Bandit scanner reference for STO
You can scan your code repositories using Bandit, an open-source tool designed to find common security issues in Python code.
Important notes for running Bandit scans in STO
Docker-in-Docker requirements
The following use cases require a Docker-in-Docker background step in your pipeline:
- Container image scans on Kubernetes and Docker build infrastructures
- Required for Orchestration and Dataload scan modes
- Security steps (not step palettes) on Kubernetes and Docker build infrastructures
- Required for all target types and Orchestration/DataLoad modes
The following use cases do not require Docker-in-Docker:
- Harness Cloud AMD64 build infrastructures
- SAST/DAST/configuration scans that use scanner templates (not Security steps)
- Ingestion scans where the data file has already been generated
Set up a Docker-in-Docker background step
-
Go to the stage where you want to run the scan.
-
In Overview, add the shared path
/var/run
. -
In Execution, do the following:
-
Click Add Step and then choose Background.
-
Configure the Background step as follows:
-
Dependency Name =
dind
-
Container Registry = The Docker connector to download the DinD image. If you don't have one defined, go to Docker connector settings reference.
-
Image =
docker:dind
-
Under Entry Point, add the following:
dockerd
In most cases, using
dockerd
is a faster and more secure way to set up the background step. For more information, go to the TLS section in the Docker quick reference.
If the DinD service doesn't start with
dockerd
, clear the Entry Point field and then run the pipeline again. This starts the service with the default entry point.- Under Optional Configuration, select the Privileged checkbox.
-
-
- Visual setup
- YAML setup

Add a Background step to your pipeline and set it up as follows:
- step:
type: Background
name: background-dind-service
identifier: Background_1
spec:
connectorRef: CONTAINER_IMAGE_REGISTRY_CONNECTOR
image: docker:dind
shell: Sh
entrypoint:
- dockerd
privileged: true
Root access requirements
You need to run the scan step with root access if either of the following apply:
-
You need to run a Docker-in-Docker background service.
-
You need to add trusted certificates to your scan images at runtime.
You can set up your STO scan images and pipelines to run scans as non-root and establish trust for your own proxies using self-signed certificates. For more information, go to Configure STO to Download Images from a Private Registry.
For more information
The following topics contain useful information for setting up scanner integrations in STO:
Bandit step settings for STO scans
The recommended workflow is to add a Bandit step to a Security Tests or CI Build stage and then configure it as described below.
Scan
Scan Mode
- Orchestration Configure the step to run a scan and then ingest, normalize, and deduplicate the results.
- Ingestion Configure the step to read scan results from a data file and then ingest, normalize, and deduplicate the data.
Scan Configuration
The predefined configuration to use for the scan. All scan steps have at least one configuration.
Target
Type
-
Repository Scan a codebase repo.
In most cases, you specify the codebase using a code repo connector that connects to the Git account or repository where your code is stored. For information, go to Configure codebase.
Name
The identifier for the target, such as codebaseAlpha
or jsmith/myalphaservice
. Descriptive target names make it much easier to navigate your scan data in the STO UI.
It is good practice to specify a baseline for every target.
Variant
The identifier for the specific variant to scan. This is usually the branch name, image tag, or product version. Harness maintains a historical trend for each variant.
Workspace (repository)
The workspace path on the pod running the scan step. The workspace path is /harness
by default.
You can override this if you want to scan only a subset of the workspace. For example, suppose the pipeline publishes artifacts to a subfolder /tmp/artifacts
and you want to scan these artifacts only. In this case, you can specify the workspace path as /harness/tmp/artifacts
.
Ingestion File
The path to your scan results when running an Ingestion scan, for example /shared/scan_results/myscan.latest.sarif
.
-
The data file must be in a supported format for the scanner.
