added material

2026-07-26 22:53:03 -04:00
commit 95b1c6bf27
369 changed files with 3468754 additions and 0 deletions
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+# 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}')