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SSM-Adaptor Microservice (Spyderisk v3.5.x API compatible)

The adaptor is a Python-based web application microservice designed to expand or customize the functionality of the Spyderisk System Modeller (also known as "SSM"). It utilizes the Spyderisk REST API and runs on FastAPI.

Deploying SSM-Adaptor

The default configuration of the SSM-Adaptor can be customized through the '.env_adaptor' file. To get started, please make a copy of the provided .env_adaptor.template file and rename it to .env_adaptor. Then, you can modify any of the default parameters in the .env_adaptor file to match your specific environment configuration.

There are several ways to deploy the SSM-Adaptor service:

Stand-alone SSM-Adaptor with docker compose

This deployment relies on an external Spyderisk service.

Edit .env_adaptor file and adjust the SSM_URL variable with a valid SSM service URL.

Run the service

docker-compose -f docker-compose-standalone.yml --env-file .env_adaptor up -d

The SSM-Adaptor endpoint will be listening on port 17643

SSM-Adaptor with Spyderisk (SSM)

This deployment includes a local instance of Spyderisk. Configuration parameters are stored in .env_adaptor.

Run the service:

docker-compose -f docker-compose.yml --env-file .env_adaptor up -d

The adaptor service will be accessible from http://localhost:8089/system-modeller/adaptor, and the SSM service from port 8089/system-modeller.

SSM-Adaptor with Spyderisk (SSM) dev mode

This deployment includes a local instance of Spyderisk. Configuration parameters are stored in .env_adaptor. The host folder is mounted via the volume ./code directly to the adaptor container.

Run the service:

docker-compose -f docker-compose-dev.yml --env-file .env_adaptor up -d

The adaptor service will be accessible from http://localhost:8089/system-modeller/adaptor, and the SSM service from port 8089/system-modeller.

Check the adaptor container logs with:

docker-compose -f docker-compose-dev.yml --env-file .env_adaptor logs -f ssm-adaptor

The adapter container can be restarted at any point to incorporate code changes made in the host folder, e.g.

docker-compose -f docker-compose-dev.yml --env-file .env_adaptor restart ssm-adaptor

Build SSM-Adaptor docker image

Build docker image:

docker build -t ssm-adaptor .

SSM-Adaptor Configuration

The core of the microservice code is common to serve both FogProtect and ProTego. Edit .env_adaptor and define the environment variable SSM_URL to your SSM service, mainly:

PROJECT_NAME=SSM Adaptor Microservice

SSM_ADAPTOR_MODE=all

ROOT_PATH=/system-modeller/adaptor

SSM_URL=http://ssm-proxy:80/system-modeller

DATA_FOLDER=/data
LOG_FOLDER=/logs

KAFKA_ENABLED=False

POLLING_DELAY_1=4
POLLING_DELAY_2=2

LOGGING_LEVEL=DEBUG

MAX_RISKS=10

ACCEPTABLE_RISK_LEVEL=Medium

FILTER_LOW_LEVEL_RISKS=TRUE

GET_ASSET_METADATA_FROM_VULN=TRUE
FP_DISABLEMENT_CONTROL=DisabledDataFlow

RISK_CALC_MODE=CURRENT

OPENVAS_REPORT_FILE_LOCATION=/code/tmp

MAX_THREATS=10

DOMAIN_MODEL_VERSION=5

Dev, FogProtect and ProTego Modes

The SSM_ADAPTOR_MODE variable controls the exposed microservice API and takes the following values:

  • PROTEGO
  • FOGPROTECT
  • ALL

The names Protego and FogProtect refer to specific EU projects that also funded some Spyderisk development.

Code Structure

The current deployment of the microservice is based on the FastAPI Framework which is a modern, fast (high-performance), web framework for building APIs with Python 3.8+ based on standard Python type hints.

The main reasons for migrating the microservice code to FastAPI were modularity and asynchronous non-blocking call support.

The main components are:

  • app the main microservice FastAPI code
  • ssm_api_client python client library for the Spyderisk API
  • openapi openapi json docs
  • test various test code/scripts/examples
.
├── app
│   ├── api
│   ├── core
│   ├── crud
│   ├── db
│   ├── main.py
│   ├── models
│   └── ssm
├── docker-compose.yml
├── docker-compose-dev.yml
├── docker-compose-standalone.yml
├── Dockerfile
├── openapi
│   └── ssm
├── README.md
├── requirements.txt
├── ssm_api_client
│   ├── api
│   ├── api_client.py
│   ├── configuration.py
│   ├── exceptions.py
│   ├── __init__.py
│   ├── models
│   └── rest.py
└── tests

The app component

  • api API endpoints
  • core Core functionality, e.g. configuration
  • crud CRUD functionality to support endpoints
  • db Mongo DB connection support
  • models models to handle data json structures and db collections
  • ssm SSM client class, and background tasks support, e.g. algorithms

Layered structure

layered structure

  • external SSM API Client level. No need to change code in ssm_api_client unless the SSM API is changed. Other API's client libraries, e.g. kafka, should be included in this layer.

