diff --git a/docs/my-website/docs/proxy/guardrails/grayswan.md b/docs/my-website/docs/proxy/guardrails/grayswan.md
index 7cc75b9f3b..d6efaf1550 100644
--- a/docs/my-website/docs/proxy/guardrails/grayswan.md
+++ b/docs/my-website/docs/proxy/guardrails/grayswan.md
@@ -73,6 +73,17 @@ Gray Swan can run during `pre_call`, `during_call`, and `post_call` stages. Comb
 | `during_call`| Parallel to call  | User input only       | Low-latency monitoring without blocking |
 | `post_call`  | After response    | Full conversation     | Scan output for policy violations, leaked secrets, or IPI |
 
+
+When using `during_call` with `on_flagged_action: block` or `on_flagged_action: passthrough`:
+
+- **The LLM call runs in parallel** with the guardrail check using `asyncio.gather`
+- **LLM tokens are still consumed** even if the guardrail detects a violation
+- The guardrail exception prevents the response from reaching the user, but **does not cancel the running LLM task**
+- This means you pay full LLM costs while returning an error/passthrough message to the user
+
+**Recommendation:** For cost-sensitive applications, use `pre_call` and `post_call` instead of `during_call` for blocking or passthrough modes. Reserve `during_call` for `monitor` mode where you want low-latency logging without impacting the user experience.
+
+
 <Tabs>
 <TabItem value="monitor" label="Monitor Only">
 
@@ -131,6 +142,24 @@ guardrails:
 
 Provides the strongest enforcement by inspecting both prompts and responses.
 
+</TabItem>
+<TabItem value="passthrough" label="Passthrough Mode">
+
+```yaml
+guardrails:
+  - guardrail_name: "cygnal-passthrough"
+    litellm_params:
+      guardrail: grayswan
+      mode: [pre_call, post_call]
+      api_key: os.environ/GRAYSWAN_API_KEY
+      optional_params:
+        on_flagged_action: passthrough
+        violation_threshold: 0.5
+      default_on: true
+```
+
+Allows requests to proceed without raising a 400 error when content is flagged. Instead of blocking, the model response content is replaced with a detailed violation message including violation score, violated rules, and detection flags (mutation, IPI). **Supported Response Formats:** OpenAI chat/text completions, Anthropic Messages API. Other response types (embeddings, images, etc.) will log a warning and return unchanged.
+
 </TabItem>
 </Tabs>
 
@@ -142,7 +171,7 @@ Provides the strongest enforcement by inspecting both prompts and responses.
 |---------------------------------------|-----------------|-------------|
 | `api_key`                             | string          | Gray Swan Cygnal API key. Reads from `GRAYSWAN_API_KEY` if omitted. |
 | `mode`                                | string or list  | Guardrail stages (`pre_call`, `during_call`, `post_call`). |
-| `optional_params.on_flagged_action`   | string          | `monitor` (log only), `block` (raise `HTTPException`), or `passthrough` (include detection info in response without blocking). |
+| `optional_params.on_flagged_action`   | string          | `monitor` (log only), `block` (raise `HTTPException`), or `passthrough` (replace response content with violation message, no 400 error). |
 | `.optional_params.violation_threshold`| number (0-1)    | Scores at or above this value are considered violations. |
 | `optional_params.reasoning_mode`      | string          | `off`, `hybrid`, or `thinking`. Enables Cygnal's reasoning capabilities. |
 | `optional_params.categories`          | object          | Map of custom category names to descriptions. |
diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py
index bb5883dd47..51f7933422 100644
--- a/litellm/integrations/custom_guardrail.py
+++ b/litellm/integrations/custom_guardrail.py
@@ -35,6 +35,45 @@ if TYPE_CHECKING:
 dc = DualCache()
 
