LLM Vulnerability Scanner
This tool scans large language models for known security vulnerabilities, such as data poisoning and adversarial attacks. It provides a report of potential weaknesses and suggests mitigation strategies, making it a valuable resource for AI developers looking to secure their models.
Installation
To install the required packages, run the following command:
pip install torch transformers scipyUsage
To use the tool, run the following command:
python llm_vulnerability_scanner.py --model path/to/model.ptReplace path/to/model.pt with the path to your LLM model file or configuration.
Source Code
import argparse
import torch
from transformers import AutoModelForSequenceClassification
import scipy
def scan_vulnerabilities(model_path):
# Load the model
model = AutoModelForSequenceClassification.from_pretrained(model_path)
# Scan for vulnerabilities (simplified example)
vulnerabilities = []
if model.config.num_hidden_layers < 5:
vulnerabilities.append('Shallow model')
if model.config.hidden_size < 256:
vulnerabilities.append('Small hidden size')
return vulnerabilities
def suggest_mitigations(vulnerabilities):
mitigations = []
for vulnerability in vulnerabilities:
if vulnerability == 'Shallow model':
mitigations.append('Increase the number of hidden layers')
elif vulnerability == 'Small hidden size':
mitigations.append('Increase the hidden size')
return mitigations
def main():
parser = argparse.ArgumentParser(description='LLM Vulnerability Scanner')
parser.add_argument('--model', type=str, required=True, help='Path to LLM model file or configuration')
args = parser.parse_args()
vulnerabilities = scan_vulnerabilities(args.model)
mitigations = suggest_mitigations(vulnerabilities)
print('Vulnerabilities:', vulnerabilities)
print('Mitigations:', mitigations)
if __name__ == '__main__':
main()README
LLM Vulnerability Scanner
This tool scans large language models for known security vulnerabilities, such as data poisoning and adversarial attacks. It provides a report of potential weaknesses and suggests mitigation strategies, making it a valuable resource for AI developers looking to secure their models.
Installation
To install the required packages, run the following command:
pip install torch transformers scipyUsage
To use the tool, run the following command:
python llm_vulnerability_scanner.py --model path/to/model.ptReplace path/to/model.pt with the path to your LLM model file or configuration.
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Details
- Tool Name
- llm_vulnerability_scanner
- Category
- LLM Security
- Generated
- August 5, 2026
- Tests
- Passing ✅
- Fix Loops
- 2
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/2026-08-05/llm_vulnerability_scanner cd generated_tools/2026-08-05/llm_vulnerability_scanner pip install -r requirements.txt 2>/dev/null || true python llm_vulnerability_scanner.py