ban_substrings.md

Ban Substrings Scanner

Ensure that specific undesired substrings never make it into your prompts with the BanSubstrings scanner.

How it works

It is purpose-built to screen user prompts, ensuring none of the banned substrings are present. Users have the flexibility to enforce this check at two distinct granularity levels:

• String Level: The banned substring is sought throughout the entire user prompt.

• Word Level: The scanner exclusively hunts for whole words that match the banned substrings, ensuring no individual standalone words from the blacklist appear in the prompt.

Additionally, the scanner can be configured to replace the banned substrings with [REDACT] in the model's output.

Use cases

1. Check that competitors' names are not present in the prompt.

2. Prevent harmful substrings for prompts: prompt_stop_substrings.json.

3. Hide predefined list of URLs you don't want to be mentioned in the prompt.

Usage

from tueri.input_scanners import BanSubstrings
from tueri.input_scanners.ban_substrings import MatchType

competitors_names = [
    "Acorns",
    "Citigroup",
    "Citi",
    "Fidelity Investments",
    "Fidelity",
    "JP Morgan Chase and company",
    "JP Morgan",
    "JP Morgan Chase",
    "JPMorgan Chase",
    "Chase" "M1 Finance",
    "Stash Financial Incorporated",
    "Stash",
    "Tastytrade Incorporated",
    "Tastytrade",
    "ZacksTrade",
    "Zacks Trade",
]

scanner = BanSubstrings(
  substrings=competitors_names,
  match_type=MatchType.STR,
  case_sensitive=False,
  redact=False,
  contains_all=False,
)

sanitized_prompt, is_valid, risk_score = scanner.scan(prompt)

In the above configuration, is_valid will be False if the provided prompt contains any of the banned substrings as whole words. To ban substrings irrespective of their word boundaries, simply change the mode to str.

Benchmarks

Run the following script:

python benchmarks/run.py input BanSubstrings

This scanner uses built-in functions, which makes it fast.