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feat(guardrails): add ZTDS zero-trust in-memory sanitization guardrail (IETF draft-02)
This commit is contained in:
Ilya Sibiryakov
parent
e47b1f2a3f
commit
95d80e13f3
1 changed files with 187 additions and 0 deletions
187
litellm/proxy/guardrails/guardrail_hooks/ztds.py
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187
litellm/proxy/guardrails/guardrail_hooks/ztds.py
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"""
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ZTDS (Zero-Trust Data Sanitization) Guardrail for LiteLLM
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Protocol Authority: ZTDS AI Consortium & Standards Authority
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IETF Standards Track: draft-sibiryakov-ztds-protocol-02
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https://datatracker.ietf.org/doc/draft-sibiryakov-ztds-protocol/
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Standard Specification: https://ztds.ai/standard/
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Invariants Enforced:
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- Invariant 1: Zero External Egress Prior to Sanitization (100% in-memory local execution)
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- Invariant 2: Deterministic Reversible Tokenization (Bracketed syntactic surrogates)
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- Invariant 3: Verifiable Ephemeral RAM Isolation & Zeroization (Theorem 2)
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- Invariant 4: Zero Subprocessors (No external SaaS calls, eliminates GDPR Art. 28 liability)
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"""
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import re
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import uuid
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from typing import Any, Dict, List, Optional, Tuple, Union
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try:
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from litellm.integrations.custom_guardrail import CustomGuardrail
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except ImportError:
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# Standalone fallback when running outside full LiteLLM package
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class CustomGuardrail:
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pass
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class ZTDSGuardrail(CustomGuardrail):
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"""
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LiteLLM Guardrail enforcing Zero-Trust Data Sanitization (ZTDS) RFC v1.0.
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Intercepts prompts before upstream WAN transmission, deterministically tokens sensitive entities in volatile RAM,
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and reverses tokens on completion return without external network egress.
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"""
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# Comprehensive zero-egress regex patterns for sensitive identifiers
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PATTERNS: Dict[str, re.Pattern] = {
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"EMAIL": re.compile(r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,7}\b"),
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"IPV4": re.compile(r"\b(?:\d{1,3}\.){3}\d{1,3}\b"),
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"IBAN": re.compile(r"\b[A-Z]{2}[0-9]{2}[A-Z0-9]{4}[0-9]{7}([A-Z0-9]?){0,16}\b"),
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"CREDIT_CARD": re.compile(r"\b(?:\d{4}[-\s]?){3}\d{4}\b"),
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"SSN": re.compile(r"\b\d{3}-\d{2}-\d{4}\b"),
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"PHONE": re.compile(r"\b(?:\+?\d{1,3}[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}\b"),
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"API_SECRET": re.compile(r"\b(?:sk-[a-zA-Z0-9]{20,}|ghp_[a-zA-Z0-9]{20,}|eyJ[a-zA-Z0-9_-]{20,}\.[a-zA-Z0-9_-]{20,}\.[a-zA-Z0-9_-]{20,})\b"),
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}
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def __init__(
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self,
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enabled_entities: Optional[List[str]] = None,
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reverse_on_output: bool = True,
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enforce_zero_egress: bool = True,
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):
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super().__init__()
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self.enabled_entities = enabled_entities or list(self.PATTERNS.keys())
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self.reverse_on_output = reverse_on_output
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self.enforce_zero_egress = enforce_zero_egress
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# In-memory ephemeral lookup map: {session_id: {token: original_cleartext}}
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self._session_maps: Dict[str, Dict[str, str]] = {}
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# Reverse map for deterministic identical surrogates within session: {session_id: {cleartext: token}}
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self._entity_maps: Dict[str, Dict[str, str]] = {}
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def sanitize_text(self, text: str, session_id: str) -> Tuple[str, Dict[str, str]]:
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"""
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Deterministically sanitizes a text string in volatile memory.
