...
The machine running the scanner must have
docker
installedThe machine running the scanner must have internet access
We can recommend a base of 8GB RAM / 4 CPUs to run the scans, but note that scan time is proportional to the code base size so the specs that fit your needs may vary based on the size of your codebase.
Step 1: Generate a SAST Security Results API Key
Navigate to Data Theorem’s API key provisioning portal https://www.securetheorem.com/devsecops/v2/results_api_access
Make sure the API key has the “SAST Scanning” feature permission
...
Step 2: Run the Data Theorem SAST scanner
The Data Theorem Scanner docker image is available at us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast
Environment Variables Inputs
The Data Theorem SAST scanner needs the following inputs to run:
DT_SAST_API_KEY
: Data Theorem API Key retrieved on step 1DT_SAST_REPOSITORY_NAME
: name of your resource to scanexample
my_org_name/my_repo_name
DT_SAST_REPOSITORY_ID
: the identifier for the repository on your platform (Github, Bitbucket, Gitlab…)
example https://github.com/DT_SAST_REPOSITORY_HTML_URL
: base web url to the resourceHere are our base spec recommendations for running the on-prem scanner
Repository Size | CPUs | RAM | Disk Size (SSD) |
---|---|---|---|
0-5 GB | 4 CPUs | 8 GB | 16 GB |
5-10 GB | 8 CPUs | 16 GB | 32 GB |
10-20 GB | 16 CPUs | 32 GB | 64 GB |
Note: Scan time is relative to the repository size so the specs that fit your needs may vary based on the size of your repository.
Step 1: Generate a SAST Security Results API Key
Navigate to Data Theorem’s API key provisioning portal https://www.securetheorem.com/devsecops/v2/results_api_access
Make sure the API key has the “SAST Scanning” feature permission
...
Step 2: Run the Data Theorem SAST scanner
The Data Theorem Scanner docker image is available at us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast
Environment Variables Inputs
The Data Theorem SAST scanner needs the following inputs to run:
DT_SAST_API_KEY
: Data Theorem API Key retrieved on step 1DT_SAST_REPOSITORY_NAME
: name of your resource to scanexample
my_org_name/my_repo_name
DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME
: name of theID
: the identifier for the repository on your platform (Github, Bitbucket, Gitlab…)DT_SAST_REPOSITORY_HTML_URL
: base web url to the resourceexample
https://github.com/my_org_name/my_repo_name
DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME
: name of the default branch name of your repositoryexample
main
...
set
DT_SAST_FAIL_MODE=true
if set, the process will return a non-zero status when issues are found. This can be used to make Data Theorem SAST a blocking step of your workflow.set
DT_SAST_NO_FORWARD_MODE=true
if you want to skip forwarding scan results/metadata to Data Theorem, note that this will mean that no scan results will be visible from the Data Theorem Portal
...
set
DT_SAST_INCLUDE_CODE_SNIPPETS=false
if you want to hide code snippets from the printed scan result in the output (you will still see the issue location in the code from the file path and line)
Local Scanning example
The Data Theorem on-prem scanner can run from your local machine.
...
Code Block |
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docker run -it \ -e DT_SAST_API_KEY=$DT_SAST_API_KEY \ -e DT_SAST_REPOSITORY_NAME="<my_org>/<my_repo>" \ -e DT_SAST_NO_FORWARD_MODE=true \ --mount type=bind,source="$(pwd)"/,target=/target \ us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast \ data_theorem_sast_analyzer scan /target |
Sample output:
...
