README.md

metadata

title: CyberSec Models - Advanced Demo
emoji: 🛡️
colorFrom: red
colorTo: purple
sdk: gradio
sdk_version: 5.50.0
app_file: app.py
pinned: true
license: apache-2.0
tags:
  - cybersecurity
  - iso27001
  - rgpd
  - gdpr
  - compliance
  - rag
  - fine-tuned
  - streaming
models:
  - AYI-NEDJIMI/CyberSec-Assistant-3B
  - AYI-NEDJIMI/ISO27001-Expert-1.5B
  - AYI-NEDJIMI/RGPD-Expert-1.5B
datasets:
  - AYI-NEDJIMI/iso27001
  - AYI-NEDJIMI/rgpd-fr
  - AYI-NEDJIMI/gdpr-en
  - AYI-NEDJIMI/mitre-attack-fr
  - AYI-NEDJIMI/owasp-top10-fr
  - AYI-NEDJIMI/nis2-directive-fr

🛡️ CyberSec AI Models - Advanced Demo

Advanced interactive demo showcasing 3 fine-tuned cybersecurity AI models with RAG and streaming.

Features

💬 Chat Mode

• Select from 3 specialized models
• Enable RAG (Retrieval-Augmented Generation) for context from 80+ datasets
• Streaming responses (token-by-token generation)
• Adjustable temperature and max tokens
• Multi-turn conversations with full history

⚖️ Compare Mode

• Ask the same question to all 3 models simultaneously
• See side-by-side responses
• Identify each model's strengths and specializations
• Compare with or without RAG

🔍 RAG (Retrieval-Augmented Generation)

• Semantic search across 80+ cybersecurity datasets
• Top-k document retrieval using sentence-transformers
• Automatic context injection for more accurate, detailed answers
• Sources include: ISO 27001, RGPD/GDPR, MITRE ATT&CK, OWASP, NIS2, and more

Models

Model	Base	Parameters	Specialty
ISO27001-Expert-1.5B	Qwen2.5-1.5B-Instruct	1.5B	ISO/IEC 27001 ISMS implementation, controls, auditing
RGPD-Expert-1.5B	Qwen2.5-1.5B-Instruct	1.5B	GDPR/RGPD compliance, data protection, DPO guidance
CyberSec-Assistant-3B	Qwen2.5-3B-Instruct	3B	General cybersecurity, pentesting, SOC, compliance

All models are fine-tuned with QLoRA (4-bit quantization) on specialized cybersecurity datasets.

Technical Details

• Fine-tuning method: QLoRA (LoRA rank=64, alpha=128)
• Training data: 80+ bilingual (FR/EN) cybersecurity datasets
• RAG embedding: sentence-transformers/all-MiniLM-L6-v2
• Inference: CPU with float32 (Hugging Face free tier)
• Streaming: TextIteratorStreamer for real-time token generation

Use Cases

• ISO 27001 compliance: Implementation guidance, control selection, audit preparation
• GDPR/RGPD compliance: Data protection requirements, DPIA, breach notification
• Cybersecurity research: MITRE ATT&CK, OWASP, threat hunting, SOC operations
• Training & education: Interactive Q&A for cybersecurity professionals
• Compliance assessment: Compare regulatory frameworks (NIS2, DORA, AI Act)

Performance Notes

⚠️ Running on CPU: First response takes 30-60 seconds while models load. Subsequent responses are faster but still slower than GPU inference.

💡 Tip: The 1.5B models (ISO27001 and RGPD) are more responsive on CPU. The 3B model may be slower.

Author

Ayi NEDJIMI - Senior Offensive Cybersecurity & AI Consultant

• 🌐 Website
• 💼 LinkedIn
• 🐙 GitHub
• 🐦 Twitter/X
• 🤗 HuggingFace Collection

License

Apache 2.0