🔘Pynt as a Standalone Container

Run Pynt as a standalone container without the CLI for isolated and scalable API security testing. Ensure consistent and efficient protection across your development environments.

🚀 At a Glance: Pynt’s standalone container mode allows you to run the Pynt container without the CLI, making it ideal for systems like Kubernetes or container orchestration platforms. In this mode, you control Pynt through its APIs and route HTTP traffic through the container for security testing.

Standalone container mode

Pynt container can run without the CLI, facilitating its use in various deployment scenarios beyond traditional Docker-based environments. This mode is particularly useful for systems leveraging Kubernetes or similar container orchestration platforms.

This mode is based on Pynt command, but here the user is required to run the Pynt container, control it through APIs, and route the http traffic through the container.

There are two step needed for this integration:

Run the Pynt Container: This involves setting up and running the Pynt container. Pynt can operate as a stand-alone server, as long as it setup correctly.

Control via APIs & Route HTTP Traffic: After deploying the Pynt container, you will need to manage it through its APIs. Additionally, route your HTTP traffic through the container to have Pynt scan the traffic.

How to run the Pynt container

Image:

ghcr.io/pynt-io/pynt:v1-latest

Ports:

6666 - Pynt proxy port
5001 - port for API commands to Pynt server

Environment variables:

PYNT_ID="$PYNT_ID" - Pynt credentials, how to get it
PYNT_SAAS_URL="https://api.pynt.io/v1" - Pynt Platform's URL

Flags:

When the application identifier is not provided, the scan results will not be saved in any application, and you can see it in the global views. The best practice is to provide the identifier.

--application-id - Where can I find the application ID?
--application-name - Your existing application name or a new one. (the application will be created automatically if it does not exist)

Here is an example of running Pynt server using docker:

docker run -e PYNT_ID="$PYNT_ID" -p 6666:6666 -p 5001:5001 --rm ghcr.io/pynt-io/pynt:v1-latest proxy --application-name my-app

How to control Pynt container

Once the Pynt container is running in your environment, run the Pynt scan by the following these steps:

Set a few environment variables pointing to the container (or to your local machine when exposing the ports):
```
export PYNT_SERVER_BASE=http://127.0.0.1
export PYNT_SERVER_URL=$PYNT_SERVER_BASE:5001
```
To activate the Pynt proxy, make a call to the /api/proxy/start endpoint. Once activated, Pynt will listen on port 6666 for incoming traffic. For example, you can use curl as follows:
```
scan_output=$(curl -X PUT $PYNT_SERVER_URL/api/proxy/start)
```
Run your functional tests through the Pynt proxy. Pynt will read and analyze the traffic. For example, using Python Pytest:
```
export HTTP_PROXY=$PYNT_SERVER_BASE:6666
export HTTPS_PROXY=$PYNT_SERVER_BASE:6666
pytest goat.py
```
To start a Pynt scan, you need to call the /api/proxy/stop endpoint, providing the scan_id in the message body. For example, you can use the following curl command:
```
curl -X PUT $PYNT_SERVER_URL/api/proxy/stop -d "$scan_output" -H "Content-Type: application/json"
```

Optionally, you can pass the Application ID and Test Name for improved management of this scan in the Pynt platform. For example:

scanId=$(echo $scan_output | jq -r .scanId)
applicationId=xxxx
testName="My Test Name"
json_payload=$(printf '{"scanId": "%s", "applicationId": "%s", "testName": "%s"}' "$scanId" "$applicationId" "$testName")
curl -X PUT $PYNT_SERVER_URL/api/proxy/stop -d "$json_payload" -H "Content-Type: application/json"

Retrieving Scan Reports

After running a Pynt scan, you can retrieve the scan report by polling the /api/report endpoint using the scan ID. This process ensures that you get the final report once the scan is complete.

Polling for Report Completion

Since scans take time to process, you must continuously check the report status until the scan completes. The server returns:

202 (Accepted): The scan is still in progress.
200 (OK): The scan is complete, and the report is available.

Retrieving the HTML Report

The HTML report provides a human-readable summary of the scan results.

Example using curl

scanId=$(echo $scan_output | jq -r .scanId)
status_code=$(curl -o "pynt_report.html" -s -w "%{http_code}\n" "$PYNT_SERVER_URL/api/report?scanId=$scanId&format=html")

This command saves the report as pynt_report.html

Controlling the return code from Pynt

Pynt container have an optional flag --severity-level

With this flag, you have granular control over whether Pynt returns an error code (3) in the event of findings. Use this flag to control when Pynt will break the CI/CD run, allowed values are:

'all', 'medium', 'high', 'critical', 'none' (default)

Retrieving the JSON Report

The JSON report contains structured data about vulnerabilities, making it useful for integrations with other tools.

Example using curl

scanId=$(echo $scan_output | jq -r .scanId)
status_code=$(curl -o "pynt_report.json" -s -w "%{http_code}\n" "$PYNT_SERVER_URL/api/report?scanId=$scanId&format=json")

This command retrieves the scan results in JSON format and saves them as pynt_report.json

Example: Pynt with Kubernetes

💡 Still Need Help? For any questions or troubleshooting, reach out to the Pynt Community Support.

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Last updated 4 months ago