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---
Derivative work notice: This model is a fine-tuned derivative of
Qwen/Qwen2.5-1.5B-Instruct (https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct),
released under the Apache License, Version 2.0. Modifications: LoRA
fine-tuning and weight fusion for structured PWNISMS threat-model JSON output.

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---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- chat
- mlx
- gguf
- llama.cpp
- ollama
- security
- threat-modeling
- structured-output
- json
library_name: mlx
---
# PWNISMS-Threat-Model-Structured
Fused [MLX](https://github.com/ml-explore/mlx) and GGUF releases of **Qwen2.5-1.5B-Instruct** fine-tuned to emit **valid JSON** matching a **PWNISMS** structured threat model (seven domains: Product, Workload, Network, IAM, Secrets, Monitoring, SupplyChain), with optional STRIDE cross-tags and concrete mitigations.
## Base Model And License
- **Base:** [`Qwen/Qwen2.5-1.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) (Apache-2.0).
- This release is a **derivative work** of the base model. The base license applies; retain notices and state modifications as required by Apache-2.0. See [`LICENSE`](LICENSE).
## Training Summary
- **Method:** LoRA fine-tuning on MLX (`mlx_lm`), then fused into a single checkpoint.
- **Base:** `Qwen/Qwen2.5-1.5B-Instruct`
- **LoRA:** rank 8, scale 20, 16 layers, max sequence length 10240, 1200 iterations.
- **GGUF conversion:** llama.cpp `convert_hf_to_gguf.py`, plus Q4_K_M quantization with `llama-quantize`.
## Output Contract
The model is trained to answer with **JSON only** for a chat shaped as:
- **System:** PWNISMS architect instructions requiring all seven domains, concrete mitigations, and scenario-grounded components.
- **User:** Markdown system description.
The expected object is defined by the included [`threat_model_schema.json`](threat_model_schema.json).
**Minimum bar:** at least **5** threats, exactly **7** `pwnisms_coverage` entries, and each threat id must appear under its domains `threat_ids`.
## Limitations And Evaluation
Internal pulse check (n=20 held-out style samples, local script): **16/20** parse as JSON, **12/20** pass full Pydantic validation, and **12/20** cover all seven domains with the schema. Real deployments should validate outputs with Pydantic or JSON Schema and never treat this model as a substitute for expert review.
Long scenarios can need **up to ~12k output tokens**; lower caps may truncate JSON.
## Load And Generate (MLX)
```python
from mlx_lm import load, generate
model, tokenizer = load("abhaybhargav/PWNISMS-Threat-Model-Structured")
system = """You are a senior security architect. Produce a PWNISMS threat model for the described system.
Address all seven PWNISMS domains: Product, Workload, Network, IAM, Secrets, Monitoring, SupplyChain.
Mitigations must reference concrete technologies, configurations, or processes.
Return only valid JSON matching the required schema."""
user = open("scenario.md").read()
messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
text = generate(model, tokenizer, prompt=prompt, max_tokens=12000, verbose=False)
print(text)
```
## Load And Generate (GGUF / llama.cpp)
Recommended default:
- `PWNISMS-Threat-Model-Structured-Q4_K_M.gguf` (~940MB): broad local compatibility, much smaller than F16.
Reference precision:
- `PWNISMS-Threat-Model-Structured-F16.gguf` (~2.9GB): F16 GGUF export.
Example with llama.cpp:
```bash
llama-cli \
-m PWNISMS-Threat-Model-Structured-Q4_K_M.gguf \
--ctx-size 12000 \
--temp 0.2 \
-p '<|im_start|>system
You are a senior security architect. Produce a PWNISMS threat model for the described system.
Address all seven PWNISMS domains: Product, Workload, Network, IAM, Secrets, Monitoring, SupplyChain.
Mitigations must reference concrete technologies, configurations, or processes.
Return only valid JSON matching the required schema.<|im_end|>
<|im_start|>user
<paste the system scenario markdown here><|im_end|>
<|im_start|>assistant
'
```
## Ollama
Create a `Modelfile` next to the downloaded GGUF:
```text
FROM ./PWNISMS-Threat-Model-Structured-Q4_K_M.gguf
PARAMETER temperature 0.2
PARAMETER num_ctx 12000
TEMPLATE """{{ .Prompt }}"""
```
Then run:
```bash
ollama create pwnisms-threat-model-structured -f Modelfile
ollama run pwnisms-threat-model-structured
```
## Files
| File | Purpose |
|------|---------|
| `model.safetensors` | Fused MLX/HF-format weights |
| `PWNISMS-Threat-Model-Structured-Q4_K_M.gguf` | Quantized GGUF for llama.cpp/Ollama/local tools |
| `PWNISMS-Threat-Model-Structured-F16.gguf` | F16 GGUF reference export |
| `config.json`, `tokenizer.json`, `tokenizer_config.json`, `chat_template.jinja` | Model + tokenizer |
| `threat_model_schema.json` | JSON Schema for outputs |
| `examples/sample_scenario.md` | Tiny example input shape |
## Intended Use
This model is intended to assist application and security architects in drafting structured PWNISMS threat models from system descriptions. It is not a formal risk decision engine and should be reviewed by humans before use in production assurance, audit, or compliance workflows.

