Deadfish Teams é seguro?
Deadfish Teams — Nerq Trust Score 53.4/100 (Grau D). Pontuação baseada em 5 independent trust signals.
Deadfish Teams é um software tool (deadfish pipeline for Claude Code Agent Teams) com um Nerq Trust Score de 53.4/100 (D), com base em 5 dimensões de dados independentes. Segurança: 0/100. Manutenção: 1/100. Popularidade: 0/100. Dados obtidos de múltiplas fontes públicas incluindo registros de pacotes, GitHub, NVD, OSV.dev e OpenSSF Scorecard. Última atualização: n/a. Dados legíveis por máquina (JSON).
Deadfish Teams é seguro?
Detalhamento da Pontuação de Confiança — Deadfish Teams has a Nerq Trust Score of 53.4/100 (D). Measured across 5 independent trust signals.
Qual é a pontuação de confiança de Deadfish Teams?
Deadfish Teams tem uma Pontuação de Confiança Nerq de 53.4/100, obtendo grau D. Esta pontuação é baseada em 5 dimensões medidas independentemente.
Quais são as principais descobertas de segurança de Deadfish Teams?
O sinal mais forte de Deadfish Teams é conformidade com 100/100. Nenhuma vulnerabilidade conhecida foi detectada.
O que é Deadfish Teams e quem o mantém?
| Autor | Fredasterehub |
| Categoria | Coding |
| Source | https://github.com/Fredasterehub/deadfish-teams |
| Frameworks | openai · anthropic |
| Protocols | mcp |
Conformidade Regulatória
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternativas Populares em coding
What Is Deadfish Teams?
Deadfish Teams is a software tool in the coding category: deadfish pipeline for Claude Code Agent Teams. Nerq Trust Score: 53/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including segurança vulnerabilities, manutenção activity, license conformidade, and adoção pela comunidade.
How Nerq Assesses Deadfish Teams's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensões. Here is how Deadfish Teams performs in each:
- Segurança (0/100): Deadfish Teams's segurança posture is poor. This score factors in known CVEs, dependency vulnerabilities, segurança policy presence, and code signing practices.
- Manutenção (1/100): Deadfish Teams 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 documentação, usage examples, and contribution guidelines.
- Compliance (100/100): Deadfish Teams is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Baseado em GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 53.4/100 (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 Deadfish Teams?
Deadfish Teams is commonly evaluated by:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Deadfish Teams's measured signals (segurança 0/100, manutenção 1/100, documentação 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 Deadfish Teams's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Revise o/a repository's segurança policy, open issues, and recent commits for signs of active manutenção.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Deadfish Teams's dependency tree. - Avaliação permissions — Understand what access Deadfish Teams requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Deadfish Teams 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=deadfish-teams - Revise o/a license — Confirm that Deadfish Teams'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 segurança concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Deadfish Teams
When evaluating whether Deadfish Teams is safe, consider these category-specific risks:
Understand how Deadfish Teams processes, stores, and transmits your data. Revise o/a tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Deadfish Teams's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher segurança risk.
Regularly check for updates to Deadfish Teams. Segurança patches and bug fixes are only effective if you're running the latest version.
If Deadfish Teams 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 Deadfish Teams's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Deadfish Teams in violation of its license can expose your organization to legal liability.
Deadfish Teams and the EU AI Act
Deadfish Teams 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 conformidade assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal conformidade.
Best Practices for Using Deadfish Teams Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Deadfish Teams while minimizing risk:
Periodically review how Deadfish Teams is used in your workflow. Check for unexpected behavior, permissions drift, and conformidade with your segurança policies.
Ensure Deadfish Teams and all its dependencies are running the latest stable versions to benefit from segurança patches.
Grant Deadfish Teams only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Deadfish Teams's segurança advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Deadfish Teams is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Deadfish Teams
Nerq's signals are one input. In the following situations, evaluate Deadfish Teams'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 Deadfish Teams's measured trust score of 53.4/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Deadfish Teams is suitable for any particular use.
How Deadfish Teams Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Deadfish Teams's score of 53.4/100 is near the category average of 62/100.
This places Deadfish Teams in line with the typical coding 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 moderado 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 Deadfish Teams 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 manutenção patterns change, Deadfish Teams'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 segurança and quality. Conversely, a downward trend may signal reduced manutenção, growing technical debt, or unresolved vulnerabilities. To track Deadfish Teams's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=deadfish-teams&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 — segurança, manutenção, documentação, conformidade, and community — has evolved independently, providing granular visibility into which aspects of Deadfish Teams are strengthening or weakening over time.
Deadfish Teams vs Alternativas
In the coding category, Deadfish Teams scores 53.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Deadfish Teams vs AutoGPT — Trust Score: 65.3/100
- Deadfish Teams vs ollama — Trust Score: 64.4/100
- Deadfish Teams vs langchain — Trust Score: 77.0/100
Pontos Principais
- Deadfish Teams has a measured Nerq Trust Score of 53.4/100 (D) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Deadfish Teams scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — segurança, manutenção, documentação, conformidade, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Perguntas Frequentes
Deadfish Teams é seguro?
Qual é a pontuação de confiança de Deadfish Teams?
Quais são alternativas mais seguras ao Deadfish Teams?
Com que frequência o score de segurança do Deadfish Teams é atualizado?
Posso usar Deadfish Teams em um ambiente regulado?
Veja também
Disclaimer: As pontuações de confiança da Nerq são avaliações automatizadas baseadas em sinais publicamente disponíveis. Não são endossos ou garantias. Sempre realize sua própria verificação.