ai threat modeling action

️ This repository is deprecated and will be archived. All prompts moved to: https://github.com/xvnpw/fabric-agent-action

AI Threat Modeling action

? You can use this GitHub Action to generate AI featured content for threat modeling and security review. It uses xvnpw/ai-threat-modeling underneath.

️ This is experimental project

Supported features:

Feature	Description
High Level Security and Privacy Requirements	Action will take project description and will use LLM to generate high level requirements regarding security and privacy
Threat Model of Architecture	Action will take architecture description and will use LLM to generate threat model for it
Security Acceptance Criteria for User Story	Action will take particular user story and generate security related acceptance criteria
Review of input file	Action will take input file (e.g. Architecture Description) are review it using LLM

Table of content

• Versions
• Example Outputs
  • Feature: High Level Security and Privacy Requirements
  • Feature: Threat Model of Architecture
  • Feature: Security Acceptance Criteria for User Story
  • Feature: Review of input file
• Inputs
• LLM Providers
• Usage
  • High Level Security and Privacy Requirements
  • Architecture Threat Model
  • Security Acceptance Criteria for User Story
    • Trigger on changes to directory
    • Trigger on issue change
  • Review of input file
  • Push into Repository
  • Create Pull Request
  • Custom Prompts
• Roadmap
• Tech Stack
• Fork
• Privacy
  • OpenAI
  • OpenRouter

Versions

Use below versions for specific models:

Model	Version	Note
OpenAI GPT-3.5, Anthropic Claude 2	v1.2.6.1	️ Latest releases include prompts that might not work properly with those models
OpenAI GPT-4	Latest
Claude 3	Latest

Example Outputs

Feature: High Level Security and Privacy Requirements

Model	Input	Output
OpenAI GPT-3.5	PROJECT.md	PROJECT_SECURITY.md or as pull request
Anthropic Claude 2	PROJECT.md	PROJECT_SECURITY.md or as pull request
OpenAI GPT-4	PROJECT.md	PROJECT_SECURITY.md or as pull request
Anthropic Claude 3 Opus	PROJECT.md	PROJECT_SECURITY.md or as pull request

Feature: Threat Model of Architecture

Model	Input	Output
OpenAI GPT-3.5	ARCHITECTURE.md	ARCHITECTURE_SECURITY.md
Anthropic Claude 2	ARCHITECTURE.md	ARCHITECTURE_SECURITY.md
OpenAI GPT-4	ARCHITECTURE.md	ARCHITECTURE_SECURITY.md
Anthropic Claude 3 Opus	ARCHITECTURE.md	ARCHITECTURE_SECURITY.md

Feature: Security Acceptance Criteria for User Story

Model	Input	Output
OpenAI GPT-3.5	0001_STORE_DIET_INTRODUCTIONS.md or issue	0001_STORE_DIET_INTRODUCTIONS_SECURITY.md or as issue comment
Anthropic Claude 2	0001_STORE_DIET_INTRODUCTIONS.md or issue	0001_STORE_DIET_INTRODUCTIONS_SECURITY.md or as issue comment
OpenAI GPT-4	0001_STORE_DIET_INTRODUCTIONS.md or issue	0001_STORE_DIET_INTRODUCTIONS_SECURITY.md or as issue comment
Anthropic Claude 3 Opus	0001_STORE_DIET_INTRODUCTIONS.md or issue	0001_STORE_DIET_INTRODUCTIONS_SECURITY.md or as issue comment

Feature: Review of input file

Model	Input	Output
OpenAI GPT-4	ARCHITECTURE.md	ARCHITECTURE_REVIEW.md
Anthropic Claude 3 Opus	ARCHITECTURE.md	ARCHITECTURE_REVIEW.md

Inputs

Add a step like this to your workflow:

- uses: xvnpw/[email protected] # You can change this to use a specific version.
  with:
    # Type of feature, one of: project, architecture, user-story
    # Default: ''
    # Required
    type: 'project'

