added material
This commit is contained in:
@@ -0,0 +1,118 @@
|
||||
# requires openai/anthropic to run; didnt implement those. the script is just for guardrail review so that isnt nessecary
|
||||
|
||||
from pydantic import BaseModel, StringConstraints
|
||||
from typing import Annotated
|
||||
|
||||
class LLMQuery(BaseModel, validate_assignment=True):
|
||||
prompt: Annotated[str, StringConstraints(pattern=r"^[0-9.\+\-\*/\(\)]+$")]
|
||||
response: Annotated[str, StringConstraints(pattern=r"^[0-9\.]+$")] = None
|
||||
|
||||
SYSTEM_PROMPT = '''You are a calculator. Please compute the result of the following mathematical expression.
|
||||
Only respond with the result, no other text.
|
||||
|
||||
'''
|
||||
|
||||
import json
|
||||
|
||||
PRODUCTS = [
|
||||
'SnaccPayload',
|
||||
'PowerChex',
|
||||
'CrunchPacket',
|
||||
'ByteChew',
|
||||
'CryptoChunks'
|
||||
]
|
||||
|
||||
# https://gist.githubusercontent.com/mspublic/f942cb80a83a7880cff689def8334c7b/raw/30527efde9e1d2b11ede9d9bf205d98c2ba9d550/Instruction-Bypass.yara
|
||||
PROMPT_INJECTION_REGEX = r"^.*(Ignore|Disregard|Skip|Forget|Neglect|Overlook|Omit|Bypass)\s*(prior|previous|preceding|above|foregoing|earlier|initial)?\s*(content|text|instructions|instruction|directives|directive|commands|command).*$"
|
||||
|
||||
# https://gist.githubusercontent.com/mspublic/f942cb80a83a7880cff689def8334c7b/raw/30527efde9e1d2b11ede9d9bf205d98c2ba9d550/jailbreaks.json
|
||||
JAILBREAKS = json.load(open('./jailbreaks.json')).get('jailbreak')
|
||||
|
||||
# check if any item in the passed list is contained in the passed string
|
||||
def list_check(list, string):
|
||||
return any(item in string for item in list)
|
||||
|
||||
# detect jailbreak based on string similarity
|
||||
from difflib import SequenceMatcher
|
||||
def jailbreak_detect(prompt, jailbreak_threshold=0.5):
|
||||
return any(SequenceMatcher(None, jailbreak, prompt).ratio() > jailbreak_threshold for jailbreak in JAILBREAKS)
|
||||
|
||||
class GuardrailPromptException(Exception):
|
||||
pass
|
||||
|
||||
class GuardrailResponseException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
from pydantic import BaseModel, field_validator
|
||||
import re
|
||||
|
||||
class LLMQuery(BaseModel, validate_assignment=True):
|
||||
prompt: str
|
||||
response: str = None
|
||||
|
||||
@field_validator("prompt")
|
||||
@classmethod
|
||||
def validate_prompt(cls, prompt: str) -> str:
|
||||
prompt = prompt.strip()
|
||||
|
||||
# Check for PacketSnacc product
|
||||
if not list_check(PRODUCTS, prompt):
|
||||
raise GuardrailPromptException("No PacketSnacc product mentioned in user prompt.")
|
||||
|
||||
# Check for prompt injection
|
||||
if re.search(PROMPT_INJECTION_REGEX, prompt, re.IGNORECASE):
|
||||
raise GuardrailPromptException("Prompt injection attempt detected.")
|
||||
|
||||
# Check for jailbreaking
|
||||
if jailbreak_detect(prompt):
|
||||
raise GuardrailPromptException("Jailbreak attempt detected.")
|
||||
|
||||
return prompt
|
||||
|
||||
@field_validator("response")
|
||||
@classmethod
|
||||
def validate_response(cls, response: str) -> str:
|
||||
# Check for competitors
|
||||
if list_check(COMPETITORS, response):
|
||||
raise GuardrailResponseException("Output does not satisfy company policy.")
|
||||
|
||||
# Check for profanity
|
||||
if list_check(PROFANITY, response):
|
||||
raise GuardrailResponseException("Profane language detected.")
|
||||
|
||||
# Check for credit card information
|
||||
if re.search(r"^.*[0-9]{13,19}.*$", response):
|
||||
raise GuardrailResponseException("Information leakage detected.")
|
||||
|
||||
# Remove HTML-Tags
|
||||
response = re.sub(r"<.*?>", "", response)
|
||||
|
||||
return response
|
||||
|
||||
COMPETITORS = [
|
||||
"SnackOverflow",
|
||||
"NullBite",
|
||||
"CyberChow"
|
||||
]
|
||||
|
||||
# https://raw.githubusercontent.com/zacanger/profane-words/refs/heads/master/words.json
|
||||
PROFANITY = json.load(open('./words.json'))
|
||||
|
||||
def query_llm(system_prompt:str, prompt: str) -> str:
|
||||
# openai/anthorpic etc; not relevent
|
||||
return response
|
||||
|
||||
def protected_query_llm(prompt: str) -> LLMQuery:
|
||||
query = LLMQuery(prompt=prompt)
|
||||
query.response = query_llm(SYSTEM_PROMPT, query.prompt)
|
||||
return query
|
||||
|
||||
|
||||
while 1:
|
||||
try:
|
||||
prompt = input("> ")
|
||||
query_obj = protected_query_llm(prompt)
|
||||
print(query_obj.response)
|
||||
except Exception as e:
|
||||
print(f'Error: {e}')
|
||||
Reference in New Issue
Block a user