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
Create README.md
Browse files---
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
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
## Intended use
Authorized defensive security testing of your own code only.