  • SSMClient layer, this is a wrapper class around the SSM API Client library, it provides generic functionality that is required by the microservice API operations, e.g. get_full_model, apply_control, etc.

  • Tasks foreground and background are the main methods that implement the SSM-Adaptor functionality, e.g. mitigation algorithm, or calc_risk

  • Top level Router methods that start the execution path of a request and correspond to the API endpoints. API requests servicing should be handled by foreground and background tasks.

Background and Foreground Task lifecycle

The actual request serving should be executed by a task/job in either blocking or non blocking way. The lifecycle of a task involves the following stages:

  • CREATED, created upon incoming requests
  • ACCEPTED, session lock acquired
  • RUNNING,
  • FINISHED,
  • REJECTED, e.g. failed to acquire a session lock
  • FAILED

Task lifecycle

The job status model:

{
  "modelId": "string",
  "status": "CREATED",
  "err_msg": "string",
  "created_at": "2021-05-19T14:25:08.517Z",
  "updated_at": "2021-05-19T14:25:08.517Z",
  "messages": "string",
  "id": "string"
}

Exceptions and HTTP Return Codes

Execution paths should include try and catch blocks to handle exceptions. Background tasks should raise an exception. Blocking API tasks should raise an HTTPException, which will terminate the thread serving the request. In both cases, an update of the job status to "FAILED" should be executed before raising an exception.

Session locking mechanism

A basic session locking mechanism is introduced, the main idea is that each task that operates with an SSM model call has to acquire a lock first. Failing to acquire the lock, the task should return a HTTP 423 error code.

Locks are allocated per SSM model webkey, i.e. each model has its own lock.

A task, or foreground/background job should be registered first as CREATED and then will try to acquire the model lock, failing to do so the task status should be changed to REJECTED and raise an HTTPException HTTP_423_LOCKED.

The key attributes of a lock object are:

  • model ID
  • task job ID
  • status [LOCKED|UNLOCKED]

There are two main methods:

  • acquire_session_lock()
  • release_session_lock()

How it can be applied:

vjob = await create_vjob(db, {"modelId": modelId})
if not vjob:
   raise HTTPException(status_code=status.HTTP_404_NOT_FOUND,
                 detail="Failed to create calc-risk job")

vjob_id = str(vjob.id)
logger.info(f"calc risk job {vjob}, {vjob_id}")

# acquire session lock
lock_acquired = await acquire_session_lock(db, vjob_id)

if not lock_acquired:
   # update status of job as REJECTED
   await update_status(db, vjob_id, "REJECTED")
   raise HTTPException(status_code=status.HTTP_423_LOCKED,
            detail="Resource is locked by another process, try again later.")

...

await release_session_lock(db, vjob_id)

Generate SSM client library stubs with OpenAPI

Install the OpenAPI generator using NPM

As prerequisites java and npm are required, e.g.

sudo apt-get install npm
sudo apt-get install openjk-18-jre-headless

Then continue with the installation of the openapi-generator:

# install the latest version of "openapi-generator-cli"
npm install @openapitools/openapi-generator-cli -g
# install a specific version of "openapi-generator-cli"
npm install @openapitools/openapi-generator-cli@cli-4.3.1 -g
# Or install it as dev-dependency in your node.js projects
npm install @openapitools/openapi-generator-cli -D

create a config.json file:

{
   "modelPackage": "models",
   "apiPackage": "api",
   "packageName": "ssm_api_client"
}

Generate the SSM API python client library (ssm_api_clinet_v{x})

Before generating the client library the derived openapi yaml file requires few minor adaptations. Use an editor and change the following:

  • date-time types should be converted to string and the type should be int64
  • references to getaLabel and getmLabel should be converted to aLabel and mLabel.

There is a tool in tools/pre_fix_api.sh that can apply those changes automatically.

After editing the YAML file, generate the client code using the following line:

mkdir client
openapi-generator generate -i openapi.yaml -g python -o client/ -c config.json

Edit generated code and add the ssm_api_client prefix in the following files import statemetns:

  • ssm_api_client/init.py
  • ssm_api_clinet/api/_init.py

Alternatively use a bash script in tools/post_fix_api.sh to apply those changes.

e.g. tools/post_fix_api.sh ssm_api_client

Licence

The software is Copyright 2023 University of Southampton IT Innovation Centre and licensed under the Apache 2.0 license.

3rd Party Licenses

CSV files used for alert mappings are provided to you with licenses which can be found within app/static/mappings. As a quick summary the licenses for each file are:

  • cwec.csv - Non-exclusive, royalty-free for research, development, and commercial purposes
  • wasc.csv - CC-BY 2.5
  • capec.csv - Non-exclusive, royalty-free for research, development, and commercial purposes
  • owasp_top10_2010.csv - CC-BY-SA 3.0

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