 
+class ModifyResponseException(Exception):
+    """
+    Exception raised when a guardrail wants to modify the response.
+
+    This exception carries the synthetic response that should be returned
+    to the user instead of calling the LLM or instead of the LLM's response.
+    It should be caught by the proxy and returned with a 200 status code.
+
+    This is a base exception that all guardrails can use to replace responses,
+    allowing violation messages to be returned as successful responses
+    rather than errors.
+    """
+
+    def __init__(
+        self,
+        message: str,
+        model: str,
+        request_data: Dict[str, Any],
+        guardrail_name: Optional[str] = None,
+        detection_info: Optional[Dict[str, Any]] = None,
+    ):
+        """
+        Initialize the modify response exception.
+
+        Args:
+            message: The violation message to return to the user
+            model: The model that was being called
+            request_data: The original request data
+            guardrail_name: Name of the guardrail that raised this exception
+            detection_info: Additional detection metadata (scores, rules, etc.)
+        """
+        self.message = message
+        self.model = model
+        self.request_data = request_data
+        self.guardrail_name = guardrail_name
+        self.detection_info = detection_info or {}
+        super().__init__(message)
+
+
 class CustomGuardrail(CustomLogger):
     def __init__(
         self,
@@ -96,6 +135,50 @@ class CustomGuardrail(CustomLogger):
             )
             return default
 
+    def raise_passthrough_exception(
+        self,
+        violation_message: str,
+        request_data: Dict[str, Any],
+        detection_info: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """
+        Raise a passthrough exception for guardrail violations.
+
+        This helper method should be used by guardrails when they detect a violation
+        in passthrough mode.
+
+        The exception will be caught by the proxy endpoints and converted to a 200 response
+        with the violation message, preventing the LLM call from being made (pre_call/during_call)
+        or replacing the LLM response (post_call).
+
+        Args:
+            violation_message: The formatted violation message to return to the user
+            request_data: The original request data dictionary
+            detection_info: Optional dictionary with detection metadata (scores, rules, etc.)
+
+        Raises:
+            ModifyResponseException: Always raises this exception to short-circuit
+                                     the LLM call and return the violation message
+
+        Example:
+            if violation_detected and self.on_flagged_action == "passthrough":
+                message = self._format_violation_message(detection_info)
+                self.raise_passthrough_exception(
+                    violation_message=message,
+                    request_data=data,
+                    detection_info=detection_info
+                )
+        """
+        model = request_data.get("model", "unknown")
+
+        raise ModifyResponseException(
+            message=violation_message,
+            model=model,
+            request_data=request_data,
+            guardrail_name=self.guardrail_name,
+            detection_info=detection_info,
+        )
+
     @staticmethod
     def get_config_model() -> Optional[Type["GuardrailConfigModel"]]:
         """
diff --git a/litellm/proxy/anthropic_endpoints/endpoints.py b/litellm/proxy/anthropic_endpoints/endpoints.py
index 3317560904..53d9bf756f 100644
--- a/litellm/proxy/anthropic_endpoints/endpoints.py
+++ b/litellm/proxy/anthropic_endpoints/endpoints.py
@@ -8,6 +8,7 @@ from fastapi import APIRouter, Depends, HTTPException, Request, Response
 from litellm._logging import verbose_proxy_logger
 from litellm.proxy._types import *
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.integrations.custom_guardrail import ModifyResponseException
 from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
 from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
 from litellm.types.utils import TokenCountResponse
@@ -65,6 +66,50 @@ async def anthropic_response(  # noqa: PLR0915
             version=version,
         )
         return result
+    except ModifyResponseException as e:
+        # Guardrail flagged content in passthrough mode - return 200 with violation message
+        _data = e.request_data
+        await proxy_logging_obj.post_call_failure_hook(
+            user_api_key_dict=user_api_key_dict,
+            original_exception=e,
+            request_data=_data,
+        )
+
+        # Create Anthropic-formatted response with violation message
+        import uuid
+        from litellm.types.utils import AnthropicMessagesResponse
+
+        _anthropic_response = AnthropicMessagesResponse(
+            id=f"msg_{str(uuid.uuid4())}",
+            type="message",
+            role="assistant",
+            content=[{"type": "text", "text": e.message}],
+            model=e.model,
+            stop_reason="end_turn",
+            usage={"input_tokens": 0, "output_tokens": 0},
+        )
+
+        if data.get("stream", None) is not None and data["stream"] is True:
+            # For streaming, use the standard SSE data generator
+            async def _passthrough_stream_generator():
+                yield _anthropic_response
+
+            selected_data_generator = (
+                ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+                    response=_passthrough_stream_generator(),
+                    user_api_key_dict=user_api_key_dict,
+                    request_data=_data,
+                    proxy_logging_obj=proxy_logging_obj,
+                )
+            )
+
+            return await create_streaming_response(
+                generator=selected_data_generator,
+                media_type="text/event-stream",
+                headers={},
+            )
+
+        return _anthropic_response
     except Exception as e:
         await proxy_logging_obj.post_call_failure_hook(
             user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
diff --git a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
index 7f9f900a5a..a1cab09209 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
@@ -147,7 +147,7 @@ class GraySwanGuardrail(CustomGuardrail):
             )
             return data
 
