Average Agent安全吗?
Average Agent — Nerq Trust Score 39.5/100 (E级). 基于5个信任维度的分析,被评估为存在重大安全风险。 最后更新:2026-04-23。
请对Average Agent保持警惕。 Average Agent 是一个software tool Nerq 信任分数 39.5/100(E). 低于 Nerq 验证阈值 数据来源于多个公共来源,包括包注册表、GitHub、NVD、OSV.dev和OpenSSF Scorecard。最后更新:2026-04-23。 机器可读数据(JSON).
Average Agent安全吗?
NO — USE WITH CAUTION — Average Agent has a Nerq Trust Score of 39.5/100 (E). 信任信号低于平均水平,存在重大缺口 in 安全性, 维护, or 文档. Not recommended for production use without thorough manual review and additional 安全性 measures.
Average Agent的信任评分是多少?
Average Agent 的 Nerq 信任分数为 39.5/100,等级为 E。该分数基于 5 个独立测量的维度,包括安全性、维护和社区采用。
Average Agent的主要安全发现是什么?
Average Agent 最强的信号是 整体信任度,为 39.5/100。 未检测到已知漏洞。 尚未达到 Nerq 认证阈值 70+。
Average Agent是什么,谁在维护它?
| 开发者 | 01164e64debfc33df89958123367ffbc5a984ffff64d05cf |
| 类别 | Fetch-Ai |
| 来源 | https://agentverse.ai/agents/average-agent |
fetch-ai中的热门替代品
What Is Average Agent?
Average Agent is a software tool in the fetch-ai category available on agentverse. Nerq Trust Score: 40/100 (E).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including 安全性 vulnerabilities, 维护 activity, license 合规性, and 社区采用.
How Nerq Assesses Average Agent's Safety
Nerq evaluates every software tool across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core 维度: 安全性 (known CVEs, dependency vulnerabilities, 安全性 policies), 维护 (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 司法管辖区s), and Community (stars, forks, downloads, ecosystem integrations).
Average Agent receives an overall Trust Score of 39.5/100 (E), which Nerq considers low. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=Average Agent
Each dimension is weighted according to its importance for the tool's category. For example, 安全性 and 维护 carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Average Agent's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five 维度, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).
Who Should Use Average Agent?
Average Agent is designed for:
- Developers and teams working with fetch-ai tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Average Agent. The low trust score suggests potential risks in 安全性, 维护, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Average Agent's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — 查看 repository 安全性 policy, open issues, and recent commits for signs of active 维护.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Average Agent's dependency tree. - 评论 permissions — Understand what access Average Agent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Average Agent 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=Average Agent - 查看 license — Confirm that Average Agent'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 安全性 concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Average Agent
When evaluating whether Average Agent is safe, consider these category-specific risks:
Understand how Average Agent processes, stores, and transmits your data. 查看 tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Average Agent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher 安全性 risk.
Regularly check for updates to Average Agent. 安全性 patches and bug fixes are only effective if you're running the latest version.
If Average Agent 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 Average Agent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Average Agent in violation of its license can expose your organization to legal liability.
Best Practices for Using Average Agent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Average Agent while minimizing risk:
Periodically review how Average Agent is used in your workflow. Check for unexpected behavior, permissions drift, and 合规性 with your 安全性 policies.
Ensure Average Agent and all its dependencies are running the latest stable versions to benefit from 安全性 patches.
Grant Average Agent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Average Agent's 安全性 advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Average Agent is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Average Agent?
Even promising tools aren't right for every situation. Consider avoiding Average Agent in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional 合规性 review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Average Agent's trust score of 39.5/100 meets your organization's risk tolerance. We recommend running a manual 安全性 assessment alongside the automated Nerq score.
How Average Agent Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among fetch-ai tools, the average Trust Score is 62/100. Average Agent's score of 39.5/100 is below the category average of 62/100.
This suggests that Average Agent trails behind many comparable fetch-ai tools. Organizations with strict 安全性 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 中等 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 Average Agent 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 维护 patterns change, Average Agent'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 安全性 and quality. Conversely, a downward trend may signal reduced 维护, growing technical debt, or unresolved vulnerabilities. To track Average Agent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Average Agent&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 — 安全性, 维护, 文档, 合规性, and community — has evolved independently, providing granular visibility into which aspects of Average Agent are strengthening or weakening over time.
Average Agent vs 替代品
In the fetch-ai category, Average Agent scores 39.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Average Agent vs Finbert Financial Sentiment Agen — Trust Score: 50.8/100
- Average Agent vs SEO Analysis Agent — Trust Score: 39.5/100
- Average Agent vs Grammar Agent — Trust Score: 39.5/100
主要结论
- Average Agent has a Trust Score of 39.5/100 (E) and is not yet Nerq Verified.
- Average Agent has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among fetch-ai tools, Average Agent scores below the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Average Agent收集哪些数据?
隐私 assessment for Average Agent is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Average Agent安全吗?
安全分数: 正在评估中. Review 安全性 practices and consider alternatives with higher 安全性 scores for sensitive use cases.
Nerq 对照 NVD、OSV.dev 和注册表特定漏洞数据库监控此实体 以进行持续安全评估.
完整分析: Average Agent安全报告
我们如何计算此评分
Average Agent's trust score of 39.5/100 (E) 由以下内容计算得出 多个公共来源,包括包注册表、GitHub、NVD、OSV.dev和OpenSSF Scorecard. 该评分反映了 0 独立维度: . 每个维度被同等加权以产生综合信任评分.
Nerq 在 26 个注册表中分析超过 750 万个实体 使用相同的方法,实现实体间的直接比较. 评分会在新数据可用时持续更新.
本页面最近审查于 April 23, 2026. 数据版本: 1.0.
常见问题
Average Agent安全吗?
Average Agent的信任评分是多少?
Average Agent有哪些更安全的替代品?
Average Agent的安全评分多久更新一次?
我可以在受监管的环境中使用Average Agent吗?
另请参阅
Disclaimer: Nerq 信任评分是基于公开信号的自动评估。它们不构成建议或保证。请始终进行自己的验证。