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{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0]['role'] == 'system' %}
{{- messages[0]['content'] }}
{%- else %}
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
{%- endif %}
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- if message.content %}
{{- '\n' + message.content }}
{%- endif %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

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{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"eos_token_id": [
151645,
151643
],
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"max_position_embeddings": 32768,
"max_window_layers": 21,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"rms_norm_eps": 1e-06,
"rope_theta": 1000000.0,
"sliding_window": 32768,
"tie_word_embeddings": true,
"torch_dtype": "bfloat16",
"transformers_version": "4.43.1",
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 151936
}

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# Example scenario (excerpt)
Use a full system description in markdown: components, data flows, users, compliance, and trust boundaries. The model responds with a single JSON object (no code fences) matching `threat_model_schema.json`.
This file is illustrative; replace with your own scenario text.
## Sample title
A minimal API service that issues OAuth tokens to internal services behind mTLS.
## Application Information
- REST API on AWS Lambda behind API Gateway
- Tokens signed with an AWS KMS key; rotation weekly
- Audit logs to CloudWatch
## Users
- Internal service principals only (no public internet clients)
## Compliance
- SOC 2

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{
"bos_token_id": 151643,
"pad_token_id": 151643,
"do_sample": true,
"eos_token_id": [
151645,
151643
],
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_p": 0.8,
"top_k": 20,
"transformers_version": "4.37.0"
}