-        await self.run_grayswan_guardrail(payload, data)
+        await self.run_grayswan_guardrail(payload, data, GuardrailEventHooks.pre_call)
         add_guardrail_to_applied_guardrails_header(
             request_data=data, guardrail_name=self.guardrail_name
         )
@@ -193,7 +193,9 @@ class GraySwanGuardrail(CustomGuardrail):
             )
             return data
 
-        await self.run_grayswan_guardrail(payload, data)
+        await self.run_grayswan_guardrail(
+            payload, data, GuardrailEventHooks.during_call
+        )
         add_guardrail_to_applied_guardrails_header(
             request_data=data, guardrail_name=self.guardrail_name
         )
@@ -240,23 +242,57 @@ class GraySwanGuardrail(CustomGuardrail):
             )
             return response
 
-        await self.run_grayswan_guardrail(payload, data)
+        await self.run_grayswan_guardrail(payload, data, GuardrailEventHooks.post_call)
 
-        # If passthrough mode and detection info exists, add it to response
+        # If passthrough mode and detection info exists, replace response content with violation message
         if self.on_flagged_action == "passthrough" and "metadata" in data:
             guardrail_detections = data.get("metadata", {}).get(
                 "guardrail_detections", []
             )
             if guardrail_detections:
-                # Add guardrail detections to response hidden params for client visibility
-                hidden_params = getattr(response, "_hidden_params", None)
-                if hidden_params is not None:
-                    if not hidden_params:
-                        hidden_params = {}
-                        setattr(response, "_hidden_params", hidden_params)
+                # Replace the model response content with guardrail violation message
+                violation_message = self._format_violation_message(
+                    guardrail_detections, is_output=True
+                )
 
-                    hidden_params["guardrail_detections"] = guardrail_detections
-                    setattr(response, "_hidden_params", hidden_params)
+                # Handle ModelResponse (OpenAI-style chat/text completions)
+                if hasattr(response, "choices") and response.choices:
+                    verbose_proxy_logger.debug(
+                        "Gray Swan Guardrail: Replacing response content in ModelResponse format"
+                    )
+                    for choice in response.choices:
+                        # Handle chat completion format (message.content)
+                        if hasattr(choice, "message") and hasattr(
+                            choice.message, "content"
+                        ):
+                            choice.message.content = violation_message
+                        # Handle text completion format (text)
+                        elif hasattr(choice, "text"):
+                            choice.text = violation_message
+
+                        # Update finish_reason to indicate content filtering
+                        if hasattr(choice, "finish_reason"):
+                            choice.finish_reason = "content_filter"
+
+                # Handle AnthropicMessagesResponse format
+                elif hasattr(response, "content") and isinstance(response.content, list):  # type: ignore
+                    verbose_proxy_logger.debug(
+                        "Gray Swan Guardrail: Replacing response content in Anthropic Messages format"
+                    )
+                    # Replace content blocks with text block containing violation message
+                    response.content = [  # type: ignore
+                        {"type": "text", "text": violation_message}
+                    ]
+                    # Update stop_reason if present
+                    if hasattr(response, "stop_reason"):
+                        response.stop_reason = "end_turn"  # type: ignore
+
+                else:
+                    verbose_proxy_logger.warning(
+                        "Gray Swan Guardrail: Passthrough mode enabled but response format not recognized. "
+                        "Cannot replace content. Response type: %s",
+                        type(response).__name__,
+                    )
 
