File size: 2,598 Bytes
4d3c8f5 9b03866 4d3c8f5 374d563 4d3c8f5 9b03866 374d563 4d3c8f5 9b03866 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
title: Security Mcp Tools
emoji: 🛡️
colorFrom: gray
colorTo: pink
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: false
license: mit
tags:
- mcp-server-track
- bandit
- security-scanner
- code-analysis
- modal
short_description: on-demand security analysis for Python code
---
## Bandit Security Scanner (via Modal MCP)
This Gradio application provides an interface to scan Python code for common security vulnerabilities using **Bandit**. The analysis is performed by a Bandit tool running on a [Modal Labs](https://modal.com) Multi-Compute-Platform (MCP) server.
### How to Use
1. **Input Parameters**:
* The input field expects a JSON object.
* This JSON object **must** contain a key named `"code"` whose value is the Python code string you want to analyze.
* An example is pre-filled for convenience:
```json
{
"code": "import subprocess\n\n# Example of a potential security risk with subprocess\nsubprocess.call(\"ls -l\", shell=True)"
}
```
2. **Submit**: Click the "Submit" button.
3. **Output**:
* The application will send the code to the Bandit tool on the Modal MCP server.
* The results of the Bandit analysis will be displayed as a JSON object in the output field. This JSON will typically include:
* `tool`: "bandit"
* `issues`: A list of security issues found, with details like issue text, severity, confidence, line number, and test ID.
* `files_analyzed`: Number of files analyzed (usually 1 for the provided code snippet).
* Any errors encountered during the process or stderr output from Bandit.
### Configuration
For this application to function correctly, the `MODAL_MCP_ENDPOINT` environment variable must be set. This variable should point to your deployed Modal function that handles MCP tool execution (e.g., the `/execute_tool` endpoint).
* Create a `.env` file in the `mcp_deploy` directory (or the root of your Space if deploying to Hugging Face Spaces and it's not automatically picked up from this directory).
* Add the following line to the `.env` file, replacing the placeholder with your actual Modal endpoint URL:
```
MODAL_MCP_ENDPOINT="https://your-username--mcp-server-app-execute-tool.modal.run"
```
If the `MODAL_MCP_ENDPOINT` is not set or is incorrect, the application will display an error message upon submission.
### Note
This application is specifically configured to use the "bandit" tool on the MCP server.
### Future works
Add more security tools and expose them through this mcp server. |