화
⚠인기도: 1/100 — 109 스타 수: huggingface author2

Lucy 128K은(는) 무엇이며 누가 관리하나요?

개발자Menlo
카테고리Ai Assistant
스타109
출처https://huggingface.co/Menlo/Lucy-128k
Protocolshuggingface_api

규정 준수

EU AI Act Risk ClassNot assessed
Compliance Score87/100
JurisdictionsAssessed across 52 관할권s

AI assistant의 인기 대안

Captain Dackie
49.7/100 · D
erc8004
Neta-Lumina
60.3/100 · C
huggingface_search_ext
gemma-3-12b-it-heretic
58.8/100 · D
huggingface_new
kanana-2-30b-a3b-thinking-2601
59.2/100 · D
huggingface_w2
Dria-Agent-a-7B
57.0/100 · D
huggingface_author2

What Is Lucy 128K?

Lucy 128K is a software tool in the AI assistant category: Menlo/Lucy-128k is an AI assistant.. It has 109 GitHub stars. Nerq Trust Score: 60/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including 보안 vulnerabilities, 유지보수 activity, license 규정 준수, and 커뮤니티 채택.

How Nerq Assesses Lucy 128K's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five 차원. Here is how Lucy 128K performs in each:

The overall Trust Score of 59.7/100 (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 Lucy 128K?

Lucy 128K is commonly evaluated by:

How to read the signals: Lucy 128K's measured signals (유지보수 0/100, 문서화 0/100, community 1/100) 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 Lucy 128K's Safety Yourself

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

  1. Check the source code — 다음을 검토하세요: repository 보안 policy, open issues, and recent commits for signs of active 유지보수.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Lucy 128K's dependency tree.
  3. 리뷰 permissions — Understand what access Lucy 128K requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Lucy 128K 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=Lucy-128k
  6. 다음을 검토하세요: license — Confirm that Lucy 128K'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 보안 concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Lucy 128K

When evaluating whether Lucy 128K is safe, consider these category-specific risks:

Data handling

Understand how Lucy 128K processes, stores, and transmits your data. 다음을 검토하세요: tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency 보안

Check Lucy 128K's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher 보안 risk.

Update frequency

Regularly check for updates to Lucy 128K. 보안 patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Lucy 128K 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 규정 준수

Verify that Lucy 128K's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Lucy 128K in violation of its license can expose your organization to legal liability.

Best Practices for Using Lucy 128K Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Lucy 128K while minimizing risk:

Conduct regular audits

Periodically review how Lucy 128K is used in your workflow. Check for unexpected behavior, permissions drift, and 규정 준수 with your 보안 policies.

Keep dependencies updated

Ensure Lucy 128K and all its dependencies are running the latest stable versions to benefit from 보안 patches.

Follow least privilege

Grant Lucy 128K only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for 보안 advisories

Subscribe to Lucy 128K's 보안 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 Lucy 128K is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant 독립적 Review of Lucy 128K

Nerq's signals are one input. In the following situations, evaluate Lucy 128K's measured signals against your own requirements before making a decision:

For each situation, compare Lucy 128K's measured trust score of 59.7/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Lucy 128K is suitable for any particular use.

How Lucy 128K Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among AI assistant tools, the average Trust Score is 62/100. Lucy 128K's score of 59.7/100 is near the category average of 62/100.

This places Lucy 128K in line with the typical AI assistant 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 보통 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 Lucy 128K 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 유지보수 patterns change, Lucy 128K'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 보안 and quality. Conversely, a downward trend may signal reduced 유지보수, growing technical debt, or unresolved vulnerabilities. To track Lucy 128K's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Lucy-128k&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 — 보안, 유지보수, 문서화, 규정 준수, and community — has evolved independently, providing granular visibility into which aspects of Lucy 128K are strengthening or weakening over time.

Lucy 128K vs 대안

In the AI assistant category, Lucy 128K scores 59.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:

주요 요점

자주 묻는 질문

Lucy 128K은(는) 안전한가요?
Lucy-128k Nerq 신뢰 점수 59.7/100 (D). 가장 강력한 신호: 규정 준수 (87/100). 유지보수 (0/100), 인기도 (1/100), 문서화 (0/100) 기반 점수.
Lucy 128K의 신뢰 점수는?
Lucy-128k: 59.7/100 (D). 유지보수 (0/100), 인기도 (1/100), 문서화 (0/100) 기반 점수. Compliance: 87/100. 새로운 데이터가 제공되면 점수가 업데이트됩니다. API: GET nerq.ai/v1/preflight?target=Lucy-128k
Lucy 128K의 더 안전한 대안은?
Ai Assistant 카테고리에서, higher-rated alternatives include Captain Dackie (50/100), Neta-Lumina (60/100), gemma-3-12b-it-heretic (59/100). Lucy-128k scores 59.7/100.
Lucy 128K의 보안 점수는 얼마나 자주 업데이트되나요?
Nerq recomputes Lucy 128K's trust score as new data becomes available. Current: 59.7/100 (D). API: GET nerq.ai/v1/preflight?target=Lucy-128k
규제 환경에서 Lucy 128K을 사용할 수 있나요?
Lucy 128K: 59.7/100 (D). Compliance: 45 of 52 관할권s. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

참고 항목

Disclaimer: Nerq 신뢰 점수는 공개적으로 사용 가능한 신호를 기반으로 한 자동 평가입니다. 추천이나 보증이 아닙니다. 항상 직접 확인하세요.

분석 및 캐싱을 위해 쿠키를 사용합니다. 개인정보