         add_guardrail_to_applied_guardrails_header(
             request_data=data, guardrail_name=self.guardrail_name
@@ -267,7 +303,12 @@ class GraySwanGuardrail(CustomGuardrail):
     # Core GraySwan interaction
     # ------------------------------------------------------------------
 
-    async def run_grayswan_guardrail(self, payload: dict, data: Optional[dict] = None):
+    async def run_grayswan_guardrail(
+        self,
+        payload: dict,
+        data: Optional[dict] = None,
+        hook_type: Optional[GuardrailEventHooks] = None,
+    ):
         headers = self._prepare_headers()
 
         try:
@@ -290,7 +331,7 @@ class GraySwanGuardrail(CustomGuardrail):
             )
             raise GraySwanGuardrailAPIError(str(exc)) from exc
 
-        self._process_grayswan_response(result, data)
+        self._process_grayswan_response(result, data, hook_type)
 
     # ------------------------------------------------------------------
     # Helpers
@@ -324,7 +365,10 @@ class GraySwanGuardrail(CustomGuardrail):
         return payload
 
     def _process_grayswan_response(
-        self, response_json: Dict[str, Any], data: Optional[dict] = None
+        self,
+        response_json: Dict[str, Any],
+        data: Optional[dict] = None,
+        hook_type: Optional[GuardrailEventHooks] = None,
     ) -> None:
         violation_score = float(response_json.get("violation", 0.0) or 0.0)
         violated_rules = response_json.get("violated_rules", [])
@@ -347,10 +391,17 @@ class GraySwanGuardrail(CustomGuardrail):
         )
 
         if self.on_flagged_action == "block":
+            # Determine if violation was in input or output
+            violation_location = (
+                "output"
+                if hook_type == GuardrailEventHooks.post_call
+                else "input"
+            )
             raise HTTPException(
                 status_code=400,
                 detail={
                     "error": "Blocked by Gray Swan Guardrail",
+                    "violation_location": violation_location,
                     "violation": violation_score,
                     "violated_rules": violated_rules,
                     "mutation": mutation_detected,
@@ -362,26 +413,90 @@ class GraySwanGuardrail(CustomGuardrail):
                 "Gray Swan Guardrail: Monitoring mode - allowing flagged content to proceed"
             )
         elif self.on_flagged_action == "passthrough":
+            # Store detection info
+            detection_info = {
+                "guardrail": "grayswan",
+                "flagged": True,
+                "violation_score": violation_score,
+                "violated_rules": violated_rules,
+                "mutation": mutation_detected,
+                "ipi": ipi_detected,
+            }
+
+            # For pre_call and during_call, raise exception to short-circuit LLM call
+            if hook_type in (
+                GuardrailEventHooks.pre_call,
+                GuardrailEventHooks.during_call,
+            ):
+                verbose_proxy_logger.info(
+                    "Gray Swan Guardrail: Passthrough mode - raising exception to short-circuit LLM call"
+                )
+                violation_message = self._format_violation_message(
+                    [detection_info], is_output=False
+                )
+                self.raise_passthrough_exception(
+                    violation_message=violation_message,
+                    request_data=data or {},
+                    detection_info=detection_info,
+                )
+
+            # For post_call, store in metadata to replace response later
             verbose_proxy_logger.info(
                 "Gray Swan Guardrail: Passthrough mode - storing detection info in metadata"
             )
             if data is not None:
-                # Store guardrail detection info in metadata to be included in response
                 if "metadata" not in data:
                     data["metadata"] = {}
                 if "guardrail_detections" not in data["metadata"]:
                     data["metadata"]["guardrail_detections"] = []
-
-                detection_info = {
-                    "guardrail": "grayswan",
-                    "flagged": True,
-                    "violation_score": violation_score,
-                    "violated_rules": violated_rules,
-                    "mutation": mutation_detected,
-                    "ipi": ipi_detected,
-                }
                 data["metadata"]["guardrail_detections"].append(detection_info)
 
