diff --git a/pyrit/executor/attack/component/conversation_manager.py b/pyrit/executor/attack/component/conversation_manager.py
index 7a27cb5666..af9c2dee62 100644
--- a/pyrit/executor/attack/component/conversation_manager.py
+++ b/pyrit/executor/attack/component/conversation_manager.py
@@ -20,7 +20,7 @@
 )
 from pyrit.prompt_normalizer.prompt_normalizer import PromptNormalizer
 from pyrit.prompt_target import PromptTarget
-from pyrit.prompt_target.common.prompt_chat_target import PromptChatTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
 
 if TYPE_CHECKING:
     from pyrit.executor.attack.core import AttackContext
@@ -242,7 +242,7 @@ def get_last_message(
     def set_system_prompt(
         self,
         *,
-        target: PromptChatTarget,
+        target: PromptTarget,
         conversation_id: str,
         system_prompt: str,
         labels: Optional[dict[str, str]] = None,
@@ -251,11 +251,16 @@ def set_system_prompt(
         Set or update the system prompt for a conversation.
 
         Args:
-            target: The chat target to set the system prompt on.
+            target: The target to set the system prompt on. Must handle the
+                SYSTEM_PROMPT capability (natively or via an ADAPT policy).
             conversation_id: Unique identifier for the conversation.
             system_prompt: The system prompt text.
             labels: Optional labels to associate with the system prompt.
+
+        Raises:
+            ValueError: If target cannot handle the SYSTEM_PROMPT capability.
         """
+        target.configuration.ensure_can_handle(capability=CapabilityName.SYSTEM_PROMPT)
         target.set_system_prompt(
             system_prompt=system_prompt,
             conversation_id=conversation_id,
@@ -283,7 +288,7 @@ async def initialize_context_async(
         3. Updates context.executed_turns for multi-turn attacks
         4. Sets context.next_message if there's an unanswered user message
 
-        For PromptChatTarget:
+        For chat-capable PromptTarget:
             - Adds prepended messages to memory with simulated_assistant role
             - All messages get new UUIDs
 
@@ -306,7 +311,7 @@ async def initialize_context_async(
 
         Raises:
             ValueError: If conversation_id is empty, or if prepended_conversation
-                requires a PromptChatTarget but target is not one.
+                requires a chat-capable PromptTarget but target is not one.
         """
         if not conversation_id:
             raise ValueError("conversation_id cannot be empty")
@@ -321,8 +326,11 @@ async def initialize_context_async(
             logger.debug(f"No prepended conversation for context initialization: {conversation_id}")
             return state
 
-        # Handle target type compatibility
-        is_chat_target = isinstance(target, PromptChatTarget)
+        # Targets that don't natively support editable history cannot consume a
+        # prepended multi-message conversation as-is — route them to the
+        # single-string fallback path. Type identity (PromptChatTarget) is a
+        # legacy signal for this; capability-based routing is the durable form.
+        is_chat_target = target.configuration.includes(capability=CapabilityName.EDITABLE_HISTORY)
         if not is_chat_target:
             return await self._handle_non_chat_target_async(
                 context=context,
@@ -366,8 +374,8 @@ async def _handle_non_chat_target_async(
 
         if config.non_chat_target_behavior == "raise":
             raise ValueError(
-                "prepended_conversation requires the objective target to be a PromptChatTarget. "
-                "Non-chat objective targets do not support conversation history. "
+                "prepended_conversation requires the objective target to be a chat-capable "
+                "PromptTarget. Non-chat objective targets do not support conversation history. "
                 "Use PrependedConversationConfig with non_chat_target_behavior='normalize_first_turn' "
                 "to normalize the conversation into the first message instead."
             )
diff --git a/pyrit/executor/attack/component/prepended_conversation_config.py b/pyrit/executor/attack/component/prepended_conversation_config.py
index c78ffad767..fddeae5371 100644
--- a/pyrit/executor/attack/component/prepended_conversation_config.py
+++ b/pyrit/executor/attack/component/prepended_conversation_config.py
@@ -22,7 +22,7 @@ class PrependedConversationConfig:
     This class provides control over:
     - Which message roles should have request converters applied
     - How to normalize conversation history for non-chat objective targets
-    - What to do when the objective target is not a PromptChatTarget
+    - What to do when the objective target is not a chat-capable PromptTarget
     """
 
     # Roles for which request converters should be applied to prepended messages.
@@ -36,13 +36,13 @@ class PrependedConversationConfig:
     # ConversationContextNormalizer is used that produces "Turn N: User/Assistant" format.
     message_normalizer: Optional[MessageStringNormalizer] = None
 
-    # Behavior when the target is a PromptTarget but not a PromptChatTarget:
+    # Behavior when the target is a PromptTarget but not a chat-capable PromptTarget:
     # - "normalize_first_turn": Normalize the prepended conversation into a string and
     #   store it in ConversationState.normalized_prepended_context. This context will be
     #   prepended to the first message sent to the target. Uses objective_target_context_normalizer
     #   if provided, otherwise falls back to ConversationContextNormalizer.
     # - "raise": Raise a ValueError. Use this when prepended conversation history must be
-    #   maintained by the target (i.e., target must be a PromptChatTarget).
+    #   maintained by the target (i.e., target must be a chat-capable PromptTarget).
     non_chat_target_behavior: Literal["normalize_first_turn", "raise"] = "normalize_first_turn"
 
     def get_message_normalizer(self) -> MessageStringNormalizer:
diff --git a/pyrit/executor/attack/core/attack_strategy.py b/pyrit/executor/attack/core/attack_strategy.py
index dac86d10aa..efe2dcca8e 100644
--- a/pyrit/executor/attack/core/attack_strategy.py
+++ b/pyrit/executor/attack/core/attack_strategy.py
@@ -8,7 +8,7 @@
 import time
 from abc import ABC
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING, Any, Generic, Optional, TypeVar, Union, overload
+from typing import TYPE_CHECKING, Any, ClassVar, Generic, Optional, TypeVar, Union, overload
 
 from pyrit.common.logger import logger
 from pyrit.executor.attack.core.attack_parameters import AttackParameters, AttackParamsT
@@ -27,6 +27,7 @@
     ConversationReference,
     Message,
 )
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 
 if TYPE_CHECKING:
     from pyrit.executor.attack.core.attack_config import AttackScoringConfig
@@ -233,6 +234,10 @@ class AttackStrategy(Strategy[AttackStrategyContextT, AttackStrategyResultT], Id
     Defines the interface for executing attacks and handling results.
     """
 
+    #: Capability requirements placed on ``objective_target``. Subclasses
+    #: override to declare what the attack needs. Validated in ``__init__``.
+    TARGET_REQUIREMENTS: ClassVar[TargetRequirements] = TargetRequirements()
+
     def __init__(
         self,
         *,
@@ -259,6 +264,7 @@ def __init__(
             ),
             logger=logger,
         )
+        type(self).TARGET_REQUIREMENTS.validate(target=objective_target)
         self._objective_target = objective_target
         self._params_type = params_type
         # Guard so subclasses that set converters before calling super() aren't clobbered
diff --git a/pyrit/executor/attack/multi_turn/chunked_request.py b/pyrit/executor/attack/multi_turn/chunked_request.py
index 1a70c89195..7280ea838a 100644
--- a/pyrit/executor/attack/multi_turn/chunked_request.py
+++ b/pyrit/executor/attack/multi_turn/chunked_request.py
@@ -29,6 +29,8 @@
 )
 from pyrit.prompt_normalizer import PromptNormalizer
 from pyrit.prompt_target import PromptTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 
 if TYPE_CHECKING:
     from pyrit.score import TrueFalseScorer
@@ -82,6 +84,15 @@ class ChunkedRequestAttack(MultiTurnAttackStrategy[ChunkedRequestAttackContext,
         """
     ).strip()
 
+    # Chunked request issues multiple distinct turns that depend on the target
+    # remembering prior responses. History-squash adaptation would collapse
+    # them into a single prompt and silently break the attack's semantics.
+    # Declare MULTI_TURN as ``native_required`` so adaptation is rejected at
+    # construction time.
+    TARGET_REQUIREMENTS = TargetRequirements(
+        native_required=frozenset({CapabilityName.MULTI_TURN}),
+    )
+
     @apply_defaults
     def __init__(
         self,
@@ -226,16 +237,7 @@ async def _setup_async(self, *, context: ChunkedRequestAttackContext) -> None:
 