    # Provider name, one of: openai, openrouter
    # Default: 'openai'
    provider: 'openai'

    # Paths to input files formatted as json array
    # Default: ''
    input_files: '["PROJECT.md"]'

    # Path to output file
    # Default: ''
    output_file: 'PROJECT_SECURITY.md'

    # For USER STORY only! paths to architecture files formatted as json array
    # Default: ''
    input_architecture_files: '["ARCHITECTURE.md"]'

    # For USER STORY only! path to architecture threat model
    # Default: ''
    input_architecture_threat_model_file: 'ARCHITECTURE_SECURITY.md'

    # For USER STORY only! suffix that will be added to input file name to create output file
    # Default: '_SECURITY'
    user_story_output_suffix: '_SECURITY'

    # Type of OpenAI GPT model
    # Default: gpt-4
    # For openai models check: https://platform.openai.com/account/rate-limits
    # For openrouter models check: https://openrouter.ai/docs#models
    model: 'gpt-3.5-turbo-16k'

    # Sampling temperature for a model
    # Default: 0
    temperature: '0.3'

    # Review input files using LLM
    # Default: false
    review: true

    # Verbose log messages
    # Default: false
    verbose: true

    # Debug log messages
    # Default: false
    debug: true

    # Prompt templates directory
    # Default: '/app/templates'
    # By default action will use prompt templates build-in docker image. You can specify your own without forking action.
    templates_dir: './templates'
  env:
    # OpenAI API key
    # Optional. Only if want to use openai provider
    # Get a key from https://platform.openai.com/account/api-keys
    # Add it to secrets in your repository settings
    OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}

    # Open Router API key
    # Optional. Only if want to use openrouter provider
    # Get a key from https://openrouter.ai/keys
    # Add it to secrets in your repository settings
    OPENROUTER_API_KEY: ${{ secrets.OPENROUTER_API_KEY }}

LLM Providers

Currently supporting:

• OpenAI
• OpenRouter

Usage

Action will generate output_file based on inputs. Using other actions you can:

• directly push into repository,
• create pull request,
• or add comment to issue.

High Level Security and Privacy Requirements

If your input files are quite big you need to change model to one with bigger context, e.g. gpt-3.5-turbo-16k.

If you change input files, remember to change the trigger:

on:
  push:
    branches:
      - main
    paths:
      - 'project-desc-1.md'
      - 'project-desc-2.md'

Example (pull requests approach):

on:
  push:
    branches:
      - main
    paths:
      - 'PROJECT.md'

jobs:
  project_ai_devsecops_job:
    runs-on: ubuntu-latest

    permissions:
      # Give the default GITHUB_TOKEN write permission to commit and push the
      # added or changed files to the repository. Also permission to create/update
      # pull requests.
      contents: write
      pull-requests: write

    name: Run ai threat modeling action for project analysis
    steps:
      - name: Checkout repo
        uses: actions/checkout@v3
      - name: Generate project security requirements
        uses: xvnpw/[email protected]
        with:
          type: 'project'
          input_files: '["PROJECT.md"]'
          output_file: 'PROJECT_SECURITY.md'
          temperature: 0
          verbose: true
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
      # Will use peter-evans/create-pull-request to create or update pull request
      - name: Create Pull Request
        uses: peter-evans/create-pull-request@v5
        with:
          branch: create-pull-request/project
          title: (AI Generated) High Level Security and Privacy Requirements
          body: Automated pull request based on your changes to project. Please review it carefully.
          labels: 'security, ai'

Architecture Threat Model

Check High Level Security and Privacy Requirements for details about triggers and models.

Example (direct push into repository):

on:
  push:
    branches:
      - main
    paths:
      - 'ARCHITECTURE.md'

jobs:
  architecture_ai_tm_job:
    runs-on: ubuntu-latest

    permissions:
      # Give the default GITHUB_TOKEN write permission to commit and push the
      # added or changed files to the repository.
      contents: write

    name: Will run ai threat modeling action for architecture analysis
    steps:
      - name: Checkout repo
        uses: actions/checkout@v3
      - name: Generate architecture threat model
        uses: xvnpw/[email protected]
        with:
          type: 'architecture'
          input_files: '["ARCHITECTURE.md"]'
          output_file: 'ARCHITECTURE_SECURITY.md'
          temperature: 0
          verbose: true
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
      # Will use add-and-commit action to push output_file directly into repository
      - name: Commit changes
        uses: EndBug/add-and-commit@v9
        with:
          message: 'Project architecture threat model'
          add: 'ARCHITECTURE_SECURITY.md'

Security Acceptance Criteria for User Story

Most useful usage is with github issues. But you can also generate output based on changes to particular directory (I did that in research).