+    def _format_violation_message(
+        self, guardrail_detections: list, is_output: bool = False
+    ) -> str:
+        """
+        Format guardrail detections into a user-friendly violation message.
+
+        Args:
+            guardrail_detections: List of detection info dictionaries
+            is_output: True if violation is in model output (post_call), False if in input (pre_call/during_call)
+
+        Returns:
+            Formatted violation message string
+        """
+        if not guardrail_detections:
+            return "Content was flagged by guardrail"
+
+        # Get the most recent detection (should be from this guardrail)
+        detection = guardrail_detections[-1]
+
+        violation_score = detection.get("violation_score", 0.0)
+        violated_rules = detection.get("violated_rules", [])
+        mutation = detection.get("mutation", False)
+        ipi = detection.get("ipi", False)
+
+        # Indicate whether violation was in input or output
+        violation_location = "the model response" if is_output else "input query"
+
+        message_parts = [
+            f"Sorry I can't help with that. According to the Gray Swan Cygnal Guardrail, the {violation_location} has a violation score of {violation_score:.2f}.",
+        ]
+
+        if violated_rules:
+            message_parts.append(
+                f"It was violating the rule(s): {', '.join(map(str, violated_rules))}."
+            )
+
+        if mutation:
+            message_parts.append(
+                "Mutation effort to make the harmful intention disguised was DETECTED."
+            )
+
+        if ipi:
+            message_parts.append("Indirect Prompt Injection was DETECTED.")
+
+        return "\n".join(message_parts)
+
     def _resolve_threshold(self, threshold: Optional[float]) -> float:
         if threshold is not None:
             return min(max(threshold, 0.0), 1.0)
diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 6aef4ab493..19cdbf225b 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -171,6 +171,7 @@ from litellm.constants import (
 )
 from litellm.exceptions import RejectedRequestError
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.integrations.custom_guardrail import ModifyResponseException
 from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting
 from litellm.litellm_core_utils.core_helpers import (
     _get_parent_otel_span_from_kwargs,
@@ -4945,6 +4946,43 @@ async def chat_completion(  # noqa: PLR0915
             return model_dump_with_preserved_fields(result, exclude_unset=True)
         else:
             return result
+    except ModifyResponseException as e:
+        # Guardrail flagged content in passthrough mode - return 200 with violation message
+        _data = e.request_data
+        await proxy_logging_obj.post_call_failure_hook(
+            user_api_key_dict=user_api_key_dict,
+            original_exception=e,
+            request_data=_data,
+        )
+        _chat_response = litellm.ModelResponse()
+        _chat_response.model = e.model  # type: ignore
+        _chat_response.choices[0].message.content = e.message  # type: ignore
+        _chat_response.choices[0].finish_reason = "content_filter"  # type: ignore
+
+        if data.get("stream", None) is not None and data["stream"] is True:
+            _iterator = litellm.utils.ModelResponseIterator(
+                model_response=_chat_response, convert_to_delta=True
+            )
+            _streaming_response = litellm.CustomStreamWrapper(
+                completion_stream=_iterator,