         Args:
             context (ChunkedRequestAttackContext): The attack context containing attack parameters.
-
-        Raises:
-            ValueError: If the objective target does not support multi-turn conversations.
         """
-        if not self._objective_target.capabilities.supports_multi_turn:
-            raise ValueError(
-                "ChunkedRequestAttack requires a multi-turn target. "
-                "The objective target does not support multi-turn conversations."
-            )
-
         # Ensure the context has a session
         context.session = ConversationSession()
 
diff --git a/pyrit/executor/attack/multi_turn/crescendo.py b/pyrit/executor/attack/multi_turn/crescendo.py
index 4a180d5df3..434b4280b6 100644
--- a/pyrit/executor/attack/multi_turn/crescendo.py
+++ b/pyrit/executor/attack/multi_turn/crescendo.py
@@ -43,7 +43,9 @@
     SeedPrompt,
 )
 from pyrit.prompt_normalizer import PromptNormalizer
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 from pyrit.score import (
     FloatScaleThresholdScorer,
     Scorer,
@@ -112,6 +114,16 @@ class CrescendoAttack(MultiTurnAttackStrategy[CrescendoAttackContext, CrescendoA
     You can learn more about the Crescendo attack [@russinovich2024crescendo].
     """
 
+    # Crescendo fundamentally relies on multi-turn conversation history to
+    # gradually escalate prompts; history-squash adaptation would collapse the
+    # conversation into a single prompt and silently break the attack's
+    # semantics. Declare MULTI_TURN as native_required so adaptation is
+    # rejected at construction time.
+    TARGET_REQUIREMENTS = TargetRequirements(
+        required=frozenset({CapabilityName.EDITABLE_HISTORY, CapabilityName.MULTI_TURN}),
+        native_required=frozenset({CapabilityName.MULTI_TURN}),
+    )
+
     # Default system prompt template path for Crescendo attack
     DEFAULT_ADVERSARIAL_CHAT_SYSTEM_PROMPT_TEMPLATE_PATH: Path = (
         Path(EXECUTOR_SEED_PROMPT_PATH) / "crescendo" / "crescendo_variant_1.yaml"
@@ -121,7 +133,7 @@ class CrescendoAttack(MultiTurnAttackStrategy[CrescendoAttackContext, CrescendoA
     def __init__(
         self,
         *,
-        objective_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        objective_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         attack_adversarial_config: AttackAdversarialConfig,
         attack_converter_config: Optional[AttackConverterConfig] = None,
         attack_scoring_config: Optional[AttackScoringConfig] = None,
@@ -134,7 +146,8 @@ def __init__(
         Initialize the Crescendo attack strategy.
 
         Args:
-            objective_target (PromptChatTarget): The target system to attack. Must be a PromptChatTarget.
+            objective_target (PromptTarget): The target system to attack. Must
+                support editable conversation history.
             attack_adversarial_config (AttackAdversarialConfig): Configuration for the adversarial component,
                 including the adversarial chat target and optional system prompt path.
             attack_converter_config (Optional[AttackConverterConfig]): Configuration for attack converters,
@@ -148,7 +161,7 @@ def __init__(
                 application by role, message normalization, and non-chat target behavior.
 
         Raises:
-            ValueError: If objective_target is not a PromptChatTarget.
+            ValueError: If objective_target does not natively support editable history.
         """
         # Initialize base class
         super().__init__(objective_target=objective_target, logger=logger, context_type=CrescendoAttackContext)
@@ -257,17 +270,7 @@ async def _setup_async(self, *, context: CrescendoAttackContext) -> None:
 
         Args:
             context (CrescendoAttackContext): Attack context with configuration
-
-        Raises:
-            ValueError: If the objective target does not support multi-turn conversations.
         """
-        if not self._objective_target.capabilities.supports_multi_turn:
-            raise ValueError(
-                "CrescendoAttack requires a multi-turn target. Crescendo fundamentally relies on "
-                "multi-turn conversation history to gradually escalate prompts. "
-                "Use RedTeamingAttack or TreeOfAttacksWithPruning instead."
-            )
-
         # Ensure the context has a session
         context.session = ConversationSession()
 
diff --git a/pyrit/executor/attack/multi_turn/multi_prompt_sending.py b/pyrit/executor/attack/multi_turn/multi_prompt_sending.py
index a9d4b75adc..3239c5568e 100644
--- a/pyrit/executor/attack/multi_turn/multi_prompt_sending.py
+++ b/pyrit/executor/attack/multi_turn/multi_prompt_sending.py
@@ -29,6 +29,8 @@
 )
 from pyrit.prompt_normalizer import PromptNormalizer
 from pyrit.prompt_target import PromptTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 from pyrit.score import Scorer
 
 if TYPE_CHECKING:
@@ -123,6 +125,15 @@ class MultiPromptSendingAttack(MultiTurnAttackStrategy[MultiTurnAttackContext[An
     and multiple scorer types for comprehensive evaluation.
     """
 
+    # Sending a sequence of distinct prompts depends on the target maintaining
+    # conversation state between them. History-squash adaptation would collapse
+    # them into one message and silently break the attack's sequencing
+    # semantics. Declare MULTI_TURN as ``native_required`` so adaptation is
+    # rejected at construction time.
+    TARGET_REQUIREMENTS = TargetRequirements(
+        native_required=frozenset({CapabilityName.MULTI_TURN}),
+    )
+
     @apply_defaults
     def __init__(
         self,
@@ -204,16 +215,7 @@ async def _setup_async(self, *, context: MultiTurnAttackContext[Any]) -> None:
 
         Args:
             context (MultiTurnAttackContext): The attack context containing attack parameters.
-
-        Raises:
-            ValueError: If the objective target does not support multi-turn conversations.
         """
-        if not self._objective_target.capabilities.supports_multi_turn:
-            raise ValueError(
-                "MultiPromptSendingAttack requires a multi-turn target. "
-                "The objective target does not support multi-turn conversations."
-            )
-
         # Ensure the context has a session (like red_teaming.py does)
         context.session = ConversationSession()
 
diff --git a/pyrit/executor/attack/multi_turn/multi_turn_attack_strategy.py b/pyrit/executor/attack/multi_turn/multi_turn_attack_strategy.py
index 04c8084f7b..007845d864 100644
--- a/pyrit/executor/attack/multi_turn/multi_turn_attack_strategy.py
+++ b/pyrit/executor/attack/multi_turn/multi_turn_attack_strategy.py
@@ -18,6 +18,7 @@
 )
 from pyrit.memory import CentralMemory
 from pyrit.models import ConversationReference, ConversationType
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
 
 if TYPE_CHECKING:
     from pyrit.models import (
@@ -117,7 +118,7 @@ def _rotate_conversation_for_single_turn_target(
         Args:
             context: The current attack context.
         """
-        if self._objective_target.capabilities.supports_multi_turn:
+        if self._objective_target.configuration.includes(capability=CapabilityName.MULTI_TURN):
             return
 
         if context.executed_turns == 0:
diff --git a/pyrit/executor/attack/multi_turn/tree_of_attacks.py b/pyrit/executor/attack/multi_turn/tree_of_attacks.py
index 7ea7f927b7..e8da296d60 100644
--- a/pyrit/executor/attack/multi_turn/tree_of_attacks.py
+++ b/pyrit/executor/attack/multi_turn/tree_of_attacks.py
@@ -50,7 +50,9 @@
     SeedPrompt,
 )
 from pyrit.prompt_normalizer import PromptConverterConfiguration, PromptNormalizer
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptChatTarget, PromptTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 from pyrit.score import (
     FloatScaleThresholdScorer,
     Scorer,
@@ -64,6 +66,13 @@
 
 logger = logging.getLogger(__name__)
 
+# TAP sets a system prompt on its adversarial target and drives a multi-turn dialogue through it.
+# Both capabilities must be natively supported — adaptation would silently change the semantics
+# (e.g. history-squash normalization would collapse the escalation into a single turn).
+_ADVERSARIAL_REQUIREMENTS = TargetRequirements(
+    native_required=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT}),
+)
+
 
 class TAPAttackScoringConfig(AttackScoringConfig):
     """
@@ -257,7 +266,7 @@ class _TreeOfAttacksNode:
     def __init__(
         self,
         *,
-        objective_target: PromptChatTarget,
+        objective_target: PromptTarget,
         adversarial_chat: PromptChatTarget,
         adversarial_chat_seed_prompt: SeedPrompt,
         adversarial_chat_prompt_template: SeedPrompt,
@@ -279,7 +288,7 @@ def __init__(
         Initialize a tree node.
 