User Stories feature requires two new parameters:

• input_architecture_files - json array of paths of input architecture files e.g. ["arch-1.md","arch-2.md"]
• input_architecture_threat_model_file - path to architecture threat model e.g. ARCHITECTURE_SECURITY.md

and one optional:

• user_story_output_suffix - suffix that will be added to input file name to create output file, e.g. _SECURITY

Trigger on changes to directory

In case of user story, build is triggered on changes to particular directory. First, it needs to figure out which files were changed and process them individually.

As you can see, we don't use input_files parameter. This time we watch the whole directory for changes:

on:
  push:
    branches:
      - main
    paths:
      - 'user-stories/*.md'
      - '!user-stories/*_SECURITY.md'

For your own directories, you need to adjust paths configuration. The same apply for committing changes with add: 'user-stories/'.

Example (direct push into repository):

on:
  push:
    branches:
      - main
    paths:
      - 'user-stories/*.md'
      - '!user-stories/*_SECURITY.md'

jobs:
  user_story_ai_tm_job:
    runs-on: ubuntu-latest

    permissions:
      # Give the default GITHUB_TOKEN write permission to commit and push the
      # added or changed files to the repository.
      contents: write

    name: Will run ai threat modeling action for user story analysis
    steps:
      - name: Checkout repo
        uses: actions/checkout@v3
      - name: Check which files were changed
        id: files_check
        uses: lots0logs/[email protected]
        with:
          token: ${{ secrets.GITHUB_TOKEN }}
      - name: Printing
        run: |
          echo "${{ steps.files_check.outputs.all }}"
      - name: Generate user story security acceptance criteria
        uses: xvnpw/[email protected]
        with:
          type: 'user-story'
          input_files: "${{ steps.files_check.outputs.all }}"
          input_architecture_files: '["ARCHITECTURE.md"]'
          input_architecture_threat_model_file: "ARCHITECTURE_SECURITY.md"
          user_story_output_suffix: "_SECURITY"
          temperature: 0
          verbose: true
          model: "gpt-3.5-turbo-16k"
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
      - name: Commit changes
        uses: EndBug/add-and-commit@v9
        with:
          message: 'User stories: security acceptance criteria'
          add: 'user-stories/'

Trigger on issue change

In this case we consider only stories with certain label:

if: contains(github.event.issue.labels.*.name, 'ai-threat-modeling')

Comment is added (or updated) using peter-evans/find-comment and peter-evans/create-or-update-comment actions.

Example (comment on issue):

name: Run ai threat modeling action for user story in issue analysis
on:
  issues:
    types:
      - labeled
      - edited

jobs:
  user_story_issue_ai_devsecops:
    name: Run ai threat modeling action for user story in issue analysis
    if: contains(github.event.issue.labels.*.name, 'ai-threat-modeling')
    runs-on: ubuntu-latest
    permissions:
      issues: write
      contents: write

    steps:
      - name: Checkout repo
        uses: actions/checkout@v3
      - uses: actions/github-script@v6
        id: set-result
        with:
          result-encoding: string
          retries: 3
          script: |
            const issue = await github.rest.issues.get({
              issue_number: ${{ github.event.issue.number }},
              owner: "${{ github.repository_owner }}",
              repo: "${{ github.event.repository.name }}",
            });
            const body = issue.data.body;
            const fs = require('fs');
            fs.writeFile('${{ github.workspace }}/issue_body.md', body, (err) => {
                if (err) throw err;
                console.log('Data written to file');
            });
            return JSON.stringify(body);
      - name: Generate user story security acceptance criteria
        uses: xvnpw/[email protected]
        with:
          type: 'user-story'
          input_files: '["issue_body.md"]'
          input_architecture_files: '["ARCHITECTURE.md"]'
          input_architecture_threat_model_file: "ARCHITECTURE_SECURITY.md"
          temperature: 0
          verbose: true
          model: "gpt-3.5-turbo-16k"
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
      - name: Find Comment
        uses: peter-evans/find-comment@v2
        id: fc
        with:
          issue-number: ${{ github.event.issue.number }}
          comment-author: 'github-actions[bot]'
          body-includes: (AI Generated) Security Related Acceptance Criteria
      - name: Add comment
        uses: peter-evans/create-or-update-comment@v3
        with:
          comment-id: ${{ steps.fc.outputs.comment-id }}
          issue-number: ${{ github.event.issue.number }}
          body-path: ${{ github.workspace }}/issue_body_SECURITY.md
          edit-mode: replace

