ASGTransformer
ASGTransformer is a unified, catalog-grounded defensive cybersecurity scenario model. It bundles the semantic encoder, scenario planner, duration planner, professional text renderer, and knowledge catalog in one Hugging Face repository.
Pipeline
Input Text
│
▼
Semantic Encoder
│
▼
Scenario Planner
│
▼
Duration Planner
│
▼
Professional Text Generator
│
▼
Structured Defensive Scenario
Features
- Unified end-to-end defensive scenario generation.
- Knowledge catalog integration for realistic enterprise scenarios.
- Multi-language support.
- Professional scenario rendering.
- Duration estimation.
- Compatible with the Hugging Face Transformers ecosystem.
- CPU and GPU inference support.
- Designed for authorized defensive cybersecurity training.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "wasmdashai/asg-v1"
tokenizer = AutoTokenizer.from_pretrained(
model_id,
trust_remote_code=True,
)
model = AutoModelForCausalLM.from_pretrained(
model_id,
trust_remote_code=True,
torch_dtype="auto",
device_map="auto",
)
result = model.generate_scenario(
tokenizer,
(
"Create an authorized defensive enterprise scenario focused on "
"phishing awareness, credential protection, and response readiness."
),
language="en",
max_new_tokens=384,
do_sample=True,
temperature=0.7,
top_p=0.9,
)
print(result["text"])
print(result["estimated_duration_minutes"])
print(result["scenario_type"])
Intended Use
ASGTransformer is designed exclusively for authorized defensive cybersecurity activities, including:
- Security awareness training
- Tabletop exercises
- Purple team engagements
- Detection engineering
- Incident response preparation
- Security control validation
- Enterprise cyber defense simulations
Repository
GitHub
https://github.com/asgmodel/ASGTransformer
Contact
For technical support, collaboration, or enterprise licensing:
Email: modelasg@gmail.com
License
Please refer to the repository license for usage terms.