         Args:
-            objective_target (PromptChatTarget): The target to attack.
+            objective_target (PromptTarget): The target to attack.
             adversarial_chat (PromptChatTarget): The chat target for generating adversarial prompts.
             adversarial_chat_seed_prompt (SeedPrompt): The seed prompt for the first turn.
             adversarial_chat_prompt_template (SeedPrompt): The template for subsequent turns.
@@ -780,7 +789,7 @@ def duplicate(self) -> "_TreeOfAttacksNode":
         # For single-turn targets, duplicate only the system messages (e.g., system prompt
         # from prepended conversation) so the target retains its configuration without
         # carrying over attack turn history that would cause validation errors.
-        if self._objective_target.capabilities.supports_multi_turn:
+        if self._objective_target.configuration.includes(capability=CapabilityName.MULTI_TURN):
             duplicate_node.objective_target_conversation_id = self._memory.duplicate_conversation(
                 conversation_id=self.objective_target_conversation_id
             )
@@ -1254,7 +1263,7 @@ class TreeOfAttacksWithPruningAttack(AttackStrategy[TAPAttackContext, TAPAttackR
     def __init__(
         self,
         *,
-        objective_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        objective_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         attack_adversarial_config: AttackAdversarialConfig,
         attack_converter_config: Optional[AttackConverterConfig] = None,
         attack_scoring_config: Optional[AttackScoringConfig] = None,
@@ -1271,7 +1280,7 @@ def __init__(
         Initialize the Tree of Attacks with Pruning attack strategy.
 
         Args:
-            objective_target (PromptChatTarget): The target system to attack.
+            objective_target (PromptTarget): The target system to attack.
             attack_adversarial_config (AttackAdversarialConfig): Configuration for the adversarial chat component.
             attack_converter_config (Optional[AttackConverterConfig]): Configuration for attack converters.
                 Defaults to None.
@@ -1293,7 +1302,8 @@ def __init__(
 
         Raises:
             ValueError: If attack_scoring_config uses a non-FloatScaleThresholdScorer objective scorer,
-                if target is not PromptChatTarget, or if parameters are invalid.
+                if the adversarial target does not natively support the capabilities TAP needs,
+                or if parameters are invalid.
         """
         # Validate tree parameters
         if tree_depth < 1:
@@ -1322,8 +1332,14 @@ def __init__(
 
         # Initialize adversarial configuration
         self._adversarial_chat = attack_adversarial_config.target
-        if not isinstance(self._adversarial_chat, PromptChatTarget):
-            raise ValueError("The adversarial target must be a PromptChatTarget for TAP attack.")
+        # TAP sets a system prompt on the adversarial target and drives a
+        # multi-turn dialogue through it; both capabilities must be native.
+        # (The class-level ``TARGET_REQUIREMENTS`` inherited from ``AttackStrategy``
+        # only covers ``objective_target``; this is a separate target.)
+        try:
+            _ADVERSARIAL_REQUIREMENTS.validate(target=self._adversarial_chat)
+        except ValueError as exc:
+            raise ValueError(f"TreeOfAttacksWithPruningAttack {exc}") from exc
 
         # Load system prompts
         self._adversarial_chat_system_prompt_path = (
@@ -1857,7 +1873,7 @@ def _create_attack_node(
                 generate adversarial prompts and evaluate responses.
         """
         node = _TreeOfAttacksNode(
-            objective_target=cast("PromptChatTarget", self._objective_target),
+            objective_target=self._objective_target,
             adversarial_chat=self._adversarial_chat,
             adversarial_chat_seed_prompt=self._adversarial_chat_seed_prompt,
             adversarial_chat_system_seed_prompt=self._adversarial_chat_system_seed_prompt,
diff --git a/pyrit/prompt_converter/denylist_converter.py b/pyrit/prompt_converter/denylist_converter.py
index 46f427caef..7cbc6f5e9e 100644
--- a/pyrit/prompt_converter/denylist_converter.py
+++ b/pyrit/prompt_converter/denylist_converter.py
@@ -10,7 +10,7 @@
 from pyrit.models import PromptDataType, SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
 from pyrit.prompt_converter.prompt_converter import ConverterResult
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -19,14 +19,14 @@ class DenylistConverter(LLMGenericTextConverter):
     """
     Replaces forbidden words or phrases in a prompt with synonyms using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         system_prompt_template: Optional[SeedPrompt] = None,
         denylist: list[str] | None = None,
     ):
@@ -34,7 +34,7 @@ def __init__(
         Initialize the converter with a target, an optional system prompt template, and a denylist.
 
         Args:
-            converter_target (PromptChatTarget): The target for the prompt conversion.
+            converter_target (PromptTarget): The target for the prompt conversion.
                 Can be omitted if a default has been configured via PyRIT initialization.
             system_prompt_template (Optional[SeedPrompt]): The system prompt template to use for the conversion.
                 If not provided, a default template will be used.
diff --git a/pyrit/prompt_converter/llm_generic_text_converter.py b/pyrit/prompt_converter/llm_generic_text_converter.py
index f56990247f..9cb15ef1f6 100644
--- a/pyrit/prompt_converter/llm_generic_text_converter.py
+++ b/pyrit/prompt_converter/llm_generic_text_converter.py
@@ -15,7 +15,7 @@
     SeedPrompt,
 )
 from pyrit.prompt_converter.prompt_converter import ConverterResult, PromptConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -27,12 +27,13 @@ class LLMGenericTextConverter(PromptConverter):
 
     SUPPORTED_INPUT_TYPES = ("text",)
     SUPPORTED_OUTPUT_TYPES = ("text",)
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         system_prompt_template: Optional[SeedPrompt] = None,
         user_prompt_template_with_objective: Optional[SeedPrompt] = None,
         **kwargs: Any,
@@ -41,8 +42,10 @@ def __init__(
         Initialize the converter with a target and optional prompt templates.
 
         Args:
-            converter_target (PromptChatTarget): The endpoint that converts the prompt.
-                Can be omitted if a default has been configured via PyRIT initialization.
+            converter_target (PromptTarget): The endpoint that converts the prompt. Must satisfy
+                ``CHAT_CONSUMER_REQUIREMENTS`` (multi-turn + editable history capabilities, possibly
+                via normalization-pipeline adaptation). Can be omitted if a default has been configured
+                via PyRIT initialization.
             system_prompt_template (SeedPrompt, Optional): The prompt template to set as the system prompt.
             user_prompt_template_with_objective (SeedPrompt, Optional): The prompt template to set as the user prompt.
                 expects
@@ -51,6 +54,7 @@ def __init__(
         Raises:
             ValueError: If converter_target is not provided and no default has been configured.
         """
+        super().__init__(converter_target=converter_target)
         self._converter_target = converter_target
         self._system_prompt_template = system_prompt_template
         self._prompt_kwargs = kwargs
diff --git a/pyrit/prompt_converter/malicious_question_generator_converter.py b/pyrit/prompt_converter/malicious_question_generator_converter.py
index 41a7848458..5725fff9c4 100644
--- a/pyrit/prompt_converter/malicious_question_generator_converter.py
+++ b/pyrit/prompt_converter/malicious_question_generator_converter.py
@@ -10,7 +10,7 @@
 from pyrit.models import PromptDataType, SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
 from pyrit.prompt_converter.prompt_converter import ConverterResult
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -19,21 +19,21 @@ class MaliciousQuestionGeneratorConverter(LLMGenericTextConverter):
     """
     Generates malicious questions using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         prompt_template: Optional[SeedPrompt] = None,
     ):
         """
         Initialize the converter with a specific target and template.
 
         Args:
-            converter_target (PromptChatTarget): The endpoint that converts the prompt.
+            converter_target (PromptTarget): The endpoint that converts the prompt.
                 Can be omitted if a default has been configured via PyRIT initialization.
             prompt_template (SeedPrompt): The seed prompt template to use.
         """
diff --git a/pyrit/prompt_converter/math_prompt_converter.py b/pyrit/prompt_converter/math_prompt_converter.py
index fd6491bbc1..a3520b190c 100644
--- a/pyrit/prompt_converter/math_prompt_converter.py
+++ b/pyrit/prompt_converter/math_prompt_converter.py
@@ -10,7 +10,7 @@
 from pyrit.models import PromptDataType, SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
 from pyrit.prompt_converter.prompt_converter import ConverterResult
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -19,21 +19,21 @@ class MathPromptConverter(LLMGenericTextConverter):
     """
     Converts natural language instructions into symbolic mathematics problems using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         prompt_template: Optional[SeedPrompt] = None,
     ):
         """
         Initialize the converter with a specific target and template.
 
         Args:
-            converter_target (PromptChatTarget): The endpoint that converts the prompt.
+            converter_target (PromptTarget): The endpoint that converts the prompt.
                 Can be omitted if a default has been configured via PyRIT initialization.
             prompt_template (SeedPrompt): The seed prompt template to use.
         """
diff --git a/pyrit/prompt_converter/noise_converter.py b/pyrit/prompt_converter/noise_converter.py
index 0d7bdf302f..86c5375773 100644
--- a/pyrit/prompt_converter/noise_converter.py
+++ b/pyrit/prompt_converter/noise_converter.py
@@ -11,7 +11,7 @@
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -20,14 +20,14 @@ class NoiseConverter(LLMGenericTextConverter):
     """
     Injects noise errors into a conversation using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         noise: Optional[str] = None,
         number_errors: int = 5,
         prompt_template: Optional[SeedPrompt] = None,
@@ -36,7 +36,7 @@ def __init__(
         Initialize the converter with the specified parameters.
 