+                model=e.model,
+                custom_llm_provider="cached_response",
+                logging_obj=data.get("litellm_logging_obj", None),
+            )
+            selected_data_generator = select_data_generator(
+                response=_streaming_response,
+                user_api_key_dict=user_api_key_dict,
+                request_data=_data,
+            )
+
+            return StreamingResponse(
+                selected_data_generator,
+                media_type="text/event-stream",
+                status_code=200,  # Return 200 for passthrough mode
+            )
+        _usage = litellm.Usage(prompt_tokens=0, completion_tokens=0, total_tokens=0)
+        _chat_response.usage = _usage  # type: ignore
+        return _chat_response
     except RejectedRequestError as e:
         _data = e.request_data
         await proxy_logging_obj.post_call_failure_hook(
@@ -5054,6 +5092,55 @@ async def completion(  # noqa: PLR0915
             user_api_base=user_api_base,
             version=version,
         )
+    except ModifyResponseException as e:
+        # Guardrail flagged content in passthrough mode - return 200 with violation message
+        _data = e.request_data
+        await proxy_logging_obj.post_call_failure_hook(
+            user_api_key_dict=user_api_key_dict,
+            original_exception=e,
+            request_data=_data,
+        )
+
+        if _data.get("stream", None) is not None and _data["stream"] is True:
+            _text_response = litellm.ModelResponse()
+            _text_response.choices[0].text = e.message
+            _text_response.model = e.model  # type: ignore
+            _usage = litellm.Usage(
+                prompt_tokens=0,
+                completion_tokens=0,
+                total_tokens=0,
+            )
+            _text_response.usage = _usage  # type: ignore
+            _iterator = litellm.utils.ModelResponseIterator(
+                model_response=_text_response, convert_to_delta=True
+            )
+            _streaming_response = litellm.TextCompletionStreamWrapper(
+                completion_stream=_iterator,
+                model=e.model,
+            )
+
+            selected_data_generator = select_data_generator(
+                response=_streaming_response,
+                user_api_key_dict=user_api_key_dict,
+                request_data=_data,
+            )
+
+            return StreamingResponse(
+                selected_data_generator,
+                media_type="text/event-stream",
+                status_code=200,  # Return 200 for passthrough mode
+            )
+        else:
+            _response = litellm.TextCompletionResponse()
+            _response.choices[0].text = e.message
+            _response.model = e.model  # type: ignore
+            _usage = litellm.Usage(
+                prompt_tokens=0,
+                completion_tokens=0,
+                total_tokens=0,
+            )
+            _response.usage = _usage  # type: ignore
+            return _response
     except RejectedRequestError as e:
         _data = e.request_data
         await proxy_logging_obj.post_call_failure_hook(
diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py b/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py
index 6a6e5a1e48..79239e5262 100644
--- a/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py
+++ b/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py
@@ -11,8 +11,8 @@ class GraySwanGuardrailConfigModelOptionalParams(BaseModel):
     """Optional parameters for the Gray Swan guardrail."""
 
