| Developed by | Guardrails AI | | Date of development | Feb 15, 2024 | | Validator type | Safety | | Blog | | | License | Apache 2 | | Input/Output | Input, Output |

This validator monitors any text (input or output) and detects secrets present in the text. Under-the-hood, the validator uses the detect-secrets library to check whether the text contains any secrets. If any secrets are detected, the validator fails and returns the text with the secrets replaced with asterisks. Otherwise, the validator returns the generated code snippet.

• Dependencies:
  • guardrails-ai>=0.4.0
  • detect-secrets

$ guardrails hub install hub://guardrails/secrets_present

In this example, we apply the validator to a string output generated by an LLM.

# Import Guard and Validator
from guardrails import Guard
from guardrails.hub import SecretsPresent

# Setup Guard
guard = Guard().use(
    SecretsPresent(on_fail="exception")
)

response = guard.validate(
    """
    def hello():
        name = "James"
        age = 25
        return {"name": name, "age": age}
    """
)  # Validator passes

try:
    response = guard.validate(
        """
        def hello():
            user_id = "1234"
            user_pwd = "password1234"
            user_api_key = "sk-xhdfgtest"
        """
    )  # Validator fails
except Exception as e:
    print(e)

Output:

Validation failed for field with errors: The following secrets were detected in your response:
password1234
sk-xhdfgtest

__init__(self, on_fail="noop")

Initializes a new instance of the Validator class.

Parameters

• on_fail (str, Callable): The policy to enact when a validator fails. If str, must be one of reask, fix, filter, refrain, noop, exception or fix_reask. Otherwise, must be a function that is called when the validator fails.

__call__(self, value, metadata={}) -> ValidationOutcome

Validates the given `value` using the rules defined in this validator, relying on the `metadata` provided to customize the validation process. This method is automatically invoked by `guard.parse(...)`, ensuring the validation logic is applied to the input data.

Note:

1. This method should not be called directly by the user. Instead, invoke guard.parse(...) where this method will be called internally for each associated Validator.
2. When invoking guard.parse(...), ensure to pass the appropriate metadata dictionary that includes keys and values required by this validator. If guard is associated with multiple validators, combine all necessary metadata into a single dictionary.

Parameters

• value (Any): The input value to validate.
• metadata (dict): A dictionary containing metadata required for validation. No additional metadata keys are needed for this validator.