🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low individual risk factors but raises concerns due to metadata anomalies. Further investigation is recommended.

Short email domain
Lack of GitHub repository

Per-check LLM notes

Network: No network calls detected, which is normal unless the package is expected to interact with external services like Discord API.
Shell: No shell execution patterns detected, which is typical and indicates no immediate risk from command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting the package does not engage in secret or credential theft.
Metadata: The package shows some red flags such as a short email domain and lack of a GitHub repository, but there's no clear evidence of malice.

🔬 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 score 3.0

Suspicious email domain flags: Very short email domain: me.com

Very short email domain: me.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Aiden Deane" 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 DiscordScraper

Your task is to create a fully-functional mini-application that scrapes public Discord servers for specific user interactions and activity patterns using the 'DiscordScraper' Python package. This application will be particularly useful for analyzing community engagement metrics within Discord communities.

### Application Overview:
- **Name:** Discord Community Insights
- **Purpose:** To analyze user interactions and activities on public Discord servers.
- **Target Audience:** Community managers, social media analysts, and researchers interested in understanding user behavior.

### Core Features:
1. **Server Selection:** Users can input a list of Discord server IDs or URLs to scrape.
2. **Time Frame Selection:** Users can specify a date range for scraping activities.
3. **Interaction Analysis:** Analyze message counts, reactions, mentions, and other interactions.
4. **User Activity Patterns:** Identify active users, inactive users, peak activity times, etc.
5. **Visualization:** Provide visual representations of the data collected (e.g., graphs showing activity over time).
6. **Export Data:** Allow users to export the analyzed data into CSV or JSON formats.

### Utilizing 'DiscordScraper':
- Use the 'DiscordScraper' package to authenticate and connect to the specified Discord servers.
- Utilize the package's API to fetch historical messages, reactions, and other relevant interaction data.
- Ensure that all scraping activities comply with Discord's terms of service and privacy policies.

### Development Steps:
1. Set up your development environment with Python and install the necessary packages including 'DiscordScraper'.
2. Implement a user-friendly interface where users can enter server details and select their desired time frame.
3. Develop the backend logic to interact with 'DiscordScraper', fetching and processing the required data.
4. Create algorithms to analyze the scraped data according to the core features listed above.
5. Integrate visualization libraries such as Matplotlib or Seaborn to display the analysis results.
6. Add functionality to export the analyzed data into different formats.
7. Test the application thoroughly to ensure it works as expected and handles errors gracefully.
8. Document the application, explaining its purpose, features, and how to use it effectively.
9. Optionally, deploy the application online so others can access it easily.

This project will not only demonstrate your ability to work with complex data but also provide valuable insights into the dynamics of online communities.