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databricks-security-basics

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Apply Databricks security best practices for secrets and access control. Use when securing API tokens, implementing least privilege access, or auditing Databricks security configuration. Trigger with phrases like "databricks security", "databricks secrets", "secure databricks", "databricks token security", "databricks scopes".

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Databricks Security Basics

Overview

Security best practices for Databricks tokens, secrets, and access control.

Prerequisites

  • Databricks CLI installed
  • Workspace admin access (for secrets management)
  • Understanding of Unity Catalog

Instructions

Step 1: Configure Secret Scopes

# Create a secret scope (Databricks-backed)
databricks secrets create-scope my-app-secrets

# Create a secret scope (Azure Key Vault-backed)
databricks secrets create-scope azure-secrets \
  --scope-backend-type AZURE_KEYVAULT \
  --resource-id "/subscriptions/.../vaults/my-vault" \
  --dns-name "https://my-vault.vault.azure.net/"

# List scopes
databricks secrets list-scopes

Step 2: Store Secrets

# Store a secret
databricks secrets put-secret my-app-secrets db-password

# Store from file (for multi-line secrets)
databricks secrets put-secret my-app-secrets api-key --string-value "sk_live_..."

# List secrets in scope (values are hidden)
databricks secrets list-secrets my-app-secrets

Step 3: Access Secrets in Code

# In notebooks and jobs
db_password = dbutils.secrets.get(scope="my-app-secrets", key="db-password")
api_key = dbutils.secrets.get(scope="my-app-secrets", key="api-key")

# Secrets are redacted in logs
print(f"Password: {db_password}")  # Shows [REDACTED]

# Use in connection strings
jdbc_url = f"jdbc:postgresql://host:5432/db?user=app&password={db_password}"

Step 4: Secret Scope ACLs

# Grant read access to a user
databricks secrets put-acl my-app-secrets user@company.com READ

# Grant manage access to a group
databricks secrets put-acl my-app-secrets data-engineers MANAGE

# List ACLs
databricks secrets list-acls my-app-secrets

Step 5: Token Management

# src/databricks/tokens.py
from databricks.sdk import WorkspaceClient
from datetime import datetime, timedelta

def audit_tokens(w: WorkspaceClient) -> list[dict]:
    """Audit all tokens in workspace for security review."""
    tokens = list(w.tokens.list())

    token_audit = []
    for token in tokens:
        created = datetime.fromtimestamp(token.creation_time / 1000)
        expiry = datetime.fromtimestamp(token.expiry_time / 1000) if token.expiry_time else None

        token_audit.append({
            "token_id": token.token_id,
            "comment": token.comment,
            "created": created,
            "expires": expiry,
            "days_until_expiry": (expiry - datetime.now()).days if expiry else None,
            "is_expired": expiry < datetime.now() if expiry else False,
            "needs_rotation": expiry and (expiry - datetime.now()).days < 30 if expiry else True,
        })

    return token_audit

def rotate_token(w: WorkspaceClient, old_token_id: str, lifetime_days: int = 90) -> str:
    """Rotate a token by creating new and deleting old."""
    # Create new token
    new_token = w.tokens.create(
        comment=f"Rotated token - {datetime.now().isoformat()}",
        lifetime_seconds=lifetime_days * 24 * 60 * 60,
    )

    # Delete old token
    w.tokens.delete(token_id=old_token_id)

    return new_token.token_value

Step 6: Implement Least Privilege

# Environment-specific permissions
permission_matrix = {
    "development": {
        "cluster_access": "CAN_ATTACH_TO",
        "job_access": "CAN_MANAGE_RUN",
        "notebook_access": "CAN_EDIT",
    },
    "staging": {
        "cluster_access": "CAN_RESTART",
        "job_access": "CAN_MANAGE_RUN",
        "notebook_access": "CAN_READ",
    },
    "production": {
        "cluster_access": "CAN_ATTACH_TO",  # Read-only
        "job_access": "CAN_VIEW",
        "notebook_access": "CAN_READ",
    },
}

def apply_environment_permissions(
    w: WorkspaceClient,
    environment: str,
    user_email: str,
    resource_type: str,
    resource_id: str,
) -> None:
    """Apply environment-appropriate permissions."""
    perms = permission_matrix[environment]

    if resource_type == "cluster":
        w.permissions.update(
            object_type="clusters",
            object_id=resource_id,
            access_control_list=[{
                "user_name": user_email,
                "permission_level": perms["cluster_access"],
            }]
        )

Output

  • Secret scopes configured
  • Secrets stored securely
  • Token rotation procedures
  • Least privilege access

Error Handling

Security IssueDetectionMitigation
Exposed tokenAudit logsImmediate rotation
Excessive scopesPermission auditReduce to minimum
No token expiryToken auditSet 90-day max lifetime
Shared credentialsUsage patternsIndividual service principals

Examples

Security Audit Script

from databricks.sdk import WorkspaceClient

def security_audit(w: WorkspaceClient) -> dict:
    """Run comprehensive security audit."""
    audit_results = {
        "tokens": [],
        "secrets": [],
        "permissions": [],
        "findings": [],
    }

    # Audit tokens
    for token in w.tokens.list():
        if not token.expiry_time:
            audit_results["findings"].append({
                "severity": "HIGH",
                "type": "token_no_expiry",
                "detail": f"Token {token.comment} has no expiration",
            })

    # Audit secret scopes
    for scope in w.secrets.list_scopes():
        acls = list(w.secrets.list_acls(scope=scope.name))
        if not acls:
            audit_results["findings"].append({
                "severity": "MEDIUM",
                "type": "scope_no_acl",
                "detail": f"Scope {scope.name} has no ACLs",
            })

    return audit_results

Service Principal Setup (Azure)

# Create service principal in Azure AD
az ad sp create-for-rbac --name databricks-cicd

# Add to Databricks workspace (Admin Console or SCIM API)
databricks service-principals create \
  --json '{
    "display_name": "CI/CD Pipeline",
    "application_id": "your-azure-app-id"
  }'

# Grant permissions
databricks permissions update jobs --job-id 123 --json '{
  "access_control_list": [{
    "service_principal_name": "your-azure-app-id",
    "permission_level": "CAN_MANAGE"
  }]
}'

Unity Catalog Security

-- Create secure group
CREATE GROUP IF NOT EXISTS `data-scientists`;

-- Grant schema access (not table-level for simplicity)
GRANT USAGE ON CATALOG main TO `data-scientists`;
GRANT USAGE ON SCHEMA main.analytics TO `data-scientists`;
GRANT SELECT ON SCHEMA main.analytics TO `data-scientists`;

-- Audit grants
SHOW GRANTS ON SCHEMA main.analytics;

-- Row-level security
ALTER TABLE main.analytics.customers
SET ROW FILTER customer_region_filter ON (region);

Security Checklist

  • Personal access tokens have expiration dates
  • Secrets stored in Databricks Secret Scopes
  • No hardcoded credentials in notebooks
  • Service principals for automation
  • Unity Catalog for data governance
  • Audit logging enabled
  • Network security (IP access lists)
  • Cluster policies enforced

Resources

Next Steps

For production deployment, see databricks-prod-checklist.