AI Guard API Reference

Base URL

ai-guard.<csp>.<region>.pangea.cloud

• OpenAPI Specification

post/v1beta/text/guard

cURL

Code Snippet Language

curl -sSLX POST 'https://ai-guard.aws.us.pangea.cloud/v1beta/text/guard' \
-H 'Authorization: Bearer <your_token>' \
-H 'Content-Type: application/json' \
-d '{}'

Response

Raw Output

200

Code Snippet Language

---

Text Guard for scanning LLM inputs and outputs

POST

https://ai-guard.aws.us.pangea.cloud/v1beta/text/guard

Analyze and redact text to avoid manipulation of the model, addition of malicious content, and other undesirable data transfers.

required parameters

text

string

Text to be scanned by AI Guard for PII, sensitive data, malicious content, and other data types defined by the configuration. Supports processing up to 10KB of text.

text

text

optional parameters

messages

Structured data to be scanned by AI Guard for PII, sensitive data, malicious content, and other data types defined by the configuration. Supports processing up to 10KB of text.

messages

messages

recipe

string

(default: "pangea_prompt_guard")

Recipe key of a configuration of data types and settings defined in the Pangea User Console. It specifies the rules that are to be applied to the text, such as defang malicious URLs.

recipe

recipe

debug

boolean

(default: false)

Setting this value to true will provide a detailed analysis of the text data

debug

​

debug

overrides

object

prompt_injection

object

action

string

action

​

action

malicious_entity

object

ip_address_action

string

ip_address_action

​

ip_address_action

url_action

string

url_action

​

url_action

domain_action

string

domain_action

​

domain_action

Response Fields

Response Schema

object

Pangea standard response schema

result

object

prompt_text

string

Updated prompt text, if applicable.

prompt_messages

object

Updated structured prompt, if applicable.

detectors

object

Result of the recipe analyzing and input prompt.

prompt_injection

object

detected

boolean

Whether or not the Prompt Injection was detected.

data

object

Details about the analyzers.

analyzer_responses

array<object>

Triggered prompt injection analyzers.

analyzer

string

confidence

number

pii_entity

object

detected

boolean

Whether or not the PII Entities were detected.

data

object

Details about the detected entities.

entities

array<object>

Detected redaction rules.

type

string

value

string

redacted

boolean

start_pos

number

malicious_entity

object

detected

boolean

Whether or not the Malicious Entities were detected.

data

object

Details about the detected entities.

entities

array<object>

Detected harmful items.

type

string

value

string

redacted

boolean

start_pos

number

raw

object

custom_entity

object

detected

boolean

Whether or not the Custom Entities were detected.

data

object

Details about the detected entities.

entities

array<object>

Detected redaction rules.

type

string

value

string

redacted

boolean

start_pos

number

secrets_detection

object

detected

boolean

Whether or not the Secret Entities were detected.

data

object

Details about the detected entities.

entities

array<object>

Detected redaction rules.

type

string

value

string

redacted

boolean

start_pos

number

profanity_and_toxicity

object

detected

boolean

Whether or not the Toxic Entities were detected.

data

object

Details about the detected entities.

entities

array<object>

Detected redaction rules.

type

string

value

string

redacted

boolean

start_pos

number

language_detection

object

detected

boolean

Whether or not the Languages were detected.

data

object

Details about the detected languages.

language

string

fpe_context

string (base64)

If an FPE redaction method returned results, this will be the context passed to unredact.

request_id

string

A unique identifier assigned to each request made to the API. It is used to track and identify a specific request and its associated data. The request_id can be helpful for troubleshooting, auditing, and tracing the flow of requests within the system. It allows users to reference and retrieve information related to a particular request, such as the response, parameters, and raw data associated with that specific request.

"request_id":"prq_x6fdiizbon6j3bsdvnpmwxsz2aan7fqd"

request_time

string

The timestamp indicates the exact moment when a request is made to the API. It represents the date and time at which the request was initiated by the client. The request_time is useful for tracking and analyzing the timing of requests, measuring response times, and monitoring performance metrics. It allows users to determine the duration between the request initiation and the corresponding response, aiding in the assessment of API performance and latency.

"request_time":"2022-09-21T17:24:33.105Z"

response_time

string

Duration it takes for the API to process a request and generate a response. It represents the elapsed time from when the request is received by the API to when the corresponding response is returned to the client.

"response_time":"2022-09-21T17:24:34.007Z"

status

string

It represents the status or outcome of the API request made for IP information. It indicates the current state or condition of the request and provides information on the success or failure of the request.

"status":"success"

summary

string

Provides a concise and brief overview of the purpose or primary objective of the API endpoint. It serves as a high-level summary or description of the functionality or feature offered by the endpoint.

Status Codes

Status	Status Code	Description
AIGBadInputFormat	400	The input schema is not currently supported.
AIGFileTooLarge	400	File size too large.
AIGInvalidRecipe	400	Recipe contains invalid contents.
AIGMissingSvConnection	400	A service dependency was not set up.
NoProviderConfigured	400	Provider for intelligence services used by ai-guard is not configured
RecipeNotExist	400	Recipe does not exist in the ai-guard configuration

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