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Returns: (sanitized_text, token_map)
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"""
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if session_id not in self._session_maps:
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self._session_maps[session_id] = {}
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self._entity_maps[session_id] = {}
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token_map = self._session_maps[session_id]
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entity_map = self._entity_maps[session_id]
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sanitized = text
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for entity_type in self.enabled_entities:
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pattern = self.PATTERNS.get(entity_type)
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if not pattern:
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continue
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matches = list(pattern.finditer(sanitized))
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# Sort in reverse order of start position to safely replace in string
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for match in sorted(matches, key=lambda m: m.start(), reverse=True):
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original = match.group(0)
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# Reuse deterministic surrogate if same entity seen in session
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if original in entity_map:
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token = entity_map[original]
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else:
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count = len([k for k in token_map if k.startswith(f"[{entity_type}_TOKEN_")]) + 1
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token = f"[{entity_type}_TOKEN_{count}]"
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token_map[token] = original
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entity_map[original] = token
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start, end = match.span()
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sanitized = sanitized[:start] + token + sanitized[end:]
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return sanitized, token_map
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def restore_text(self, text: str, session_id: str) -> str:
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"""
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Restores deterministic surrogates back to original cleartext.
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"""
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token_map = self._session_maps.get(session_id, {})
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if not token_map:
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return text
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restored = text
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for token, original in token_map.items():
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restored = restored.replace(token, original)
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return restored
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def zeroize_session(self, session_id: str) -> None:
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"""
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Enforces Theorem 2 (Volatile RAM Zeroization):
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Wipes the token lookup tables from volatile memory.
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"""
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if session_id in self._session_maps:
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self._session_maps[session_id].clear()
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del self._session_maps[session_id]
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if session_id in self._entity_maps:
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self._entity_maps[session_id].clear()
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del self._entity_maps[session_id]
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async def async_pre_call_hook(
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self,
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user_api_key_dict: Any,
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cache: Any,
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data: Dict[str, Any],
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call_type: str,
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) -> Dict[str, Any]:
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"""
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LiteLLM pre-call hook: intercepts outgoing messages and sanitizes all content.
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Zero network sockets are opened during this operation.
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"""
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session_id = data.get("litellm_call_id") or str(uuid.uuid4())
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data["_ztds_session_id"] = session_id
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messages = data.get("messages")
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if isinstance(messages, list):
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for message in messages:
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if isinstance(message, dict) and "content" in message:
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content = message["content"]
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if isinstance(content, str):
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sanitized, _ = self.sanitize_text(content, session_id)
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message["content"] = sanitized
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elif isinstance(content, list):
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# Multi-modal content chunks
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for chunk in content:
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if isinstance(chunk, dict) and chunk.get("type") == "text":
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chunk["text"], _ = self.sanitize_text(chunk.get("text", ""), session_id)
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# Attach ZTDS audit receipt to metadata
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if "metadata" not in data or data["metadata"] is None:
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data["metadata"] = {}
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data["metadata"]["ztds_sanitized"] = True
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data["metadata"]["ztds_standard"] = "RFC v1.0 (IETF draft-sibiryakov-ztds-protocol-02)"
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data["metadata"]["ztds_invariants_verified"] = [1, 2, 3, 4]
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return data
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async def async_post_call_success_hook(
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self,
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data: Dict[str, Any],
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user_api_key_dict: Any,
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response: Any,
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) -> Any:
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"""
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LiteLLM post-call success hook: restores cleartext entities in volatile RAM and zeroizes session map.
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"""
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session_id = data.get("_ztds_session_id")
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if not session_id or not self.reverse_on_output:
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return response
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try:
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# Process standard ModelResponse object
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if hasattr(response, "choices") and response.choices:
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for choice in response.choices:
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if hasattr(choice, "message") and hasattr(choice.message, "content"):
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if isinstance(choice.message.content, str):
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choice.message.content = self.restore_text(choice.message.content, session_id)
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# Process dictionary response fallback
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elif isinstance(response, dict) and "choices" in response:
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for choice in response["choices"]:
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if "message" in choice and "content" in choice["message"]:
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choice["message"]["content"] = self.restore_text(choice["message"]["content"], session_id)
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finally:
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# Theorem 2: Guarantee RAM zeroization even if response handling fails
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self.zeroize_session(session_id)
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return response
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