Zscaler AI Guard

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Using Zscaler AI Guard with Portkey

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1. Add Zscaler Credentials to Portkey

• Navigate to the Plugins page under Admin Settings
• Click on the edit button for the Zscaler AI Guard integration
• Add your Zscaler AI Guard API Key (the DAS Application Key generated from your Zscaler AI Guard tenant)

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2. Add Zscaler AI Guard Check

• Navigate to the Guardrails page and click the Create button
• Search for “Zscaler AI Guard” and click Add
• Configure your guardrail settings:
  • Policy ID: The ID of the Zscaler Detections Policy to execute (Required)
  • Timeout: The timeout in milliseconds for the scan (Default: 10000)
• Set any actions you want on your check, and create the Guardrail!

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3. Add Guardrail ID to a Config and Make Your Request

• When you save a Guardrail, you’ll get an associated Guardrail ID - add this ID to the input_guardrails or output_guardrails params in your Portkey Config
• Create these Configs in Portkey UI, save them, and get an associated Config ID to attach to your requests. More here.

{
  "input_guardrails": ["guardrails-id-xxx", "guardrails-id-yyy"],
  "output_guardrails": ["guardrails-id-xxx", "guardrails-id-yyy"]
}

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",
    config: "pc-***" // Supports a string config id or a config object
});

portkey = Portkey(
    api_key="PORTKEY_API_KEY",
    config="pc-***" # Supports a string config id or a config object
)

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY',
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    apiKey: "PORTKEY_API_KEY",
    config: "CONFIG_ID"
  })
});

client = OpenAI(
    api_key="OPENAI_API_KEY",
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY",
        config="CONFIG_ID"
    )
)

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-config: $CONFIG_ID" \
  -d '{
    "model": "gpt-5.1-nano",
    "messages": [{
        "role": "user",
        "content": "Hello!"
      }]
  }'

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