Review of input file

Example (direct push into repository):

on:
  push:
    branches:
      - main
    paths:
      - 'ARCHITECTURE.md'
  workflow_dispatch:

jobs:
  architecture_ai_review_job:
    runs-on: ubuntu-latest

    permissions:
      # Give the default GITHUB_TOKEN write permission to commit and push the
      # added or changed files to the repository.
      contents: write

    name: Run ai threat modeling action for architecture review
    steps:
      - name: Checkout repo
        uses: actions/checkout@v3
      - name: Generate architecture review
        uses: xvnpw/[email protected]
        with:
          type: 'architecture' # will create threat model
          input_files: 'ARCHITECTURE.md'
          output_file: 'ARCHITECTURE_REVIEW.md'
          review: true
          temperature: 0.2
          verbose: true
          model: 'gpt-4'
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
      - name: Commit changes
        uses: EndBug/add-and-commit@v9
        with:
          message: 'Project architecture review'
          add: 'ARCHITECTURE_REVIEW.md'
          pull: '--rebase --autostash'

Push into Repository

With Add & Commit you can get output_file easily committed into repository:

      - name: Commit changes
        uses: EndBug/add-and-commit@v9
        with:
          message: 'Project architecture threat model'
          add: 'ARCHITECTURE_SECURITY.md'

If you change output file, remember to change commit file:

      - name: Commit changes
        uses: EndBug/add-and-commit@v9
        with:
          message: 'Project security requirements'
          add: 'project-sec-reqs.md'

Create Pull Request

With Create Pull Request you can create new pull request with output_file:

      - name: Create Pull Request
        uses: peter-evans/create-pull-request@v5
        with:
          branch: create-pull-request/project
          title: (AI Generated) High Level Security and Privacy Requirements
          body: Automated pull request based on your changes to project. Please review it carefully.
          labels: 'security, ai'

In this mode, you also need to adjust permissions for workflow:

    permissions:
      # Give the default GITHUB_TOKEN write permission to commit and push the
      # added or changed files to the repository.
      # It has also permission to pull requests
      contents: write
      pull-requests: write

Also change settings for actions.

Custom Prompts

You might want to tune prompts. To do so, you don't need to fork action, but provide templates directory into your target repository:

cd $HOME/<projects> # your directory with repositories
git clone [email protected]:xvnpw/ai-threat-modeling-action.git
cp -r ai-threat-modeling-action/templates <target-repo>/
cd <target-repo>/templates
# edit templates

In workflow file add:

uses: xvnpw/[email protected]
with:
  ...
  templates_dir: './templates'

./templates - is directory relative to root.

? Roadmap

This project started as research of LLMs capabilities, but it improved over time beyond simple PoC. With version 1, it can be used to review documents in github using direct push, pr or issues. Further development or fixes are not guaranteed. If you plan to use it in your company, best to fork it and tune to your needs.

Tech Stack

• Python
• LLM Tooling: Langchain
• LLM: OpenAI GPT, OpenRouter

Fork

Fork this project. Edit files and release action:

git add .
git commit -m "My first action is ready"
git tag -a -m "My first action release" v1
git push --follow-tags

Privacy

OpenAI

This project uses OpenAI API. By default your data will not be used for learning, as per API data usage policies:

OpenAI will not use data submitted by customers via our API to train or improve our models, unless you explicitly decide to share your data with us for this purpose. You can opt-in to share data.

OpenRouter

OpenRouter describe privacy and filtering in settings for each model.