     on_flagged_action: Optional[str] = Field(
-        default="monitor",
-        description="Action when a violation is detected: 'block' rejects the call, 'monitor' logs only, 'passthrough' includes detection info in response without blocking.",
+        default="passthrough",
+        description="Action when a violation is detected: 'block' rejects the call (400 error), 'monitor' logs only, 'passthrough' replaces response content with violation message (200 status).",
     )
     violation_threshold: Optional[float] = Field(
         default=0.5,
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_grayswan.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_grayswan.py
index 9ee31cf6cb..6dc658827b 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_grayswan.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_grayswan.py
@@ -3,6 +3,7 @@ from typing import Optional
 import pytest
 from fastapi import HTTPException
 
+from litellm.integrations.custom_guardrail import ModifyResponseException
 from litellm.proxy.guardrails.guardrail_hooks.grayswan.grayswan import (
     GraySwanGuardrail,
     GraySwanGuardrailAPIError,
@@ -71,11 +72,27 @@ def test_process_response_blocks_when_threshold_exceeded() -> None:
         event_hook=GuardrailEventHooks.pre_call,
     )
 
+    # Test block mode with input violation (pre_call)
     with pytest.raises(HTTPException) as exc:
-        guardrail._process_grayswan_response({"violation": 0.5, "violated_rules": [1]})
+        guardrail._process_grayswan_response(
+            {"violation": 0.5, "violated_rules": [1]},
+            hook_type=GuardrailEventHooks.pre_call,
+        )
 
     assert exc.value.status_code == 400
     assert exc.value.detail["violation"] == 0.5
+    assert exc.value.detail["violation_location"] == "input"
+
+    # Test block mode with output violation (post_call)
+    with pytest.raises(HTTPException) as exc:
+        guardrail._process_grayswan_response(
+            {"violation": 0.5, "violated_rules": [1]},
+            hook_type=GuardrailEventHooks.post_call,
+        )
+
+    assert exc.value.status_code == 400
+    assert exc.value.detail["violation"] == 0.5
+    assert exc.value.detail["violation_location"] == "output"
 
 
 class _DummyResponse:
@@ -110,7 +127,11 @@ async def test_run_guardrail_posts_payload(
 
     captured = {}
 
-    def fake_process(response_json: dict, data: Optional[dict] = None) -> None:
+    def fake_process(
+        response_json: dict,
+        data: Optional[dict] = None,
+        hook_type: Optional[GuardrailEventHooks] = None,
+    ) -> None:
         captured["response"] = response_json
 
     monkeypatch.setattr(grayswan_guardrail, "_process_grayswan_response", fake_process)
@@ -139,8 +160,8 @@ async def test_run_guardrail_raises_api_error(
         await grayswan_guardrail.run_grayswan_guardrail(payload)
 
 
-def test_process_response_passthrough_stores_detection_info() -> None:
-    """Test that passthrough mode stores detection info in metadata without blocking."""
+def test_process_response_passthrough_raises_exception_in_pre_call() -> None:
+    """Test that passthrough mode raises ModifyResponseException in pre_call hook."""
     guardrail = GraySwanGuardrail(
         guardrail_name="grayswan-passthrough",
         api_key="test-key",
@@ -149,6 +170,64 @@ def test_process_response_passthrough_stores_detection_info() -> None:
         event_hook=GuardrailEventHooks.pre_call,
     )
 
+    data = {"messages": [{"role": "user", "content": "test"}], "model": "gpt-4"}
+    response_json = {
+        "violation": 0.8,
+        "violated_rules": [1, 2],
+        "mutation": True,
+        "ipi": False,
+    }
+
+    # Should raise ModifyResponseException
+    with pytest.raises(ModifyResponseException) as exc:
+        guardrail._process_grayswan_response(
+            response_json, data, GuardrailEventHooks.pre_call
+        )
+
+    assert "Gray Swan Cygnal Guardrail" in exc.value.message
+    assert exc.value.model == "gpt-4"
+    assert exc.value.detection_info["violation_score"] == 0.8
+    assert exc.value.detection_info["violated_rules"] == [1, 2]
+
+
+def test_process_response_passthrough_raises_exception_in_during_call() -> None:
+    """Test that passthrough mode raises ModifyResponseException in during_call hook."""
+    guardrail = GraySwanGuardrail(
+        guardrail_name="grayswan-passthrough",
+        api_key="test-key",
+        on_flagged_action="passthrough",
+        violation_threshold=0.2,
+        event_hook=GuardrailEventHooks.during_call,
+    )
+
+    data = {"messages": [{"role": "user", "content": "test"}], "model": "gpt-4"}
+    response_json = {
+        "violation": 0.8,
+        "violated_rules": [1, 2],
+        "mutation": True,
+        "ipi": False,
+    }
+
+    # Should raise ModifyResponseException
+    with pytest.raises(ModifyResponseException) as exc:
+        guardrail._process_grayswan_response(
+            response_json, data, GuardrailEventHooks.during_call
+        )
+
+    assert "Gray Swan Cygnal Guardrail" in exc.value.message
+    assert exc.value.model == "gpt-4"
+
+
+def test_process_response_passthrough_stores_detection_info_in_post_call() -> None:
+    """Test that passthrough mode stores detection info in post_call hook (not exception)."""
+    guardrail = GraySwanGuardrail(
+        guardrail_name="grayswan-passthrough",
+        api_key="test-key",
+        on_flagged_action="passthrough",
+        violation_threshold=0.2,
+        event_hook=GuardrailEventHooks.post_call,
+    )
+
     data = {"messages": [{"role": "user", "content": "test"}]}
     response_json = {
         "violation": 0.8,
@@ -157,8 +236,10 @@ def test_process_response_passthrough_stores_detection_info() -> None:
         "ipi": False,
     }
 