         Args:
-            converter_target (PromptChatTarget): The endpoint that converts the prompt.
+            converter_target (PromptTarget): The endpoint that converts the prompt.
                 Can be omitted if a default has been configured via PyRIT initialization.
             noise (str): The noise to inject. Grammar error, delete random letter, insert random space, etc.
             number_errors (int): The number of errors to inject.
diff --git a/pyrit/prompt_converter/persuasion_converter.py b/pyrit/prompt_converter/persuasion_converter.py
index 11b6bd66e6..090cd6117d 100644
--- a/pyrit/prompt_converter/persuasion_converter.py
+++ b/pyrit/prompt_converter/persuasion_converter.py
@@ -21,7 +21,7 @@
     SeedPrompt,
 )
 from pyrit.prompt_converter.prompt_converter import ConverterResult, PromptConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -47,19 +47,20 @@ class PersuasionConverter(PromptConverter):
 
     SUPPORTED_INPUT_TYPES = ("text",)
     SUPPORTED_OUTPUT_TYPES = ("text",)
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         persuasion_technique: str,
     ):
         """
         Initialize the converter with the specified target and prompt template.
 
         Args:
-            converter_target (PromptChatTarget): The chat target used to perform rewriting on user prompts.
+            converter_target (PromptTarget): The chat target used to perform rewriting on user prompts.
                 Can be omitted if a default has been configured via PyRIT initialization.
             persuasion_technique (str): Persuasion technique to be used by the converter, determines the system prompt
                 to be used to generate new prompts. Must be one of "authority_endorsement", "evidence_based",
@@ -69,6 +70,7 @@ def __init__(
             ValueError: If converter_target is not provided and no default has been configured.
             ValueError: If the persuasion technique is not supported or does not exist.
         """
+        super().__init__(converter_target=converter_target)
         self.converter_target = converter_target
 
         try:
diff --git a/pyrit/prompt_converter/prompt_converter.py b/pyrit/prompt_converter/prompt_converter.py
index 141076e701..88ca34ea44 100644
--- a/pyrit/prompt_converter/prompt_converter.py
+++ b/pyrit/prompt_converter/prompt_converter.py
@@ -6,11 +6,15 @@
 import inspect
 import re
 from dataclasses import dataclass
-from typing import Any, Optional, Union, get_args
+from typing import TYPE_CHECKING, Any, ClassVar, Optional, Union, get_args
 
 from pyrit import prompt_converter
 from pyrit.identifiers import ComponentIdentifier, Identifiable
 from pyrit.models import PromptDataType
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
+
+if TYPE_CHECKING:
+    from pyrit.prompt_target import PromptTarget
 
 
 @dataclass
@@ -48,6 +52,11 @@ class PromptConverter(Identifiable):
     #: Tuple of output modalities supported by this converter. Subclasses must override this.
     SUPPORTED_OUTPUT_TYPES: tuple[PromptDataType, ...] = ()
 
+    #: Capability requirements placed on the converter's target (if any).
+    #: Subclasses that use a target should override this and pass the target to
+    #: ``super().__init__(converter_target=...)`` so the base class can validate it.
+    TARGET_REQUIREMENTS: ClassVar[TargetRequirements] = TargetRequirements()
+
     _identifier: Optional[ComponentIdentifier] = None
 
     def __init_subclass__(cls, **kwargs: object) -> None:
@@ -75,11 +84,17 @@ def __init_subclass__(cls, **kwargs: object) -> None:
                     f"Declare the output modalities this converter produces."
                 )
 
-    def __init__(self) -> None:
+    def __init__(self, *, converter_target: Optional["PromptTarget"] = None) -> None:
         """
         Initialize the prompt converter.
+
+        Args:
+            converter_target (Optional[PromptTarget]): Target used by the converter, if any. When
+                provided, it is validated against ``TARGET_REQUIREMENTS``.
         """
         super().__init__()
+        if converter_target is not None:
+            type(self).TARGET_REQUIREMENTS.validate(target=converter_target)
 
     @abc.abstractmethod
     async def convert_async(self, *, prompt: str, input_type: PromptDataType = "text") -> ConverterResult:
diff --git a/pyrit/prompt_converter/random_translation_converter.py b/pyrit/prompt_converter/random_translation_converter.py
index 74953c2603..7e11810323 100644
--- a/pyrit/prompt_converter/random_translation_converter.py
+++ b/pyrit/prompt_converter/random_translation_converter.py
@@ -13,7 +13,7 @@
 from pyrit.prompt_converter.prompt_converter import ConverterResult
 from pyrit.prompt_converter.text_selection_strategy import WordSelectionStrategy
 from pyrit.prompt_converter.word_level_converter import WordLevelConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -22,7 +22,7 @@ class RandomTranslationConverter(LLMGenericTextConverter, WordLevelConverter):
     """
     Translates each individual word in a prompt to a random language using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the translation (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the translation (like Azure OpenAI).
     """
 
     SUPPORTED_INPUT_TYPES = ("text",)
@@ -35,7 +35,7 @@ class RandomTranslationConverter(LLMGenericTextConverter, WordLevelConverter):
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         system_prompt_template: Optional[SeedPrompt] = None,
         languages: Optional[list[str]] = None,
         word_selection_strategy: Optional[WordSelectionStrategy] = None,
@@ -44,7 +44,7 @@ def __init__(
         Initialize the converter with a target, an optional system prompt template, and language options.
 
         Args:
-            converter_target (PromptChatTarget): The target for the prompt conversion.
+            converter_target (PromptTarget): The target for the prompt conversion.
                 Can be omitted if a default has been configured via PyRIT initialization.
             system_prompt_template (Optional[SeedPrompt]): The system prompt template to use for the conversion.
                 If not provided, a default template will be used.
diff --git a/pyrit/prompt_converter/scientific_translation_converter.py b/pyrit/prompt_converter/scientific_translation_converter.py
index 2a6c965996..bdc7987041 100644
--- a/pyrit/prompt_converter/scientific_translation_converter.py
+++ b/pyrit/prompt_converter/scientific_translation_converter.py
@@ -10,7 +10,7 @@
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -45,7 +45,7 @@ class ScientificTranslationConverter(LLMGenericTextConverter):
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         mode: str = "combined",
         prompt_template: Optional[SeedPrompt] = None,
     ) -> None:
@@ -53,7 +53,7 @@ def __init__(
         Initialize the scientific translation converter.
 
         Args:
-            converter_target (PromptChatTarget): The LLM target to perform the conversion.
+            converter_target (PromptTarget): The LLM target to perform the conversion.
             mode (str): The translation mode to use. Built-in options are:
 
                 - ``academic``: Use academic/homework style framing
diff --git a/pyrit/prompt_converter/tense_converter.py b/pyrit/prompt_converter/tense_converter.py
index 237a2934d5..eede7adef9 100644
--- a/pyrit/prompt_converter/tense_converter.py
+++ b/pyrit/prompt_converter/tense_converter.py
@@ -10,7 +10,7 @@
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -19,14 +19,14 @@ class TenseConverter(LLMGenericTextConverter):
     """
     Converts a conversation to a different tense using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         tense: str,
         prompt_template: Optional[SeedPrompt] = None,
     ):
@@ -34,7 +34,7 @@ def __init__(
         Initialize the converter with the target chat support, tense, and optional prompt template.
 
         Args:
-            converter_target (PromptChatTarget): The target chat support for the conversion which will translate.
+            converter_target (PromptTarget): The target chat support for the conversion which will translate.
                 Can be omitted if a default has been configured via PyRIT initialization.
             tense (str): The tense the converter should convert the prompt to. E.g. past, present, future.
             prompt_template (SeedPrompt, Optional): The prompt template for the conversion.
diff --git a/pyrit/prompt_converter/tone_converter.py b/pyrit/prompt_converter/tone_converter.py
index a7b8e5a9f1..4a6d0e859e 100644
--- a/pyrit/prompt_converter/tone_converter.py
+++ b/pyrit/prompt_converter/tone_converter.py
@@ -10,7 +10,7 @@
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -19,14 +19,14 @@ class ToneConverter(LLMGenericTextConverter):
     """
     Converts a conversation to a different tone using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
     """
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         tone: str,
         prompt_template: Optional[SeedPrompt] = None,
     ):
@@ -34,7 +34,7 @@ def __init__(
         Initialize the converter with the target chat support, tone, and optional prompt template.
 
