AI Analysis
The package shows minimal risks across all categories checked. It has a moderate metadata risk due to being newly created but lacks any other significant red flags such as obfuscation, credential harvesting, or shell execution.
- moderate metadata risk
- newly created package
Per-check LLM notes
- Network: The network call pattern is typical for a SDK that likely communicates with an API server to perform its functions.
- Shell: No shell execution patterns detected, indicating no immediate risk from this aspect.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package appears to be newly created with limited activity and no suspicious links or domains detected.
Heuristic Checks
Found 1 network call pattern(s)
meout self._session = requests.Session() self._session.headers.update({ "Author
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository agentauditAI/AgentAudit appears legitimate
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "agentauditAI" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini-application named 'AIComplianceMonitor' that leverages the 'agentauditai-sdk' package to ensure compliance with the European Union's AI Act for AI agents. This application will serve as a tool for developers to register their AI agents, log immutable audit trails, report incidents, and perform post-market monitoring. Here’s a detailed breakdown of the project steps and features: 1. **Project Setup**: Begin by setting up a new Python environment and installing the 'agentauditai-sdk'. Ensure you have access to an Ethereum testnet for on-chain operations. 2. **User Registration**: Develop a feature where users can register their AI agents. Utilize the 'agentauditai-sdk' to create an immutable KYA (Know Your Agent) registration process on the blockchain. 3. **Audit Logs**: Implement a system that automatically logs all actions performed by the AI agent onto the blockchain using the 'agentauditai-sdk'. These logs should be immutable and timestamped. 4. **Incident Reporting**: Create a mechanism for users to report any incidents related to their AI agents. Use the 'agentauditai-sdk' to ensure these reports are securely stored and accessible on the blockchain. 5. **Post-Market Monitoring**: Build functionality that allows for continuous monitoring of AI agent performance post-deployment. Integrate 'agentauditai-sdk' features to collect and analyze data from the blockchain for compliance checks. 6. **Dashboard**: Design a user-friendly dashboard where users can view their AI agent's compliance status, audit logs, and incident reports. Use the 'agentauditai-sdk' APIs to fetch and display relevant data. 7. **Security and Privacy**: Ensure that all data handling complies with GDPR and other relevant privacy laws. Leverage the security features provided by 'agentauditai-sdk' to protect user information. 8. **Documentation and Testing**: Provide comprehensive documentation and thorough testing for the application, including integration tests with 'agentauditai-sdk'. By following these steps and utilizing the 'agentauditai-sdk', your application will not only streamline compliance processes but also enhance transparency and accountability for AI agents.
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