🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is flagged as suspicious due to its minimal maintainer history and lack of an associated GitHub repository, despite having legitimate-looking network calls.

Minimal maintainer history
No associated GitHub repository

Per-check LLM notes

Network: The package makes network calls which could be legitimate, but further investigation is needed to confirm the purpose and destination of these requests.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating low risk of unauthorized data collection.
Metadata: The package has minimal maintainer history and no associated GitHub repository, raising some suspicion, but there are no clear signs of typosquatting or malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

={data_table}' res = urllib.request.Request(url4) try: response = urllib.r
try: response = urllib.request.urlopen(res, timeout=10) html = response.read()
response = requests.get(api_url, headers=headers, timeout=10)
try: response = requests.get(url, timeout=10) result = response.json()
try: response = requests.post(test_url, json=test_data, timeout=10) result =
try: response = requests.post(url, json=data, timeout=10) result = response.j

✓ 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: qq.com

Very short email domain: qq.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "DongYang" 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 Functions-d

Create a mini-application called 'DataSyncBot' that serves as a bridge between your local data processing tasks and cloud-based Hive databases, while also integrating with enterprise messaging and Excel reporting functionalities. This app will streamline data handling processes, allowing users to perform complex operations without leaving their desktop environment. Here’s how it works:

1. **Data Import & Processing**: Users can upload CSV files into the application. The app will use the 'Functions-d' package to process these files according to user-defined rules (e.g., filtering, sorting, aggregation).
2. **Hive Database Interaction**: After processing, the application will automatically sync the cleaned-up data to a specified Hive database using the 'Hive交互' feature of 'Functions-d'.
3. **Notification System**: Once the data has been successfully synced, the app will send a notification via Enterprise WeChat using the '企业微信消息发送' function from 'Functions-d', informing the user about the completion status.
4. **Reporting Tool**: Finally, the application will generate a summary report in Excel format using the 'Excel操作' functionality provided by 'Functions-d'. This report will be sent back to the user as an attachment in the same Enterprise WeChat message.

Suggested Features:
- User-friendly GUI for easy file uploads and parameter settings.
- Detailed logs for each operation performed, stored within the application.
- Error handling and retry mechanisms for failed operations.
- Option to schedule regular data syncs.

How 'Functions-d' is Utilized:
- For data processing tasks, the '数据处理' module of 'Functions-d' will be extensively used to manipulate uploaded CSV files.
- To interact with Hive databases, the 'Hive交互' module will be leveraged to execute SQL-like commands for inserting, updating, or querying data.
- Notifications will be sent through the '企业微信消息发送' module, ensuring real-time updates on the operation status.
- The 'Excel操作' module will handle all aspects of Excel report generation, including formatting and saving files.