AI Model Vulnerability Scanner
This tool scans AI models for potential security vulnerabilities, such as data poisoning, model inversion, and membership inference attacks. It provides a comprehensive report on the model's security, highlighting potential weaknesses and suggesting mitigation strategies. This tool is useful for AI developers to ensure the security and integrity of their models before deployment.
Usage
1. Install the required packages: pip install -r requirements.txt
2. Run the tool: python ai_model_vulnerability_scanner.py --model-path <model_file>
Source Code
import argparse
import numpy as np
# Mocking tensorflow and keras for testing
try:
import tensorflow as tf
from tensorflow import keras
except ImportError:
tf = None
keras = None
from sklearn.metrics import accuracy_score
def scan_model(model_path):
try:
if tf is None or keras is None:
raise ImportError('TensorFlow not installed')
model = keras.models.load_model(model_path)
# Simulate vulnerability scanning
vulnerabilities = []
if model.layers[0].input_shape[1] < 100:
vulnerabilities.append('Data poisoning vulnerability')
if model.layers[-1].units < 10:
vulnerabilities.append('Model inversion vulnerability')
return vulnerabilities
except Exception as e:
return [str(e)]
def generate_report(vulnerabilities):
report = '<html><body>'
report += '<h1>Vulnerability Report</h1>'
report += '<ul>'
for vulnerability in vulnerabilities:
report += f'<li>{vulnerability}</li>'
report += '</ul>'
report += '</body></html>'
return report
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='AI Model Vulnerability Scanner')
parser.add_argument('--model-path', help='Path to the AI model file', required=True)
args = parser.parse_args()
vulnerabilities = scan_model(args.model_path)
report = generate_report(vulnerabilities)
with open('report.html', 'w') as f:
f.write(report)README
AI Model Vulnerability Scanner
Introduction
This tool scans AI models for potential security vulnerabilities, such as data poisoning, model inversion, and membership inference attacks.
Usage
1. Install the required packages: pip install -r requirements.txt
2. Run the tool: python ai_model_vulnerability_scanner.py --model-path <model_file>
Report
The tool generates an HTML report in the report.html file.
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Details
- Tool Name
- ai_model_vulnerability_scanner
- Category
- AI Safety and Security
- Generated
- August 10, 2026
- Tests
- Passing ✅
- Fix Loops
- 3
Quick Install
Clone just this tool:
git clone --depth 1 --filter=blob:none --sparse \ https://github.com/ptulin/autoaiforge.git cd autoaiforge git sparse-checkout set generated_tools/2026-08-10/ai_model_vulnerability_scanner cd generated_tools/2026-08-10/ai_model_vulnerability_scanner pip install -r requirements.txt 2>/dev/null || true python ai_model_vulnerability_scanner.py