-
The data file must be accessible to the scan step. It's good practice to save your results files to a shared path in your stage. In the visual editor, go to the stage where you're running the scan. Then go to Overview > Shared Paths. You can also add the path to the YAML stage definition like this:
- stage:
spec:
sharedPaths:
- /shared/scan_results
Log Level, CLI flags, and Fail on Severity
Log Level
The minimum severity of the messages you want to include in your scan logs. You can specify one of the following:
- DEBUG
- INFO
- WARNING
- ERROR
Additional CLI flags
You can use this field to customize the scan with specific command-line arguments supported by that scanner.
For example, you can skip certain tests using -skip
followed by a list of test IDs: -skip testID_1, testID_3, testID_5
Fail on Severity
Every Security step has a Fail on Severity setting. If the scan finds any vulnerability with the specified severity level or higher, the pipeline fails automatically. You can specify one of the following:
CRITICAL
HIGH
MEDIUM
LOW
INFO
NONE
— Do not fail on severity
The YAML definition looks like this: fail_on_severity : critical # | high | medium | low | info | none
Additional Configuration
In the Additional Configuration settings, you can use the following options:
Advanced settings
In the Advanced settings, you can use the following options:
Security step settings for Bandit scans in STO (legacy)
You can set up Bandit scans using a Security step, but this is a legacy functionality. Harness recommends that you use a Bandit step instead.
Scan policy types
STO supports the following policy_type
settings for Bandit:
orchestratedScan
— A Security step in the pipeline runs the scan and ingests the results. This is the easiest to set up and supports scans with default or predefined settings.ingestionOnly
— Run the scan in a Run step, or outside the pipeline, and then ingest the results. This is useful for advanced workflows that address specific security needs. See Ingest scan results into an STO pipeline.
Target and variant
The following settings are required for every Security step:
target_name
A user-defined label for the code repository, container, application, or configuration to scan.variant
A user-defined label for the branch, tag, or other target variant to scan.
Make sure that you give unique, descriptive names for the target and variant. This makes navigating your scan results in the STO UI much easier.
You can see the target name, type, and variant in the Test Targets UI:
For more information, go to Targets, baselines, and variants in STO.
Bandit scan settings
The following settings are required for Bandit scans:
product_name
=bandit
scan_type
=repository
product_config_name
=default
— Run a Bandit scan with the default settings.repository_project
— The repository name. If you want to scanhttps://github.com/my-github-account/codebaseAlpha
, for example, you would set this tocodebaseAlpha
.repository_branch
— This tells Bandit the Git branch to scan. You can specify a hardcoded string or use the runtime variable<+codebase.branch>
. This sets the branch based on the user input or trigger payload at runtime.fail_on_severity
- See Fail on Severity.
Ingestion file
If the policy_type
is ingestionOnly
:
ingestion_file
= The path to your scan results when running an Ingestion scan, for example/shared/scan_results/myscan.latest.sarif
.
-
The data file must be in a supported format for the scanner.
-
The data file must be accessible to the scan step. It's good practice to save your results files to a shared path in your stage. In the visual editor, go to the stage where you're running the scan. Then go to Overview > Shared Paths. You can also add the path to the YAML stage definition like this:
- stage:
spec:
sharedPaths:
- /shared/scan_results
YAML pipeline example
If you copy this example, replace the placeholder values with appropriate values for your project, organization, and connectors.
pipeline:
name: your-first-pipeline-v2
identifier: yourfirstpipelinev2
projectIdentifier: YOUR_HARNESS_PROJECT_ID
orgIdentifier: YOUR_HARNESS_ORGANIZATION_ID
tags: {}
stages:
- stage:
name: bandit_repo_scan
identifier: bandit_repo_scan
description: ""
type: SecurityTests
spec:
cloneCodebase: true
platform:
os: Linux
arch: Amd64
runtime:
type: Cloud
spec: {}
execution:
steps:
- step:
type: Bandit
name: bandit_repo_scan
identifier: bandit_repo_scan
spec:
mode: orchestration
config: default
target:
name: <+input>
type: repository
variant: <+input>
advanced:
log:
level: info
fail_on_severity: critical
properties:
ci:
codebase:
connectorRef: YOUR_CODEBASE_CONNECTOR_ID
repoName: <+input>
build: <+input>