Example with inputs to forward scan results to the [Data Theorem Portal](https://www.securetheorem.com/api/v2/security/sast )
Code Block |
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docker run -it \
-e DT_SAST_API_KEY=$DT_SAST_API_KEY \
-e DT_SAST_REPOSITORY_NAME="<my_org>/<my_repo>" \
-e DT_SAST_REPOSITORY_PLATFORM=BITBUCKET \
-e DT_SAST_REPOSITORY_ID={1e734a1b-8d0e-4787-a205-aba048c00a89} \
-e DT_SAST_REPOSITORY_HTML_URL="https://bitbucket.org/<my_org>/<my_repo>" \
-e DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME="main" \
-e DT_SAST_SCANNED_BRANCH="main" \
--mount type=bind,source="$(pwd)"/,target=/target \
us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast \
data_theorem_sast_analyzer scan /target |
Sample output:
Code Block |
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Scanning completed in 15.65 seconds Scan results: 1 issues on commit=f719d004ef98254b46187c53ef1b3ed2f8643082 Total Issues: 1 Issues per types: - First Party Code: 1 - SCA: 1 Issues per severity: - High Severity: 1 - Medium Severity: 1 [ { "issue_title": "Unauthenticated Route Found for Flask API", "issue_description": "The security of this code is compromised due to the presence of unauthenticated access to specific routes within the Flask API. This vulnerability poses a significant risk as it can potentially expose sensitive data or allow unauthorized actions to be performed. To mitigate this risk, it is crucial to implement robust authentication mechanisms that ensure only authorized users can access the protected routes.\n\nBy allowing unauthenticated access, the code fails to validate the identity of users before granting them access to protectedcertain routes. This canlack beof achievedauthentication throughopens variousthe methods such as username/password authentication, token-based authentication, or integration with third-party authentication providers.\n\nAdditionallydoor for malicious actors to exploit the system and gain unauthorized access to sensitive information or perform actions that they should not be able to.\n\nTo address this issue, it is importantrecommended to considerimplement implementinga othersecure securityauthentication measuresprocess suchthat verifies asthe encryptionidentity of sensitive data, input validationusers before granting them access to preventprotected injectionroutes. attacks,This andcan properbe errorachieved handlingthrough tovarious avoidmethods leakingsuch sensitive information.\n\nBy implementing these security measures, the code can ensure that only authenticated and authorized users can access the protected routes, significantly reducing the risk of unauthorized access or data breaches. It is essential to prioritize security in the development process to safeguard sensitive data and protect the integrity of the system.", "issue_type": "FIRST_PARTY_CODE", "severity": "HIGH", "detected_in_file_path": "sample_code/bad_python.pyas username/password authentication, token-based authentication, or integration with third-party authentication providers.\n\nAdditionally, it is important to consider implementing other security measures such as encryption of sensitive data, input validation to prevent injection attacks, and proper error handling to avoid leaking sensitive information.\n\nBy implementing these security measures, the code can ensure that only authenticated and authorized users can access the protected routes, significantly reducing the risk of unauthorized access or data breaches. It is essential to prioritize security in the development process to safeguard sensitive data and protect the integrity of the system.", "detectedissue_on_linetype": 7"FIRST_PARTY_CODE", "issue_severity": "HIGH", "detected_in_file_path": "sample_code/bad_python.py", "detected_on_line": 7, "issue_code_snippet": "@app.route(\"/\")\ndef index():\n cmd = request.args.get(\"cmd\", \"\")\n exec(cmd)\n return \"\"" }, { "issue_title": "jinja2 version 3.1.2 contains a known vulnerability (via PyPI dependency): Jinja vulnerable to HTML attribute injection when passing user input as keys to xmlattr filter", "issue_description": "Jinja vulnerable to HTML attribute injection when passing user input as keys to xmlattr filter", "issue_type": "SCA", "severity": "MEDIUM", "detected_in_file_path": "sample_code/requirements.txt", "detected_on_line": 1, "issue_code_snippet": "jinja2==3.1.2\n" } ] Visit https://www.securetheorem.com/api/v2/security/sast for more details |
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Code Block |
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name: Data Theorem SAST # Controls when the workflow will run, adapt to your own needs on: # Triggers the workflow on push or pull request events but only for the "main" branch # Adapt triggers to your own needs push: branches: [ "main" ] # Allows you to run this workflow manually from the Actions tab workflow_dispatch: jobs: scan: runscontinue-on-error: ubuntu-latesttrue containertimeout-minutes: 30 runs-on: ubuntu-latest container: image: us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest env: DT_SAST_API_KEY: ${{ secrets.DT_SAST_API_KEY }} DT_SAST_REPOSITORY_NAME: ${{ github.event.repository.full_name }} DT_SAST_REPOSITORY_PLATFORM: GITHUB DT_SAST_REPOSITORY_ID: ${{ github.event.repository.id }} DT_SAST_REPOSITORY_HTML_URL: ${{ github.event.repository.html_url }} DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME: ${{ github.event.repository.default_branch }} DT_SAST_OUTPUT_DIR: ./ steps: - uses: actions/checkout@v4 - name: Start Data Theorem SAST Scan run: data_theorem_sast_analyzer scan ./ - uses: actions/upload-artifact@v4 with: name: dt-sast-scan-result path: ./scan-results-sarif.json |
...