         Args:
-            converter_target (PromptChatTarget): The target chat support for the conversion which will translate.
+            converter_target (PromptTarget): The target chat support for the conversion which will translate.
                 Can be omitted if a default has been configured via PyRIT initialization.
             tone (str): The tone for the conversation. E.g. upset, sarcastic, indifferent, etc.
             prompt_template (SeedPrompt, Optional): The prompt template for the conversion.
diff --git a/pyrit/prompt_converter/toxic_sentence_generator_converter.py b/pyrit/prompt_converter/toxic_sentence_generator_converter.py
index d3390c6af7..636e50ad8d 100644
--- a/pyrit/prompt_converter/toxic_sentence_generator_converter.py
+++ b/pyrit/prompt_converter/toxic_sentence_generator_converter.py
@@ -14,7 +14,7 @@
 from pyrit.models import PromptDataType, SeedPrompt
 from pyrit.prompt_converter.llm_generic_text_converter import LLMGenericTextConverter
 from pyrit.prompt_converter.prompt_converter import ConverterResult
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -23,7 +23,7 @@ class ToxicSentenceGeneratorConverter(LLMGenericTextConverter):
     """
     Generates toxic sentence starters using an LLM.
 
-    An existing ``PromptChatTarget`` is used to perform the conversion (like Azure OpenAI).
+    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
 
     Based on Project Moonshot's attack module that generates toxic sentences to test LLM
     safety guardrails:
@@ -34,14 +34,14 @@ class ToxicSentenceGeneratorConverter(LLMGenericTextConverter):
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         prompt_template: Optional[SeedPrompt] = None,
     ):
         """
         Initialize the converter with a specific target and template.
 
         Args:
-            converter_target (PromptChatTarget): The endpoint that converts the prompt.
+            converter_target (PromptTarget): The endpoint that converts the prompt.
                 Can be omitted if a default has been configured via PyRIT initialization.
             prompt_template (SeedPrompt): The seed prompt template to use. If not provided,
                                           defaults to the ``toxic_sentence_generator.yaml``.
diff --git a/pyrit/prompt_converter/translation_converter.py b/pyrit/prompt_converter/translation_converter.py
index 911f72ab57..dfb67682f9 100644
--- a/pyrit/prompt_converter/translation_converter.py
+++ b/pyrit/prompt_converter/translation_converter.py
@@ -24,7 +24,7 @@
     SeedPrompt,
 )
 from pyrit.prompt_converter.prompt_converter import ConverterResult, PromptConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -36,12 +36,13 @@ class TranslationConverter(PromptConverter):
 
     SUPPORTED_INPUT_TYPES = ("text",)
     SUPPORTED_OUTPUT_TYPES = ("text",)
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         language: str,
         prompt_template: Optional[SeedPrompt] = None,
         max_retries: int = 3,
@@ -51,7 +52,7 @@ def __init__(
         Initialize the converter with the target chat support, language, and optional prompt template.
 
         Args:
-            converter_target (PromptChatTarget): The target chat support for the conversion which will translate.
+            converter_target (PromptTarget): The target chat support for the conversion which will translate.
                 Can be omitted if a default has been configured via PyRIT initialization.
             language (str): The language for the conversion. E.g. Spanish, French, leetspeak, etc.
             prompt_template (SeedPrompt, Optional): The prompt template for the conversion.
@@ -62,6 +63,7 @@ def __init__(
             ValueError: If converter_target is not provided and no default has been configured.
             ValueError: If the language is not provided.
         """
+        super().__init__(converter_target=converter_target)
         self.converter_target = converter_target
 
         # Retry strategy for the conversion
diff --git a/pyrit/prompt_converter/variation_converter.py b/pyrit/prompt_converter/variation_converter.py
index 328e463072..ca9c86aa6e 100644
--- a/pyrit/prompt_converter/variation_converter.py
+++ b/pyrit/prompt_converter/variation_converter.py
@@ -23,7 +23,7 @@
     SeedPrompt,
 )
 from pyrit.prompt_converter.prompt_converter import ConverterResult, PromptConverter
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 
 logger = logging.getLogger(__name__)
 
@@ -35,19 +35,20 @@ class VariationConverter(PromptConverter):
 
     SUPPORTED_INPUT_TYPES = ("text",)
     SUPPORTED_OUTPUT_TYPES = ("text",)
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     @apply_defaults
     def __init__(
         self,
         *,
-        converter_target: PromptChatTarget = REQUIRED_VALUE,  # type: ignore[assignment]
+        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[assignment]
         prompt_template: Optional[SeedPrompt] = None,
     ):
         """
         Initialize the converter with the specified target and prompt template.
 
         Args:
-            converter_target (PromptChatTarget): The target to which the prompt will be sent for conversion.
+            converter_target (PromptTarget): The target to which the prompt will be sent for conversion.
                 Can be omitted if a default has been configured via PyRIT initialization.
             prompt_template (SeedPrompt, optional): The template used for generating the system prompt.
                 If not provided, a default template will be used.
@@ -55,6 +56,7 @@ def __init__(
         Raises:
             ValueError: If converter_target is not provided and no default has been configured.
         """
+        super().__init__(converter_target=converter_target)
         self.converter_target = converter_target
 
         # set to default strategy if not provided
diff --git a/pyrit/prompt_converter/word_level_converter.py b/pyrit/prompt_converter/word_level_converter.py
index 7753c49528..50368aed9c 100644
--- a/pyrit/prompt_converter/word_level_converter.py
+++ b/pyrit/prompt_converter/word_level_converter.py
@@ -33,6 +33,7 @@ def __init__(
         *,
         word_selection_strategy: Optional[WordSelectionStrategy] = None,
         word_split_separator: Optional[str] = " ",
+        **kwargs,
     ):
         """
         Initialize the converter with the specified selection strategy.
@@ -42,8 +43,10 @@ def __init__(
                 words to convert. If None, all words will be converted. Defaults to None.
             word_split_separator (Optional[str]): Separator used to split words in the input text.
                 If None, splits by any whitespace. Defaults to " ".
+            **kwargs: Forwarded to ``PromptConverter.__init__`` to support cooperative multiple inheritance
+                (e.g., ``converter_target`` when mixed with LLM-based converters).
         """
-        super().__init__()
+        super().__init__(**kwargs)
         self._word_selection_strategy = word_selection_strategy or AllWordsSelectionStrategy()
         self._word_split_separator = word_split_separator
 
diff --git a/pyrit/prompt_target/__init__.py b/pyrit/prompt_target/__init__.py
index c71dca4089..db24087d22 100644
--- a/pyrit/prompt_target/__init__.py
+++ b/pyrit/prompt_target/__init__.py
@@ -20,7 +20,10 @@
     UnsupportedCapabilityBehavior,
 )
 from pyrit.prompt_target.common.target_configuration import TargetConfiguration
-from pyrit.prompt_target.common.target_requirements import TargetRequirements
+from pyrit.prompt_target.common.target_requirements import (
+    CHAT_CONSUMER_REQUIREMENTS,
+    TargetRequirements,
+)
 from pyrit.prompt_target.common.utils import limit_requests_per_minute
 from pyrit.prompt_target.gandalf_target import GandalfLevel, GandalfTarget
 from pyrit.prompt_target.http_target.http_target import HTTPTarget
@@ -51,6 +54,7 @@
     "AzureMLChatTarget",
     "CapabilityName",
     "CapabilityHandlingPolicy",
+    "CHAT_CONSUMER_REQUIREMENTS",
     "CopilotType",
     "ConversationNormalizationPipeline",
     "GandalfLevel",
diff --git a/pyrit/prompt_target/common/prompt_chat_target.py b/pyrit/prompt_target/common/prompt_chat_target.py
index ce1f254678..c707b7fcad 100644
--- a/pyrit/prompt_target/common/prompt_chat_target.py
+++ b/pyrit/prompt_target/common/prompt_chat_target.py
@@ -3,11 +3,10 @@
 
 from typing import Optional
 
-from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece
 from pyrit.models.json_response_config import _JsonResponseConfig
 from pyrit.prompt_target.common.prompt_target import PromptTarget
-from pyrit.prompt_target.common.target_capabilities import TargetCapabilities
+from pyrit.prompt_target.common.target_capabilities import CapabilityName, TargetCapabilities
 from pyrit.prompt_target.common.target_configuration import TargetConfiguration
 
 
@@ -27,6 +26,7 @@ class PromptChatTarget(PromptTarget):
             supports_multi_turn=True,
             supports_multi_message_pieces=True,
             supports_system_prompt=True,
+            supports_editable_history=True,
         )
     )
 
@@ -64,37 +64,6 @@ def __init__(
             custom_capabilities=custom_capabilities,
         )
 