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"type": "string"
},
"classification": {
"$ref": "#/$defs/DataClassification"
},
"location": {
"description": "Where stored/processed, e.g. 'RDS PostgreSQL', 'S3 bucket prod-lab-pdfs'.",
"title": "Location",
"type": "string"
}
},
"required": [
"id",
"name",
"description",
"classification",
"location"
],
"title": "Asset",
"type": "object"
},
"DataClassification": {
"enum": [
"Public",
"Internal",
"Confidential",
"Restricted"
],
"title": "DataClassification",
"type": "string"
},
"DataFlow": {
"properties": {
"id": {
"description": "Unique identifier, e.g. 'DF-01'.",
"title": "Id",
"type": "string"
},
"source": {
"description": "Originating component.",
"title": "Source",
"type": "string"
},
"destination": {
"description": "Receiving component.",
"title": "Destination",
"type": "string"
},
"data_classification": {
"$ref": "#/$defs/DataClassification"
},
"protocol": {
"description": "Concrete protocol, e.g. 'HTTPS', 'MQTT/TLS', 'gRPC', 'AMQP'.",
"title": "Protocol",
"type": "string"
},
"crosses_boundary": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "ID of the TrustBoundary this flow crosses, if any.",
"title": "Crosses Boundary"
}
},
"required": [
"id",
"source",
"destination",
"data_classification",
"protocol"
],
"title": "DataFlow",
"type": "object"
},
"Mitigation": {
"properties": {
"description": {
"description": "Specific, actionable control. Must reference a concrete technology, configuration, or process \u2014 not a generic category. Bad: 'use encryption'. Good: 'enable TLS 1.3 with mutual auth on the MQTT broker using AWS IoT Core device certificates'.",
"minLength": 15,
"title": "Description",
"type": "string"
},
"type": {
"$ref": "#/$defs/MitigationType"
},
"priority": {
"$ref": "#/$defs/MitigationPriority"
},
"references": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional references: OWASP/NIST/CIS control IDs or doc links.",
"title": "References"
}
},
"required": [
"description",
"type",
"priority"
],
"title": "Mitigation",
"type": "object"
},
"MitigationPriority": {
"enum": [
"P0",
"P1",
"P2"
],
"title": "MitigationPriority",
"type": "string"
},
"MitigationType": {
"enum": [
"Preventive",
"Detective",
"Corrective",
"Deterrent"
],
"title": "MitigationType",
"type": "string"
},
"PwnismsDomain": {
"description": "The seven PWNISMS domains. All seven must be addressed in every model.",
"enum": [
"Product",
"Workload",
"Network",
"IAM",
"Secrets",
"Monitoring",
"SupplyChain"
],
"title": "PwnismsDomain",
"type": "string"
},
"PwnismsDomainCoverage": {
"properties": {
"domain": {
"$ref": "#/$defs/PwnismsDomain"
},
"addressed": {
"description": "True if threats in this domain were identified; False if N/A.",
"title": "Addressed",
"type": "boolean"
},
"threat_ids": {
"description": "IDs of threats belonging to this domain (if addressed=True).",
"items": {
"type": "string"
},
"title": "Threat Ids",
"type": "array"
},
"justification_if_not_applicable": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Required when addressed=False. Must explain why the domain is not relevant to this specific system. Never leave domains unaddressed without justification.",
"title": "Justification If Not Applicable"
}
},
"required": [
"domain",
"addressed"
],
"title": "PwnismsDomainCoverage",
"type": "object"
},
"RiskLevel": {
"enum": [
"High",
"Medium",
"Low"
],
"title": "RiskLevel",
"type": "string"
},
"Scope": {
"properties": {
"in_scope": {
"description": "Components, flows, or features being threat-modeled.",
"items": {
"type": "string"
},
"minItems": 1,
"title": "In Scope",
"type": "array"
},
"out_of_scope": {
"description": "Explicitly excluded elements.",
"items": {
"type": "string"
},
"title": "Out Of Scope",
"type": "array"
},
"assumptions": {
"description": "Assumptions that, if invalidated, would change the model.",
"items": {
"type": "string"
},
"title": "Assumptions",
"type": "array"
}
},
"required": [
"in_scope"
],
"title": "Scope",
"type": "object"
},
"SecurityObjective": {
"enum": [
"Confidentiality",
"Integrity",
"Availability",
"Authenticity",
"NonRepudiation",
"Authorization",
"Privacy"
],
"title": "SecurityObjective",
"type": "string"
},
"StrideCategory": {
"description": "Optional STRIDE cross-categorization per threat.",
"enum": [
"Spoofing",
"Tampering",
"Repudiation",
"InformationDisclosure",
"DenialOfService",
"ElevationOfPrivilege"
],
"title": "StrideCategory",
"type": "string"
},
"Threat": {
"properties": {
"id": {
"description": "Unique identifier, e.g. 'T-01'.",
"title": "Id",
"type": "string"
},
"title": {
"description": "Short title of the threat.",
"maxLength": 120,
"title": "Title",
"type": "string"
},
"pwnisms_domain": {
"$ref": "#/$defs/PwnismsDomain",
"description": "Primary PWNISMS domain this threat belongs to."
},
"stride_category": {
"anyOf": [
{
"$ref": "#/$defs/StrideCategory"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional STRIDE cross-categorization for this threat."
},
"affected_component": {
