AI Analysis
Final verdict: SAFE
The package exhibits minimal risks across all categories assessed, with no indications of malicious activities or supply-chain attacks.
- Low risk scores across all categories.
- No network calls or shell executions detected.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating no immediate risk of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which may indicate a new or less active account but does not necessarily suggest malicious intent.
Package Quality Overall: Low (4.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Brief PyPI description (471 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
✦ High
Multiple Contributors
10.0
Active multi-contributor project
12 unique contributor(s) across 100 commits in CybercentreCanada/assemblyline-service-clientActive community — 5 or more distinct contributors
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
Email domain looks legitimate: cyber.gc.ca
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository CybercentreCanada/assemblyline-service-client appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "CCCS Assemblyline development team" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with assemblyline-service-client
Create a Python-based mini-application that serves as a simple interface for interacting with the Assemblyline 4 service using the 'assemblyline-service-client' package. This application will allow users to submit files for analysis, retrieve the results of those analyses, and manage their submissions and results efficiently. Here’s a detailed breakdown of what your application should accomplish: 1. **User Authentication**: Implement a basic authentication system that allows users to log in with their credentials to access the Assemblyline 4 services. 2. **File Submission**: Develop a feature where authenticated users can upload files for analysis. Ensure that the application supports various file types and provides feedback on the submission status. 3. **Analysis Result Retrieval**: Once the analysis is complete, users should be able to view the results through the application. Results should include details such as any detected threats, file hashes, and other relevant information. 4. **Submission Management**: Users should have the ability to manage their submissions. This includes viewing the status of ongoing analyses, canceling pending analyses, and deleting completed submissions. 5. **Result Export**: Provide functionality for users to export analysis results in different formats like CSV or JSON. 6. **Logging and Notifications**: Integrate logging for all actions performed within the application and set up notifications for when analyses complete. **Utilization of 'assemblyline-service-client':** - Use the 'assemblyline-service-client' to interact with the Assemblyline 4 service API endpoints. Specifically, utilize its functions for submitting files, retrieving results, and managing submissions. - Leverage the package’s capabilities to handle authentication tokens and session management securely. - Employ the package’s features for efficient data retrieval and processing of large datasets. Your application should be designed with a user-friendly interface and robust error handling mechanisms. Additionally, ensure that the codebase is well-documented and follows best practices for Python development.
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