Czy Gogogot jest bezpieczny?
Gogogot — Nerq Trust Score 63.7/100 (Ocena C). Wynik oparty na 4 independent trust signals.
Gogogot to software tool z wynikiem zaufania Nerq 63.7/100 (C), based on 4 niezależnych wymiarów danych. Bezpieczeństwo: 0/100. Konserwacja: 1/100. Popularność: 1/100. Dane pochodzą z wiele źródeł publicznych, w tym rejestry pakietów, GitHub, NVD, OSV.dev i OpenSSF Scorecard. Ostatnia aktualizacja: n/a. Dane odczytywalne maszynowo (JSON).
Czy Gogogot jest bezpieczny?
Szczegóły wyniku zaufania — Gogogot has a Nerq Trust Score of 63.7/100 (C). Measured across 4 independent trust signals.
Jaki jest wynik zaufania Gogogot?
Gogogot ma Nerq Trust Score 63.7/100 z oceną C. Ten wynik opiera się na 4 niezależnie mierzonych wymiarach, w tym bezpieczeństwie, konserwacji i adopcji społeczności.
Jakie są kluczowe ustalenia bezpieczeństwa dla Gogogot?
Najsilniejszy sygnał Gogogot to konserwacja na poziomie 1/100. Nie wykryto znanych luk w zabezpieczeniach.
Czym jest Gogogot i kto go utrzymuje?
| Autor | aspasskiy |
| Kategoria | Agent |
| Gwiazdki | 382 |
| Źródło | https://github.com/aspasskiy/GoGogot |
| Frameworks | openai · anthropic |
| Protocols | rest |
Popularne alternatywy w agent
What Is Gogogot?
Gogogot is a software tool in the agent category: GoGogot is a lightweight self-hosted AI agent in Go.. It has 382 GitHub stars. Nerq Trust Score: 64/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpieczeństwo vulnerabilities, konserwacja activity, license zgodność, and przyjęcie przez społeczność.
How Nerq Assesses Gogogot's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five wymiarów. Here is how Gogogot performs in each:
- Bezpieczeństwo (0/100): Gogogot's bezpieczeństwo posture is poor. This score factors in known CVEs, dependency vulnerabilities, bezpieczeństwo policy presence, and code signing practices.
- Konserwacja (1/100): Gogogot 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 dokumentacja, usage examples, and contribution guidelines.
- Community (1/100): Community adoption is limited. Na podstawie GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 63.7/100 (C) 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 Gogogot?
Gogogot is commonly evaluated by:
- Developers and teams working with agent tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Gogogot's measured signals (bezpieczeństwo 0/100, konserwacja 1/100, dokumentacja 1/100, 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 Gogogot's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Sprawdź repository's bezpieczeństwo policy, open issues, and recent commits for signs of active konserwacja.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Gogogot's dependency tree. - Opinia permissions — Understand what access Gogogot requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Gogogot 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=GoGogot - Sprawdź license — Confirm that Gogogot'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 bezpieczeństwo concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Gogogot
When evaluating whether Gogogot is safe, consider these category-specific risks:
Understand how Gogogot processes, stores, and transmits your data. Sprawdź tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Gogogot's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher bezpieczeństwo risk.
Regularly check for updates to Gogogot. Bezpieczeństwo patches and bug fixes are only effective if you're running the latest version.
If Gogogot 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 Gogogot's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Gogogot in violation of its license can expose your organization to legal liability.
Best Practices for Using Gogogot Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Gogogot while minimizing risk:
Periodically review how Gogogot is used in your workflow. Check for unexpected behavior, permissions drift, and zgodność with your bezpieczeństwo policies.
Ensure Gogogot and all its dependencies are running the latest stable versions to benefit from bezpieczeństwo patches.
Grant Gogogot only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Gogogot's bezpieczeństwo advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Gogogot is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Gogogot
Nerq's signals are one input. In the following situations, evaluate Gogogot'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 Gogogot's measured trust score of 63.7/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Gogogot is suitable for any particular use.
How Gogogot Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among agent tools, the average Trust Score is 62/100. Gogogot's score of 63.7/100 is above the category average of 62/100.
This positions Gogogot favorably among agent tools. While it outperforms the average, there is still room for improvement in certain trust wymiarów.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks umiarkowany 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 Gogogot 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 konserwacja patterns change, Gogogot'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 bezpieczeństwo and quality. Conversely, a downward trend may signal reduced konserwacja, growing technical debt, or unresolved vulnerabilities. To track Gogogot's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=GoGogot&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 — bezpieczeństwo, konserwacja, dokumentacja, zgodność, and community — has evolved independently, providing granular visibility into which aspects of Gogogot are strengthening or weakening over time.
Gogogot vs Alternatywy
In the agent category, Gogogot scores 63.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Gogogot vs pocketpaw — Trust Score: 60.2/100
- Gogogot vs agent-clip — Trust Score: 48.9/100
- Gogogot vs KrillClaw — Trust Score: 66.2/100
Kluczowe wnioski
- Gogogot has a measured Nerq Trust Score of 63.7/100 (C) — a composite of independent signals, not a suitability judgment.
- Among agent tools, Gogogot scores above the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — bezpieczeństwo, konserwacja, dokumentacja, zgodność, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Często zadawane pytania
Czy Gogogot jest bezpieczny?
Jaki jest wynik zaufania Gogogot?
Jakie są bezpieczniejsze alternatywy dla Gogogot?
Jak często aktualizowana jest ocena bezpieczeństwa Gogogot?
Czy mogę używać Gogogot w środowisku regulowanym?
Zobacz także
Disclaimer: Wyniki zaufania Nerq to zautomatyzowane oceny oparte na publicznie dostępnych sygnałach. Nie stanowią rekomendacji ani gwarancji. Zawsze przeprowadzaj własną weryfikację.