"description": "The component under threat. Must be a component that appears in or is directly implied by the input system description \u2014 do not invent components not present in the scenario.",
"title": "Affected Component",
"type": "string"
},
"affected_asset_ids": {
"description": "IDs of assets impacted (referencing Asset.id).",
"items": {
"type": "string"
},
"title": "Affected Asset Ids",
"type": "array"
},
"description": {
"description": "What could go wrong. 2\u20134 sentences, concrete and specific.",
"minLength": 50,
"title": "Description",
"type": "string"
},
"attack_vector": {
"description": "How an attacker realistically exploits this threat.",
"minLength": 20,
"title": "Attack Vector",
"type": "string"
},
"preconditions": {
"description": "What must be true for this threat to be exploitable.",
"items": {
"type": "string"
},
"title": "Preconditions",
"type": "array"
},
"security_objectives_violated": {
"items": {
"$ref": "#/$defs/SecurityObjective"
},
"minItems": 1,
"title": "Security Objectives Violated",
"type": "array"
},
"likelihood": {
"$ref": "#/$defs/RiskLevel"
},
"likelihood_rationale": {
"minLength": 20,
"title": "Likelihood Rationale",
"type": "string"
},
"impact": {
"$ref": "#/$defs/RiskLevel"
},
"impact_rationale": {
"minLength": 20,
"title": "Impact Rationale",
"type": "string"
},
"mitigations": {
"description": "At least one concrete mitigation per threat.",
"items": {
"$ref": "#/$defs/Mitigation"
},
"minItems": 1,
"title": "Mitigations",
"type": "array"
},
"residual_risk": {
"description": "Risk that remains after mitigations are applied.",
"title": "Residual Risk",
"type": "string"
}
},
"required": [
"id",
"title",
"pwnisms_domain",
"affected_component",
"description",
"attack_vector",
"security_objectives_violated",
"likelihood",
"likelihood_rationale",
"impact",
"impact_rationale",
"mitigations",
"residual_risk"
],
"title": "Threat",
"type": "object"
},
"TrustBoundary": {
"properties": {
"id": {
"description": "Unique identifier, e.g. 'TB-01'.",
"title": "Id",
"type": "string"
},
"name": {
"description": "Short name, e.g. 'Internet to API Gateway'.",
"title": "Name",
"type": "string"
},
"between": {
"description": "The two sides of the boundary: [outside, inside].",
"items": {
"type": "string"
},
"maxItems": 2,
"minItems": 2,
"title": "Between",
"type": "array"
},
"description": {
"title": "Description",
"type": "string"
}
},
"required": [
"id",
"name",
"between",
"description"
],
"title": "TrustBoundary",
"type": "object"
}
},
"description": "A PWNISMS threat model for the system described in the input scenario.\n\nFill every field. Every one of the seven PWNISMS domains must appear in\n`pwnisms_coverage` \u2014 either with threats, or with an explicit N/A\njustification. No silent omissions.",
"properties": {
"system_summary": {
"description": "2\u20134 sentence summary of the system being threat-modeled.",
"maxLength": 800,
"minLength": 50,
"title": "System Summary",
"type": "string"
},
"scope": {
"$ref": "#/$defs/Scope"
},
"assets": {
"description": "Named information/system assets worth protecting.",
"items": {
"$ref": "#/$defs/Asset"
},
"title": "Assets",
"type": "array"
},
"trust_boundaries": {
"description": "At least one trust boundary must be identified.",
"items": {
"$ref": "#/$defs/TrustBoundary"
},
"minItems": 1,
"title": "Trust Boundaries",
"type": "array"
},
"data_flows": {
"description": "Key data flows, especially those crossing trust boundaries.",
"items": {
"$ref": "#/$defs/DataFlow"
},
"title": "Data Flows",
"type": "array"
},
"threats": {
"description": "Identified threats. Typical count: 8\u201325 depending on system complexity. Each threat must be tagged with a PWNISMS domain.",
"items": {
"$ref": "#/$defs/Threat"
},
"minItems": 5,
"title": "Threats",
"type": "array"
},
"pwnisms_coverage": {
"description": "One entry per PWNISMS domain. All seven domains must be present. Domains without identified threats must carry an explicit justification for why they do not apply to this system.",
"items": {
"$ref": "#/$defs/PwnismsDomainCoverage"
},
"title": "Pwnisms Coverage",
"type": "array"
},
"open_questions": {
"description": "Ambiguities or missing information in the scenario that would materially affect the threat model if resolved.",
"items": {
"type": "string"
},
"title": "Open Questions",
"type": "array"
}
},
"required": [
"system_summary",
"scope",
"trust_boundaries",
"threats",
"pwnisms_coverage"
],
"title": "ThreatModel",
"type": "object"
}

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"backend": "tokenizers",
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"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"extra_special_tokens": [
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"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
"<|quad_start|>",
"<|quad_end|>",
"<|vision_start|>",
"<|vision_end|>",
"<|vision_pad|>",
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],
"is_local": true,
"local_files_only": false,
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"tool_parser_type": "json_tools",
"unk_token": null
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