-    def set_system_prompt(
-        self,
-        *,
-        system_prompt: str,
-        conversation_id: str,
-        attack_identifier: Optional[ComponentIdentifier] = None,
-        labels: Optional[dict[str, str]] = None,
-    ) -> None:
-        """
-        Set the system prompt for the prompt target. May be overridden by subclasses.
-
-        Raises:
-            RuntimeError: If the conversation already exists.
-        """
-        messages = self._memory.get_conversation(conversation_id=conversation_id)
-
-        if messages:
-            raise RuntimeError("Conversation already exists, system prompt needs to be set at the beginning")
-
-        self._memory.add_message_to_memory(
-            request=MessagePiece(
-                role="system",
-                conversation_id=conversation_id,
-                original_value=system_prompt,
-                converted_value=system_prompt,
-                prompt_target_identifier=self.get_identifier(),
-                attack_identifier=attack_identifier,
-                labels=labels,
-            ).to_message()
-        )
-
     def is_response_format_json(self, message_piece: MessagePiece) -> bool:
         """
         Check if the response format is JSON and ensure the target supports it.
@@ -128,7 +97,7 @@ def _get_json_response_config(self, *, message_piece: MessagePiece) -> _JsonResp
         """
         config = _JsonResponseConfig.from_metadata(metadata=message_piece.prompt_metadata)
 
-        if config.enabled and not self.capabilities.supports_json_output:
+        if config.enabled and not self.configuration.includes(capability=CapabilityName.JSON_OUTPUT):
             target_name = self.get_identifier().class_name
             raise ValueError(f"This target {target_name} does not support JSON response format.")
 
diff --git a/pyrit/prompt_target/common/prompt_target.py b/pyrit/prompt_target/common/prompt_target.py
index 53d7d2085a..5c9712d21b 100644
--- a/pyrit/prompt_target/common/prompt_target.py
+++ b/pyrit/prompt_target/common/prompt_target.py
@@ -8,8 +8,8 @@
 
 from pyrit.identifiers import ComponentIdentifier, Identifiable
 from pyrit.memory import CentralMemory, MemoryInterface
-from pyrit.models import Message
-from pyrit.prompt_target.common.target_capabilities import TargetCapabilities
+from pyrit.models import Message, MessagePiece
+from pyrit.prompt_target.common.target_capabilities import CapabilityName, TargetCapabilities
 from pyrit.prompt_target.common.target_configuration import TargetConfiguration, resolve_configuration_compat
 
 logger = logging.getLogger(__name__)
@@ -178,7 +178,7 @@ def _validate_request(self, *, normalized_conversation: list[Message]) -> None:
         custom_configuration_message = (
             "If your target does support this, set the custom_configuration parameter accordingly."
         )
-        if not self.capabilities.supports_multi_message_pieces and n_pieces != 1:
+        if not self.configuration.includes(capability=CapabilityName.MULTI_MESSAGE_PIECES) and n_pieces != 1:
             raise ValueError(
                 f"This target only supports a single message piece. Received: {n_pieces} pieces. "
                 f"{custom_configuration_message}"
@@ -194,7 +194,7 @@ def _validate_request(self, *, normalized_conversation: list[Message]) -> None:
                     f"{custom_configuration_message}"
                 )
 
-        if not self.capabilities.supports_multi_turn and len(normalized_conversation) > 1:
+        if not self.configuration.includes(capability=CapabilityName.MULTI_TURN) and len(normalized_conversation) > 1:
             raise ValueError(f"This target only supports a single turn conversation. {custom_configuration_message}")
 
     async def _get_normalized_conversation_async(self, *, message: Message) -> list[Message]:
@@ -270,6 +270,56 @@ def set_model_name(self, *, model_name: str) -> None:
         """
         self._model_name = model_name
 
+    def set_system_prompt(
+        self,
+        *,
+        system_prompt: str,
+        conversation_id: str,
+        attack_identifier: ComponentIdentifier | None = None,
+        labels: dict[str, str] | None = None,
+    ) -> None:
+        """
+        Inject a system prompt into memory for the given conversation.
+
+        Writes a ``system``-role message so the target's normalization pipeline
+        (or the target itself, when it natively supports system prompts) will
+        pick it up on the next ``send_prompt_async`` call.
+
+        If the target does not natively support system prompts, whether this
+        call is ultimately honored depends on the target's
+        :class:`CapabilityHandlingPolicy`:
+
+        * ``ADAPT`` — the normalization pipeline (e.g. system squash) will
+          fold the system message into user content on the wire.
+        * ``RAISE`` — the first send after the system prompt is set will
+          raise, because the pipeline cannot adapt the missing capability.
+
+        Args:
+            system_prompt (str): The system prompt text to set.
+            conversation_id (str): The conversation id to attach the prompt to.
+            attack_identifier (ComponentIdentifier | None): Optional attack identifier.
+            labels (dict[str, str] | None): Optional labels.
+
+        Raises:
+            RuntimeError: If the conversation already has messages.
+        """
+        messages = self._memory.get_conversation(conversation_id=conversation_id)
+
+        if messages:
+            raise RuntimeError("Conversation already exists, system prompt needs to be set at the beginning")
+
+        self._memory.add_message_to_memory(
+            request=MessagePiece(
+                role="system",
+                conversation_id=conversation_id,
+                original_value=system_prompt,
+                converted_value=system_prompt,
+                prompt_target_identifier=self.get_identifier(),
+                attack_identifier=attack_identifier,
+                labels=labels,
+            ).to_message()
+        )
+
     def dispose_db_engine(self) -> None:
         """
         Dispose database engine to release database connections and resources.
diff --git a/pyrit/prompt_target/common/target_capabilities.py b/pyrit/prompt_target/common/target_capabilities.py
index 58c6a7e05c..6ae9ed69e2 100644
--- a/pyrit/prompt_target/common/target_capabilities.py
+++ b/pyrit/prompt_target/common/target_capabilities.py
@@ -190,6 +190,7 @@ def get_known_capabilities(underlying_model: str) -> "Optional[TargetCapabilitie
     supports_multi_message_pieces=True,
     supports_system_prompt=True,
     supports_json_output=True,
+    supports_editable_history=True,
     input_modalities=_TEXT_IMAGE_INPUT,
     output_modalities=_TEXT_OUTPUT,
 )
@@ -200,6 +201,7 @@ def get_known_capabilities(underlying_model: str) -> "Optional[TargetCapabilitie
     supports_system_prompt=True,
     supports_json_schema=True,
     supports_json_output=True,
+    supports_editable_history=True,
     input_modalities=_TEXT_IMAGE_INPUT,
     output_modalities=_TEXT_OUTPUT,
 )
diff --git a/pyrit/prompt_target/common/target_requirements.py b/pyrit/prompt_target/common/target_requirements.py
index 95182b47b5..9118d7f427 100644
--- a/pyrit/prompt_target/common/target_requirements.py
+++ b/pyrit/prompt_target/common/target_requirements.py
@@ -6,9 +6,10 @@
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING
 
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+
 if TYPE_CHECKING:
-    from pyrit.prompt_target.common.target_capabilities import CapabilityName
-    from pyrit.prompt_target.common.target_configuration import TargetConfiguration
+    from pyrit.prompt_target.common.prompt_target import PromptTarget
 
 
 @dataclass(frozen=True)
@@ -17,38 +18,51 @@ class TargetRequirements:
     Declarative description of what a consumer (attack, converter, scorer)
     requires from a target.
 
-    Consumers define their requirements once and validate them against a
-    ``TargetConfiguration`` at construction time. This replaces ad-hoc
-    ``isinstance`` checks and scattered capability branching.
+    The single source of truth for capability names is the
+    :class:`CapabilityName` enum; this class is simply a typed wrapper
+    around the set of capabilities a consumer needs.
+
+    Two tiers of requirement are supported:
+
+    * ``required`` \u2014 satisfied either by native support on the target or
+      by an ``ADAPT`` entry in the target's
+      :class:`CapabilityHandlingPolicy`. Use this when the consumer only
+      needs the behavior to appear on the wire.
+    * ``native_required`` \u2014 must be natively supported. Adaptation is
+      rejected. Use this when adaptation would silently change the
+      consumer's semantics (e.g. an attack that depends on the target
+      remembering prior turns, where history-squash normalization would
+      collapse the conversation into a single prompt).
     """
 
-    # The set of capabilities the consumer requires.
-    required_capabilities: frozenset[CapabilityName] = field(default_factory=frozenset)
+    required: frozenset[CapabilityName] = field(default_factory=frozenset)
+    native_required: frozenset[CapabilityName] = field(default_factory=frozenset)
 
-    def validate(self, *, configuration: TargetConfiguration) -> None:
+    def validate(self, *, target: PromptTarget) -> None:
         """
-        Validate that the target configuration can satisfy all requirements.
-
-        Iterates over every required capability and delegates to
-        ``TargetConfiguration.ensure_can_handle``, which checks native support
-        first and then consults the handling policy. All violations are
-        collected and reported in a single ``ValueError``.
+        Validate that ``target`` can satisfy every declared requirement.
 
         Args:
-            configuration (TargetConfiguration): The target configuration to validate against.
+            target (PromptTarget): The target to validate against.
 
