🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to potential shell injection vulnerabilities and concerns over maintainer activity and community engagement.

High shell risk due to usage of os.system and subprocess.check_output
Low maintainer activity and community engagement

Per-check LLM notes

Network: No network calls were detected, which is normal for utility packages.
Shell: The use of shell execution commands like os.system and subprocess.check_output can pose risks if not properly sanitized, suggesting potential for unexpected behavior or security vulnerabilities.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has a new or inactive account and the repository lacks community engagement, indicating potential low activity or maintenance issues.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

th.isfile(file_path): os.system(f"code {file_path}") def editLines(file_paths): for file
try: result = subprocess.check_output( ["ssh", remote_target, cmd],
try: output = subprocess.check_output( cmd, shell=True, stderr=subprocess.DEVNULL,
_output( cmd, shell=True, stderr=subprocess.DEVNULL, text=True ).strip()

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: abstractendeavors.com

✓ 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 "putkoff" 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 abstract-utilities

Create a Python-based mini-application named 'DataSanitizer' that leverages the 'abstract-utilities' package to perform several data cleaning and transformation tasks. This application will be particularly useful for developers and data analysts who need to quickly clean up and standardize data before further processing or analysis.

The DataSanitizer app should include the following functionalities:
1. **CSV File Reader**: Implement a function to read CSV files into a Python dictionary where each key represents a column name from the CSV file, and the value is a list of values from that column.
2. **Data Validation**: Use the 'abstract-utilities' package's data comparison utilities to check if all columns in the CSV have the same length, ensuring no missing or extra entries.
3. **String Manipulation**: Provide options to manipulate string data within the CSV. For example, users should be able to remove leading and trailing spaces, convert strings to uppercase or lowercase, or replace specific substrings across all string columns.
4. **JSON Conversion**: Utilize the JSON handling utilities in 'abstract-utilities' to convert the cleaned CSV data into a JSON format. This JSON output should be easily readable and structured according to user preferences.
5. **Math Operations**: Implement basic math operations such as adding a constant to numeric columns or calculating the average value of numeric columns using the math operations provided by 'abstract-utilities'.
6. **Automation Tasks**: Automate repetitive tasks like checking file integrity, performing regular backups of processed data, and sending notifications via email when the process is completed successfully or encounters errors.

For each feature, ensure that the application provides clear user feedback and error messages. Additionally, the application should be well-documented, with instructions on how to install dependencies and run the application. Consider writing unit tests for critical functions to ensure reliability.