AI Analysis
Final verdict: SAFE
The package appears to be safe with no detected network calls, shell executions, obfuscations, or credential risks. The only minor concern is the author's single package, indicating potential lower maintenance activity.
- No network calls
- No shell execution
- No obfuscation
- No credential harvesting
- Single package by author
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network functionality.
- Shell: No shell execution patterns detected, indicating it does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The author has only one package, which could indicate a new or less active maintainer. No other red flags are present.
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: swarmauri.com
Suspicious Page Links
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.w3.org/1999/02/22-rdf-syntax-ns#
Git Repository History
Repository swarmauri/swarmauri-sdk appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Jacob Stewart" 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 EmbeddedSigner
Create a Python-based desktop application called 'MediaGuard' which allows users to securely embed XMP metadata and sign media files such as images and videos to ensure their authenticity and integrity. The application should provide an intuitive GUI interface built with Tkinter, allowing users to select media files from their local filesystem, input custom XMP metadata fields, and generate digital signatures. Utilize the 'EmbeddedSigner' package to handle the embedding of XMP metadata and signing process seamlessly. Core Features: 1. User-friendly interface for file selection and metadata input. 2. Option to specify XMP metadata fields such as copyright information, author name, creation date, etc. 3. Digital signature generation using Swarmauri plugins integrated through the 'EmbeddedSigner' package. 4. Confirmation message upon successful embedding and signing of metadata. 5. Optional feature to verify the integrity of the signed media file post-embedding. 6. Ability to save the signed and embedded media file with an option to overwrite the original file or save it as a new version. Detailed Steps: 1. Install necessary Python packages including 'EmbeddedSigner', 'Tkinter', and any required dependencies for handling media files. 2. Design a simple but effective GUI layout using Tkinter that includes buttons for file selection, metadata entry fields, and action buttons for signing and verification. 3. Implement functionality within the application to read selected media files and extract existing metadata if available. 4. Integrate 'EmbeddedSigner' to allow for the seamless embedding of user-specified XMP metadata into the chosen media file. 5. Use Swarmauri plugins via 'EmbeddedSigner' to create a digital signature for the media file, ensuring its authenticity. 6. Provide feedback to the user about the status of the operation (success or failure) and offer options for further actions like verification. 7. Ensure all operations are performed securely, with proper error handling and user prompts for important decisions like overwriting files.