AI Analysis
Final verdict: SAFE
The package appears to be safe with no detected risks related to network calls, shell execution, obfuscation, or credential harvesting. However, the metadata suggests a potentially new or less active developer.
- Low risk scores across all categories.
- Only one package from the author, lacking PyPI classifiers.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package is designed to interact with external services like S3.
- Shell: No shell execution patterns detected, which is expected and safe.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author has only one package and lacks PyPI classifiers, indicating potential low effort or new/inactive account.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository yaogdu/AgentLedger appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "AgentLedger Contributors" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with agentledger-s3
Create a fully-functional mini-application called 'DataBackupManager' that leverages the 'agentledger-s3' package to manage data backups in an S3-compatible storage system. This application should allow users to upload, download, list, and delete files stored in their chosen S3-compatible BlobStore. Additionally, it should provide functionalities to create, update, and delete backup jobs that define which directories on the local machine should be backed up to the cloud storage and at what intervals. Key Features: 1. User Authentication: Implement basic user authentication to ensure only authorized users can access and modify their backup jobs and files. 2. Backup Job Management: Users should be able to define backup jobs specifying source directories, destination paths in the BlobStore, and backup frequency. 3. File Operations: Provide an intuitive interface for uploading, downloading, listing, and deleting files from the BlobStore. 4. Scheduled Backups: Use cron-like scheduling to automatically execute backup jobs according to user-defined schedules. 5. Versioning Support: Enable versioning of backups so users can restore previous versions of their data if needed. 6. Logging and Monitoring: Implement logging for all operations performed through the application and provide a monitoring dashboard showing recent activities and status of backup jobs. How 'agentledger-s3' is Utilized: - For connecting to the S3-compatible BlobStore, utilize the 'agentledger-s3' package's core functionality to authenticate and interact with the storage service efficiently. - Use the package's methods for performing CRUD (Create, Read, Update, Delete) operations on files within the BlobStore, ensuring secure and reliable data transfer. - Leverage any additional features provided by the 'agentledger-s3' package, such as support for multipart uploads or advanced metadata handling, to enhance the robustness and scalability of your application.