AI Analysis
Final verdict: SAFE
The package is deemed safe with low risks across most categories, though its low maintenance status warrants caution.
- Low network, shell, obfuscation, and credential risks
- Medium metadata risk due to low maintenance
Per-check LLM notes
- Network: The network calls observed seem to be part of normal API interactions, possibly for data storage or service bundling purposes.
- Shell: No shell execution patterns detected, indicating no direct system command execution risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
- Metadata: The package shows low maintenance and effort, which could indicate potential risks.
Package Quality Overall: Low (4.4/10)
β¦ High
Test Suite
9.0
Test suite present β 1 test file(s) found
Test runner config found: pyproject.toml1 test file(s) detected (e.g. test_basic.py)
β Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (6826 chars)
β Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β Medium
Type Annotations
5.0
Partial type annotation coverage
65 type-annotated function signatures detected in source
β Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked β contributor count unavailable
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
er_api_key response = requests.post( self.storage.bundler_url, data=datat_id """ with httpx.Client(timeout=5.0) as client: resp = client.post(
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
Email domain looks legitimate: agentsystems.ai>
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 agentsystems-notary
Create a digital notary service application using Python that leverages the 'agentsystems-notary' package to cryptographically notarize documents. This application will allow users to upload files, such as PDFs, Word documents, or images, and receive a tamper-proof notarized version of the file along with a cryptographic proof of its integrity. Here are the steps and features your application should include: 1. **User Interface**: Design a simple yet intuitive user interface where users can upload their files. Ensure that the UI supports multiple file types and provides real-time feedback about the file upload process. 2. **File Upload Handling**: Implement a backend that securely handles file uploads from the client side. This includes setting up a server to receive the files and validate their content before processing. 3. **Notarization Process**: Utilize the 'agentsystems-notary' package to notarize the uploaded files. This involves generating a cryptographic hash of the file content, signing it with a private key, and storing both the original file and the signed hash together in a secure manner. 4. **Download Notarized Files**: After notarization, provide users with the ability to download the notarized file and its associated cryptographic proof. Ensure that the downloaded files are clearly marked as notarized. 5. **Verification Tool**: Include a feature within the application that allows users to verify the authenticity of the notarized files. Users should be able to input the file and check if it matches the stored cryptographic proof, ensuring no alterations have been made since notarization. 6. **Security Measures**: Ensure all data transmitted between the client and server is encrypted. Additionally, implement robust security measures to protect against common web vulnerabilities like SQL injection and cross-site scripting (XSS). 7. **Logging and Monitoring**: Set up logging mechanisms to track important events such as file uploads, notarizations, and verifications. Also, implement monitoring tools to keep an eye on the applicationβs performance and any potential security breaches. 8. **Documentation**: Provide comprehensive documentation detailing how to use the application, including setup instructions, API documentation, and guidelines for developers who might want to extend or modify the application. By completing this project, you'll create a powerful tool that ensures the integrity and authenticity of digital documents, demonstrating your skills in cryptography, web development, and Python programming.