-    # Should not raise an exception
-    guardrail._process_grayswan_response(response_json, data)
+    # Should NOT raise an exception in post_call
+    guardrail._process_grayswan_response(
+        response_json, data, GuardrailEventHooks.post_call
+    )
 
     # Verify detection info was stored in metadata
     assert "metadata" in data
@@ -174,8 +255,8 @@ def test_process_response_passthrough_stores_detection_info() -> None:
     assert detection["ipi"] is False
 
 
-def test_process_response_passthrough_does_not_store_if_under_threshold() -> None:
-    """Test that passthrough mode doesn't store anything if violation is under threshold."""
+def test_process_response_passthrough_does_not_raise_if_under_threshold() -> None:
+    """Test that passthrough mode doesn't raise exception if violation is under threshold."""
     guardrail = GraySwanGuardrail(
         guardrail_name="grayswan-passthrough",
         api_key="test-key",
@@ -184,14 +265,58 @@ def test_process_response_passthrough_does_not_store_if_under_threshold() -> Non
         event_hook=GuardrailEventHooks.pre_call,
     )
 
-    data = {"messages": [{"role": "user", "content": "test"}]}
+    data = {"messages": [{"role": "user", "content": "test"}], "model": "gpt-4"}
     response_json = {
         "violation": 0.3,
         "violated_rules": [],
     }
 
-    # Should not raise an exception
-    guardrail._process_grayswan_response(response_json, data)
+    # Should not raise an exception since under threshold
+    guardrail._process_grayswan_response(
+        response_json, data, GuardrailEventHooks.pre_call
+    )
 
     # Should not have any detection info since it didn't exceed threshold
     assert "guardrail_detections" not in data.get("metadata", {})
+
+
+def test_format_violation_message() -> None:
+    """Test that violation message is formatted correctly for input violations."""
+    guardrail = GraySwanGuardrail(
+        guardrail_name="grayswan-passthrough",
+        api_key="test-key",
+        on_flagged_action="passthrough",
+        violation_threshold=0.5,
+        event_hook=GuardrailEventHooks.pre_call,
+    )
+
+    detections = [
+        {
+            "guardrail": "grayswan",
+            "flagged": True,
+            "violation_score": 0.85,
+            "violated_rules": [1, 3, 5],
+            "mutation": True,
+            "ipi": False,
+        }
+    ]
+
+    # Test input violation message (pre_call/during_call)
+    message = guardrail._format_violation_message(detections, is_output=False)
+
+    assert "Sorry I can't help with that" in message
+    assert "Gray Swan Cygnal Guardrail" in message
+    assert "the input query has a violation score of 0.85" in message
+    assert "violating the rule(s): 1, 3, 5" in message
+    assert "Mutation effort to make the harmful intention disguised was DETECTED" in message
+    # IPI should not be in message since it's False
+    assert "Indirect Prompt Injection was DETECTED" not in message
+
+    # Test output violation message (post_call)
+    message = guardrail._format_violation_message(detections, is_output=True)
+
+    assert "Sorry I can't help with that" in message
+    assert "Gray Swan Cygnal Guardrail" in message
+    assert "the model response has a violation score of 0.85" in message
+    assert "violating the rule(s): 1, 3, 5" in message
+    assert "Mutation effort to make the harmful intention disguised was DETECTED" in message