         Raises:
-            ValueError: If any required capability is missing and the policy
-                does not allow adaptation.
+            ValueError: If any ``native_required`` capability is not natively
+                supported, or if any ``required`` capability is not supported
+                natively and has no ``ADAPT`` entry in the target's policy.
         """
-        errors: list[str] = []
-        for capability in sorted(self.required_capabilities, key=lambda c: c.value):
-            try:
-                configuration.ensure_can_handle(capability=capability)
-            except ValueError as exc:
-                errors.append(str(exc))
-        if errors:
-            raise ValueError(
-                f"Target does not satisfy {len(errors)} required capability(ies):\n"
-                + "\n".join(f"  - {e}" for e in errors)
-            )
+        for capability in self.native_required:
+            if not target.configuration.includes(capability=capability):
+                raise ValueError(
+                    f"Target must natively support '{capability.value}'; "
+                    "adaptation is not acceptable for this consumer."
+                )
+        for capability in self.required:
+            target.configuration.ensure_can_handle(capability=capability)
+
+
+# Shared requirement used by scorers and converters that set a system prompt
+# and drive a short multi-turn conversation. Adaptation is acceptable, native
+# support is not required.
+CHAT_CONSUMER_REQUIREMENTS = TargetRequirements(
+    required=frozenset({CapabilityName.EDITABLE_HISTORY, CapabilityName.MULTI_TURN}),
+)
diff --git a/pyrit/prompt_target/openai/openai_chat_target.py b/pyrit/prompt_target/openai/openai_chat_target.py
index db059d6807..5e45136043 100644
--- a/pyrit/prompt_target/openai/openai_chat_target.py
+++ b/pyrit/prompt_target/openai/openai_chat_target.py
@@ -72,6 +72,7 @@ class OpenAIChatTarget(OpenAITarget, PromptChatTarget):
             supports_json_output=True,
             supports_multi_message_pieces=True,
             supports_system_prompt=True,
+            supports_editable_history=True,
             input_modalities=frozenset(
                 {frozenset({"text"}), frozenset({"image_path"}), frozenset({"text", "image_path"})}
             ),
diff --git a/pyrit/scenario/core/scenario.py b/pyrit/scenario/core/scenario.py
index 283636f081..bd7e40292b 100644
--- a/pyrit/scenario/core/scenario.py
+++ b/pyrit/scenario/core/scenario.py
@@ -14,7 +14,7 @@
 import uuid
 from abc import ABC, abstractmethod
 from collections.abc import Sequence
-from typing import TYPE_CHECKING, Optional, Union, cast
+from typing import TYPE_CHECKING, ClassVar, Optional, Union, cast
 
 from tqdm.auto import tqdm
 
@@ -25,6 +25,7 @@
 from pyrit.models import AttackResult
 from pyrit.models.scenario_result import ScenarioIdentifier, ScenarioResult
 from pyrit.prompt_target import OpenAIChatTarget, PromptTarget
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 from pyrit.registry import ScorerRegistry
 from pyrit.scenario.core.atomic_attack import AtomicAttack
 from pyrit.scenario.core.attack_technique import AttackTechnique
@@ -50,6 +51,10 @@ class Scenario(ABC):
     aggregates the results into a ScenarioResult.
     """
 
+    #: Capability requirements placed on ``objective_target``. Subclasses override to declare
+    #: what the scenario needs. Validated in ``initialize_async`` once the target is supplied.
+    TARGET_REQUIREMENTS: ClassVar[TargetRequirements] = TargetRequirements()
+
     def __init__(
         self,
         *,
@@ -316,6 +321,7 @@ async def initialize_async(
         # Set instance variables from parameters
         self._objective_target = objective_target
         self._objective_target_identifier = objective_target.get_identifier()
+        type(self).TARGET_REQUIREMENTS.validate(target=objective_target)
         self._dataset_config_provided = dataset_config is not None
         self._dataset_config = dataset_config if dataset_config else self.default_dataset_config()
         self._max_concurrency = max_concurrency
diff --git a/pyrit/scenario/scenarios/airt/psychosocial.py b/pyrit/scenario/scenarios/airt/psychosocial.py
index b8963b9264..0d7be337fb 100644
--- a/pyrit/scenario/scenarios/airt/psychosocial.py
+++ b/pyrit/scenario/scenarios/airt/psychosocial.py
@@ -28,6 +28,8 @@
     PromptConverterConfiguration,
 )
 from pyrit.prompt_target import OpenAIChatTarget, PromptChatTarget
+from pyrit.prompt_target.common.target_capabilities import CapabilityName
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 from pyrit.scenario.core.atomic_attack import AtomicAttack
 from pyrit.scenario.core.attack_technique import AttackTechnique
 from pyrit.scenario.core.dataset_configuration import DatasetConfiguration
@@ -147,6 +149,13 @@ class Psychosocial(Scenario):
 
     VERSION: int = 1
 
+    #: Psychosocial runs CrescendoAttack, which requires the target to natively support
+    #: editable conversation history (for backtracking). Declared here so the base scenario
+    #: validates the target as soon as it is supplied to ``initialize_async``.
+    TARGET_REQUIREMENTS = TargetRequirements(
+        native_required=frozenset({CapabilityName.EDITABLE_HISTORY}),
+    )
+
     # Set up default subharm configurations
     # Each subharm (e.g., 'imminent_crisis', 'licensed_therapist') can have unique escalation/scoring
     # The key is the harm_category_filter value from the strategy
@@ -421,10 +430,6 @@ def _get_scorer(self, subharm: Optional[str] = None) -> FloatScaleThresholdScore
     async def _get_atomic_attacks_async(self) -> list[AtomicAttack]:
         if self._objective_target is None:
             raise ValueError("objective_target must be set before creating attacks")
-        if not isinstance(self._objective_target, PromptChatTarget):
-            raise TypeError(
-                f"PsychosocialHarmsScenario requires a PromptChatTarget, got {type(self._objective_target).__name__}"
-            )
         resolved = self._resolve_seed_groups()
         self._seed_groups = resolved.seed_groups
 
diff --git a/pyrit/score/float_scale/float_scale_scorer.py b/pyrit/score/float_scale/float_scale_scorer.py
index a117034b3b..8e36895ee3 100644
--- a/pyrit/score/float_scale/float_scale_scorer.py
+++ b/pyrit/score/float_scale/float_scale_scorer.py
@@ -7,7 +7,7 @@
 from pyrit.exceptions.exception_classes import InvalidJsonException
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import PromptDataType, Score, UnvalidatedScore
-from pyrit.prompt_target.common.prompt_chat_target import PromptChatTarget
+from pyrit.prompt_target.common.prompt_target import PromptTarget
 from pyrit.score.scorer import Scorer
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 
@@ -24,14 +24,16 @@ class FloatScaleScorer(Scorer):
     is scored independently, returning one score per piece.
     """
 
-    def __init__(self, *, validator: ScorerPromptValidator) -> None:
+    def __init__(self, *, validator: ScorerPromptValidator, chat_target: Optional[PromptTarget] = None) -> None:
         """
         Initialize the FloatScaleScorer.
 
         Args:
             validator: A validator object used to validate scores.
+            chat_target: Optional chat target used by the scorer, forwarded to the base class
+                for validation against ``TARGET_REQUIREMENTS``.
         """
-        super().__init__(validator=validator)
+        super().__init__(validator=validator, chat_target=chat_target)
 
     def validate_return_scores(self, scores: list[Score]) -> None:
         """
@@ -70,7 +72,7 @@ def get_scorer_metrics(self) -> Optional["HarmScorerMetrics"]:
     async def _score_value_with_llm(
         self,
         *,
-        prompt_target: PromptChatTarget,
+        prompt_target: PromptTarget,
         system_prompt: str,
         message_value: str,
         message_data_type: PromptDataType,
diff --git a/pyrit/score/float_scale/insecure_code_scorer.py b/pyrit/score/float_scale/insecure_code_scorer.py
index 45c64dab00..dcc91a1992 100644
--- a/pyrit/score/float_scale/insecure_code_scorer.py
+++ b/pyrit/score/float_scale/insecure_code_scorer.py
@@ -9,7 +9,7 @@
 from pyrit.exceptions.exception_classes import InvalidJsonException
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.float_scale.float_scale_scorer import FloatScaleScorer
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 
@@ -21,11 +21,12 @@ class InsecureCodeScorer(FloatScaleScorer):
     """
 
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator(supported_data_types=["text"])
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         system_prompt_path: Optional[Union[str, Path]] = None,
         validator: Optional[ScorerPromptValidator] = None,
     ):
@@ -33,12 +34,12 @@ def __init__(
         Initialize the Insecure Code Scorer.
 
