🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with minimal risks identified. It primarily interacts with an API for market data and lacks any signs of malicious activity.

Low network, shell, obfuscation, and credential risks
Metadata concerns with missing author details and inactive maintainer account

Per-check LLM notes

Network: The network calls observed are typical for fetching data from an API, which aligns with the package's likely function of tracking market data.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows some red flags with missing author details and a new/inactive maintainer account, but there's no evidence of typosquatting or suspicious links.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

try: resp = requests.post(url, json=payload, headers=headers, timeout=8) i
SI cooldown active") r = requests.get(url, params=params, timeout=timeout) meta["status_code"]
hile True: resp = requests.get( url, params={"datasource":
ntract_id}/items/" resp = requests.get( url, params={"datasource": "tranquility"},
try: resp = requests.get(url, headers=headers, params=params, timeout=timeout)
None) resp = requests.get(url, headers=headers, params=params, timeout=timeout)

✓ 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: ppfeufer.de>

✓ 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 name is missing or very short
Author "" 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 aa-markettracker-plugin

Create a web-based mini-app called 'AllianceMarketMonitor' using Django framework that integrates the 'aa-markettracker-plugin' package to track and analyze market data within the Alliance Auth ecosystem. This app will be designed for users of the Alliance Auth platform who wish to monitor their market activities more closely. Here’s a detailed breakdown of what the app should include and how it will utilize the 'aa-markettracker-plugin':

1. **User Authentication**: Users must log in via their Alliance Auth credentials. Utilize Django's authentication system for handling user sessions and permissions.

2. **Dashboard Overview**: Display a dashboard that summarizes recent market transactions, including buy/sell orders, price fluctuations, and total revenue/losses. Use 'aa-markettracker-plugin' to fetch real-time market data from Alliance Auth.

3. **Detailed Transaction Logs**: Provide a feature where users can view detailed logs of all their transactions over a specified period. This includes filtering options based on date, transaction type (buy/sell), and item types. 'aa-markettracker-plugin' will be leveraged to retrieve and display these logs accurately.

4. **Alert System**: Implement an alert system that notifies users via email or in-app notifications when specific conditions are met, such as significant price drops or spikes in demand for certain items. Integrate 'aa-markettracker-plugin' to monitor these conditions and trigger alerts accordingly.

5. **Custom Reports**: Allow users to generate custom reports based on their transaction history. These reports can be exported as PDF or CSV files. 'aa-markettracker-plugin' will provide the necessary data points for generating these reports.

6. **Graphical Analysis**: Incorporate visual elements like charts and graphs to represent trends and patterns in the market data. Libraries such as Matplotlib or Plotly can be used alongside 'aa-markettracker-plugin' to visualize the data effectively.

7. **User Preferences**: Enable users to set preferences for which markets they want to track, preferred currencies, and notification settings. Store these preferences using Django's models and utilize 'aa-markettracker-plugin' to tailor the data retrieval process based on these settings.

8. **Responsive Design**: Ensure the application has a responsive design suitable for both desktop and mobile devices. Use modern CSS frameworks like Bootstrap to achieve this.

9. **Security Measures**: Implement security measures to protect user data, including encryption of sensitive information and protection against common web vulnerabilities.

To start building 'AllianceMarketMonitor', begin by setting up a Django project and installing 'aa-markettracker-plugin'. Then, follow the steps outlined above to develop each feature, ensuring seamless integration with the package's functionalities.