Code Block |
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name: Data Theorem SAST # Controls when the workflow will run, adapt to your own needs on: # Triggers the workflow on push or pull request events but only for the "main" branch # Adapt triggers to your own needs pull_request jobs: scan: continue-on-error: true timeout-minutes: 30 runs-on: ubuntu-latest container: image: us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest env: DT_SAST_API_KEY: ${{ secrets.DT_SAST_API_KEY }} DT_SAST_REPOSITORY_NAME: ${{ github.event.repository.full_name }} DT_SAST_REPOSITORY_PLATFORM: GITHUB DT_SAST_REPOSITORY_ID: ${{ github.event.repository.id }} DT_SAST_REPOSITORY_HTML_URL: ${{ github.event.repository.html_url }} DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME: ${{ github.event.repository.default_branch }} DT_SAST_SCAN_HEAD_REF: "refs/remotes/origin/${{ github.head_ref }}" DT_SAST_SCAN_TARGET_REF: "refs/remotes/origin/${{ github.base_ref }}" DT_SAST_FAIL_MODE: true steps: - uses: actions/checkout@v4 with: fetch-depth: 0 # IMPORTANT: Needed because by default, actions/checkout@v4 doesn't load the full git history/refs - name: Start Data Theorem SAST Scan run: data_theorem_sast_analyzer scan ./ |
...
Note: the Gitlab pipeline must run the Data Theorem SAST step on an executor that supports the image
feature.
See https://docs.gitlab.com/runner/executors/#compatibility-chart for more information on compatible executors
Code Block |
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stages: - security-scan datatheorem-sast-scan-branch-job: only: - main # Trigger on default branch push, replace 'main' with the name of your default branch tags: - gitlab-runner-docker # Needs to be an executor compatible with the`image` feature stage: security-scan image: us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest script: - export DT_SAST_API_KEY=$DT_SAST_API_KEY - export DT_SAST_REPOSITORY_NAME=$CI_PROJECT_PATH - export DT_SAST_REPOSITORY_PLATFORM="GITLAB_ON_PREM" - export DT_SAST_REPOSITORY_ID=$CI_PROJECT_ID - export DT_SAST_REPOSITORY_HTML_URL=$CI_PROJECT_URL - export DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME=$CI_DEFAULT_BRANCH - export DT_SAST_SCAN_HEAD_REF=$CI_COMMIT_REF_NAME - data_theorem_sast_analyzer scan ./ datatheorem-sast-scan-merge-request-job: only: - merge_requests tags: - gitlab-runner-docker # Needs to be an executor compatible with the`image` feature stage: security-scan image: us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest script: - export DT_SAST_API_KEY=$DT_SAST_API_KEY - export DT_SAST_REPOSITORY_NAME=$CI_PROJECT_PATH - export DT_SAST_REPOSITORY_PLATFORM="GITLAB_ON_PREM" - export DT_SAST_REPOSITORY_ID=$CI_PROJECT_ID - export DT_SAST_REPOSITORY_HTML_URL=$CI_PROJECT_URL - export DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME=$CI_DEFAULT_BRANCH - export DT_SAST_SCAN_TARGET_REF=$CI_MERGE_REQUEST_TARGET_BRANCH_NAME - data_theorem_sast_analyzer scan ./ scan ./ datatheorem-sast-scan-merge-request-job: only: - merge_requests tags: - gitlab-runner-docker # Needs to be an executor compatible with the`image` feature stage: security-scan image: us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest script: - export DT_SAST_API_KEY=$DT_SAST_API_KEY - export DT_SAST_REPOSITORY_NAME=$CI_PROJECT_PATH - export DT_SAST_REPOSITORY_PLATFORM="GITLAB_ON_PREM" - export DT_SAST_REPOSITORY_ID=$CI_PROJECT_ID - export DT_SAST_REPOSITORY_HTML_URL=$CI_PROJECT_URL - export DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME=$CI_DEFAULT_BRANCH - export DT_SAST_SCAN_TARGET_REF=$CI_MERGE_REQUEST_TARGET_BRANCH_NAME - data_theorem_sast_analyzer scan ./ |
Azure DevOps Pipeline Example
Create a new Azure DevOps Pipeline
Add a variable named DT_SAST_API_KEY
with the value retrieved in step 1 and make sure the Keep this value secret
option is checked. (See https://learn.microsoft.com/en-us/azure/devops/pipelines/process/set-secret-variables?view=azure-devops&tabs=yaml%2Cbash )
The Azure Pipeline definition should look like this:
Code Block |
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trigger:
- main
pool:
vmImage: ubuntu-latest
steps:
- script: |
docker run \
-e DT_SAST_API_KEY='$(DT_SAST_API_KEY)' \
-e DT_SAST_REPOSITORY_NAME=$(Build.Repository.Name) \
-e DT_SAST_REPOSITORY_PLATFORM=AZURE_DEVOPS \
-e DT_SAST_REPOSITORY_ID=$(Build.Repository.ID) \
-e DT_SAST_REPOSITORY_HTML_URL=$(Build.Repository.Uri) \
-e DT_SAST_REPOSITORY_DEFAULT_BRANCH_NAME="main" \
-e DT_SAST_SCANNED_BRANCH=$(Build.SourceBranchName) \
-e DT_SAST_SCAN_HEAD_REF="HEAD" \
--mount type=bind,source="$(pwd)"/,target=/target \
us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest \
data_theorem_sast_analyzer scan /target
displayName: 'Data Theorem On-Prem SAST'
|
Troubleshooting
SSL Errors
If the scanner if failing because of SSL errors, it may be because you are running the scanner behind a proxy that is making SSL verification fail.
If this is the case, we recommend to do the following:
You can build a custom Docker images that embeds your own valid SSL certificates
Make sure you have valid certificates that are able to call api.securetheorem.com
from the machine that is running the Data Theorem On-Prem Scanner
The Dockerfile would look like this
Code Block |
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FROM us-central1-docker.pkg.dev/prod-scandal-us/datatheorem-sast/datatheorem-sast:latest
# Copy SSL certificates to add
COPY --from=<YOUR_SOURCE> <PATH_TO_YOUR_SSL_CERTS> /usr/share/ca-certificates/custom
# Add certificates to /etc/ca-certificates.conf
RUN for crt in /usr/share/ca-certificates/custom/*.crt; do \
echo "Adding $crt" && echo "custom/$(basename "$crt")" >> /etc/ca-certificates.conf; \
done
# Update bundled CA certificates at /etc/ssl/certs/ca-certificates.crt
RUN update-ca-certificates
ENV DT_SAST_PATH_TO_SSL_CERTS_FILE=/etc/ssl/certs/ca-certificates.crt |
If this is not working, please contact
support@datatheorem.com
for help