The Kereva LLM Code Scanner is an innovative static analysis tool tailored for Python applications that leverage Large Language Models (LLMs).
This cutting-edge solution is designed to identify security risks, performance inefficiencies, and vulnerabilities in codebases without requiring execution.
It is particularly useful for developers working on LLM-powered projects, ensuring safer and more efficient implementations of AI technologies.
To install Kereva Scanner:
git clone https://github.com/rbitr/kereva-scanner.git
pip install -r requirements.txt
You can run scans on individual files, Jupyter notebooks, or entire directories using simple commands:
python main.py path/to/file.py
python main.py path/to/directory
python main.py --json --json-dir reports
Advanced options include listing available scanners (--list_scans
), running specific scanners (--scans prompt.subjective_terms
), and enabling comprehensive logging (--comprehensive --log-dir logs
).
Kereva Scanner offers specialized modules:
The tool is invaluable for:
With its robust features and flexible reporting formats, Kereva LLM Code Scanner empowers developers to build secure, efficient, and reliable Python applications powered by LLMs.
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