AI Analysis
Final verdict: SUSPICIOUS
The package shows low risks in terms of obfuscation and credential harvesting, but the metadata suggests a lack of maintenance and community engagement, raising concerns about its legitimacy and potential for supply-chain attacks.
- Low obfuscation risk
- Low credential risk
- Inactive maintainer and repository
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer seems new or inactive, and the repository has no activity, which raises some suspicion but not enough to be conclusive.
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
}) response = requests.post(url, headers=headers, data=payload) response.raise_f
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: magicfeedback.io>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Francisco Arias" 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 MagicFeedback
Create a Python-based web application that allows users to submit feedback on various products or services, and then uses the 'MagicFeedback' package to enhance the feedback process. The application should have a clean and user-friendly interface, allowing users to provide text feedback, rate their experience on a scale of 1-5 stars, and optionally upload images or videos related to their feedback. Upon submission, the app should utilize the 'MagicFeedback' package to analyze the feedback for sentiment and suggest improvements based on the analysis. Additionally, implement a feature where users can view all their previous submissions and edit them if necessary. Finally, include an admin dashboard where administrators can manage user submissions, view analytics on feedback trends, and export data for further analysis.