Instructions to use Xx-Vexento-xX/security-testing-agent-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Xx-Vexento-xX/security-testing-agent-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Xx-Vexento-xX/security-testing-agent-lora") - Notebooks
- Google Colab
- Kaggle
| base_model: meta-llama/Meta-Llama-3.1-8B-Instruct | |
| language: | |
| - en | |
| license: mit | |
| tags: | |
| - lora | |
| - security | |
| - cybersecurity | |
| - peft | |
| # Security Testing Agent — LoRA | |
| Defensive security testing assistant. Analyzes code for vulnerabilities and suggests fixes. | |
| **Base model:** meta-llama/Meta-Llama-3.1-8B-Instruct | |
| ## Load it | |
| ```python | |
| from peft import PeftModel | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") | |
| model = PeftModel.from_pretrained(model, "Xx-Vexento-xX/security-testing-agent-lora") | |
| tokenizer = AutoTokenizer.from_pretrained("Xx-Vexento-xX/security-testing-agent-lora") | |
| ``` | |
| ## Training | |
| - 15 curriculum rounds across Python, JavaScript, Java, Go, PHP, Ruby, TypeScript, Rust, Kotlin, C# | |
| - Vulnerability types: SQL Injection, XSS, CSRF, SSRF, Command Injection, IDOR, XXE, JWT weaknesses, Path Traversal, Prototype Pollution, and more | |
| - RAG-aware: recognizes [REFERENCE CONTEXT] blocks for external knowledge injection | |
| ## Intended use | |
| Authorized defensive security testing of your own code only. | |
| Not for unauthorized access or offensive purposes. |