Agent2Agentprotocol安全吗?
Agent2Agentprotocol — Nerq 信任评分 62.5/100 (C级). 基于5个信任维度的分析,被评估为总体安全但存在一些担忧。 最后更新:2026-03-31。
请谨慎使用Agent2Agentprotocol。 Agent2Agentprotocol is a software tool Nerq 信任评分为 62.5/100 (C), based on 5 independent data dimensions. 低于推荐阈值 70。 Security: 0/100. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-31. 机器可读数据(JSON).
Agent2Agentprotocol安全吗?
谨慎 — Agent2Agentprotocol Nerq 信任评分为 62.5/100 (C). 信任信号中等,但存在一些值得关注的方面. 适合用于开发环境 — 在生产部署前请查看安全性和维护信号.
Agent2Agentprotocol的信任评分是多少?
Agent2Agentprotocol Nerq 信任评分为 62.5/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
Agent2Agentprotocol的主要安全发现是什么?
Agent2Agentprotocol's strongest signal is 合规性 at 100/100. No 已知漏洞 have been detected. It has not yet reached the Nerq Verified threshold of 70+.
Agent2Agentprotocol是什么,谁在维护它?
| 开发者 | vuutla |
| 类别 | coding |
| 星标 | 1 |
| 来源 | https://github.com/vuutla/Agent2AgentProtocol |
| Frameworks | langchain · openai · a2a |
| Protocols | a2a · rest |
合规性
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
coding中的热门替代品
What Is Agent2Agentprotocol?
Agent2Agentprotocol is a software tool in the coding category: Demonstrates multi-agent collaboration using the Google Agent-to-Agent Protocol.. It has 1 GitHub stars. Nerq 信任评分: 62/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Agent2Agentprotocol's Safety
Nerq's 信任评分 is calculated from 13+ independent signals aggregated into five dimensions. Here is how Agent2Agentprotocol performs in each:
- 安全性 (0/100): Agent2Agentprotocol's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- 维护 (0/100): Agent2Agentprotocol 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 documentation, usage examples, and contribution guidelines.
- Compliance (100/100): Agent2Agentprotocol is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall 信任评分 of 62.5/100 (C) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Agent2Agentprotocol?
Agent2Agentprotocol is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Agent2Agentprotocol is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Agent2Agentprotocol's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for 已知漏洞 in Agent2Agentprotocol's dependency tree. - 评论 permissions — Understand what access Agent2Agentprotocol requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Agent2Agentprotocol 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=Agent2AgentProtocol - 查看 license — Confirm that Agent2Agentprotocol'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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Agent2Agentprotocol
When evaluating whether Agent2Agentprotocol is safe, consider these category-specific risks:
Understand how Agent2Agentprotocol processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Agent2Agentprotocol's dependency tree for 已知漏洞. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Agent2Agentprotocol. Security patches and bug fixes are only effective if you're running the latest version.
If Agent2Agentprotocol 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 Agent2Agentprotocol's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Agent2Agentprotocol in violation of its license can expose your organization to legal liability.
Agent2Agentprotocol and the EU AI Act
Agent2Agentprotocol 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 compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Agent2Agentprotocol Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Agent2Agentprotocol while minimizing risk:
Periodically review how Agent2Agentprotocol is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Agent2Agentprotocol and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Agent2Agentprotocol only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Agent2Agentprotocol's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Agent2Agentprotocol is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Agent2Agentprotocol?
Even promising tools aren't right for every situation. Consider avoiding Agent2Agentprotocol in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Agent2Agentprotocol的信任评分为 62.5/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Agent2Agentprotocol Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average 信任评分 is 62/100. Agent2Agentprotocol's score of 62.5/100 is above the category average of 62/100.
This positions Agent2Agentprotocol favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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.
信任评分 History
Nerq continuously monitors Agent2Agentprotocol and recalculates its 信任评分 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 maintenance patterns change, Agent2Agentprotocol'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 security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Agent2Agentprotocol's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Agent2AgentProtocol&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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Agent2Agentprotocol are strengthening or weakening over time.
Agent2Agentprotocol vs Alternatives
In the coding category, Agent2Agentprotocol scores 62.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Agent2Agentprotocol vs AutoGPT — 信任评分: 74.7/100
- Agent2Agentprotocol vs ollama — 信任评分: 73.8/100
- Agent2Agentprotocol vs langchain — 信任评分: 86.4/100
主要结论
- Agent2Agentprotocol has a 信任评分 of 62.5/100 (C) and is not yet Nerq Verified.
- Agent2Agentprotocol shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Agent2Agentprotocol scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
常见问题
Agent2Agentprotocol可以安全使用吗?
Agent2Agentprotocol's trust score是什么?
Agent2Agentprotocol有哪些更安全的替代品?
How often is Agent2Agentprotocol's safety score updated?
我可以在受监管环境中使用Agent2Agentprotocol吗?
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。