         Args:
-            chat_target (PromptChatTarget): The target to use for scoring code security.
+            chat_target (PromptTarget): The target to use for scoring code security.
             system_prompt_path (Optional[Union[str, Path]]): Path to the YAML file containing the system prompt.
                 Defaults to the default insecure code scoring prompt if not provided.
             validator (Optional[ScorerPromptValidator]): Custom validator for the scorer. Defaults to None.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, chat_target=chat_target)
 
         self._prompt_target = chat_target
 
diff --git a/pyrit/score/float_scale/self_ask_general_float_scale_scorer.py b/pyrit/score/float_scale/self_ask_general_float_scale_scorer.py
index ae9e0acc4b..3abbc9cf85 100644
--- a/pyrit/score/float_scale/self_ask_general_float_scale_scorer.py
+++ b/pyrit/score/float_scale/self_ask_general_float_scale_scorer.py
@@ -5,13 +5,14 @@
 
 from typing import TYPE_CHECKING, Optional
 
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS
 from pyrit.score.float_scale.float_scale_scorer import FloatScaleScorer
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 
 if TYPE_CHECKING:
     from pyrit.identifiers import ComponentIdentifier
     from pyrit.models import MessagePiece, Score, UnvalidatedScore
-    from pyrit.prompt_target import PromptChatTarget
+    from pyrit.prompt_target import PromptTarget
 
 
 class SelfAskGeneralFloatScaleScorer(FloatScaleScorer):
@@ -24,11 +25,12 @@ class SelfAskGeneralFloatScaleScorer(FloatScaleScorer):
         supported_data_types=["text"],
         is_objective_required=True,
     )
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         system_prompt_format_string: str,
         prompt_format_string: Optional[str] = None,
         category: Optional[str] = None,
@@ -52,7 +54,9 @@ def __init__(
         in the response, the provided `category` argument will be applied.
 
         Args:
-            chat_target (PromptChatTarget): The chat target used to score.
+            chat_target (PromptTarget): The chat target used to score. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             system_prompt_format_string (str): System prompt template with placeholders for
                 objective, prompt, and message_piece.
             prompt_format_string (Optional[str]): User prompt template with the same placeholders.
@@ -71,7 +75,7 @@ def __init__(
             ValueError: If system_prompt_format_string is not provided or empty.
             ValueError: If min_value is greater than max_value.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, chat_target=chat_target)
         self._prompt_target = chat_target
         if not system_prompt_format_string:
             raise ValueError("system_prompt_format_string must be provided and non-empty.")
diff --git a/pyrit/score/float_scale/self_ask_likert_scorer.py b/pyrit/score/float_scale/self_ask_likert_scorer.py
index c6762089b6..458a60c650 100644
--- a/pyrit/score/float_scale/self_ask_likert_scorer.py
+++ b/pyrit/score/float_scale/self_ask_likert_scorer.py
@@ -12,7 +12,7 @@
 from pyrit.common.path import HARM_DEFINITION_PATH, SCORER_LIKERT_PATH
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt, UnvalidatedScore
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.float_scale.float_scale_scorer import FloatScaleScorer
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 
@@ -173,11 +173,12 @@ class SelfAskLikertScorer(FloatScaleScorer):
     """
 
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator(supported_data_types=["text"])
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         likert_scale: Optional[LikertScalePaths] = None,
         custom_likert_path: Optional[Path] = None,
         custom_system_prompt_path: Optional[Path] = None,
@@ -187,7 +188,7 @@ def __init__(
         Initialize the SelfAskLikertScorer.
 
         Args:
-            chat_target (PromptChatTarget): The chat target to use for scoring.
+            chat_target (PromptTarget): The chat target to use for scoring.
             likert_scale (Optional[LikertScalePaths]): The Likert scale configuration to use for scoring.
             custom_likert_path (Optional[Path]): Path to a custom YAML file containing the Likert scale definition.
                 This allows users to use their own Likert scales without modifying the code, as long as
@@ -201,7 +202,7 @@ def __init__(
             ValueError: If both `likert_scale` and `custom_likert_path` are provided, if neither is provided,
                 or if the provided Likert scale or system prompt YAML file is improperly formatted.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, chat_target=chat_target)
 
         self._prompt_target = chat_target
         self._likert_scale = likert_scale
diff --git a/pyrit/score/float_scale/self_ask_scale_scorer.py b/pyrit/score/float_scale/self_ask_scale_scorer.py
index 4bf0dc2dee..2ea1d27807 100644
--- a/pyrit/score/float_scale/self_ask_scale_scorer.py
+++ b/pyrit/score/float_scale/self_ask_scale_scorer.py
@@ -11,7 +11,7 @@
 from pyrit.common.path import SCORER_SCALES_PATH
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt, UnvalidatedScore
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.float_scale.float_scale_scorer import FloatScaleScorer
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 
@@ -39,11 +39,12 @@ class SystemPaths(enum.Enum):
         supported_data_types=["text"],
         is_objective_required=True,
     )
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         scale_arguments_path: Optional[Union[Path, str]] = None,
         system_prompt_path: Optional[Union[Path, str]] = None,
         validator: Optional[ScorerPromptValidator] = None,
@@ -52,14 +53,14 @@ def __init__(
         Initialize the SelfAskScaleScorer.
 
         Args:
-            chat_target (PromptChatTarget): The chat target to use for scoring.
+            chat_target (PromptTarget): The chat target to use for scoring.
             scale_arguments_path (Optional[Union[Path, str]]): Path to the YAML file containing scale definitions.
                 Defaults to TREE_OF_ATTACKS_SCALE if not provided.
             system_prompt_path (Optional[Union[Path, str]]): Path to the YAML file containing the system prompt.
                 Defaults to GENERAL_SYSTEM_PROMPT if not provided.
             validator (Optional[ScorerPromptValidator]): Custom validator for the scorer. Defaults to None.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, chat_target=chat_target)
 
         self._prompt_target = chat_target
 
diff --git a/pyrit/score/scorer.py b/pyrit/score/scorer.py
index 11308edb64..79db6936e9 100644
--- a/pyrit/score/scorer.py
+++ b/pyrit/score/scorer.py
@@ -12,6 +12,7 @@
 from typing import (
     TYPE_CHECKING,
     Any,
+    ClassVar,
     Optional,
     Union,
     cast,
@@ -35,11 +36,12 @@
     UnvalidatedScore,
 )
 from pyrit.prompt_target.batch_helper import batch_task_async
+from pyrit.prompt_target.common.target_requirements import TargetRequirements
 
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
-    from pyrit.prompt_target import PromptChatTarget, PromptTarget
+    from pyrit.prompt_target import PromptTarget
     from pyrit.score.scorer_evaluation.metrics_type import RegistryUpdateBehavior
     from pyrit.score.scorer_evaluation.scorer_evaluator import (
         ScorerEvalDatasetFiles,
@@ -59,16 +61,26 @@ class Scorer(Identifiable, abc.ABC):
     # Specifies glob patterns for datasets and a result file name.
     evaluation_file_mapping: Optional[ScorerEvalDatasetFiles] = None
 
+    #: Capability requirements placed on the scorer's chat target (if any).
+    #: Subclasses that use a chat target should override this and pass the
+    #: target to ``super().__init__(chat_target=...)`` so the base class can
+    #: validate it.
+    TARGET_REQUIREMENTS: ClassVar[TargetRequirements] = TargetRequirements()
+
     _identifier: Optional[ComponentIdentifier] = None
 
-    def __init__(self, *, validator: ScorerPromptValidator):
+    def __init__(self, *, validator: ScorerPromptValidator, chat_target: Optional[PromptTarget] = None):
         """
         Initialize the Scorer.
 
         Args:
             validator (ScorerPromptValidator): Validator for message pieces and scorer configuration.
+            chat_target (Optional[PromptTarget]): Chat target used by the scorer, if any. When
+                provided, it is validated against ``TARGET_REQUIREMENTS``.
         """
         self._validator = validator
+        if chat_target is not None:
+            type(self).TARGET_REQUIREMENTS.validate(target=chat_target)
 
     def get_identifier(self) -> ComponentIdentifier:
         """
@@ -494,7 +506,7 @@ def scale_value_float(self, value: float, min_value: float, max_value: float) ->
     async def _score_value_with_llm(
         self,
         *,
-        prompt_target: PromptChatTarget,
+        prompt_target: PromptTarget,
         system_prompt: str,
         message_value: str,
         message_data_type: PromptDataType,
@@ -516,7 +528,7 @@ async def _score_value_with_llm(
         description fields.
 
         Args:
-            prompt_target (PromptChatTarget): The target LLM to send the message to.
+            prompt_target (PromptTarget): The target LLM to send the message to.
             system_prompt (str): The system-level prompt that guides the behavior of the target LLM.
             message_value (str): The actual value or content to be scored by the LLM (e.g., text, image path,
                 audio path).
diff --git a/pyrit/score/true_false/gandalf_scorer.py b/pyrit/score/true_false/gandalf_scorer.py
index 2aab7c264e..7016d881f2 100644
--- a/pyrit/score/true_false/gandalf_scorer.py
+++ b/pyrit/score/true_false/gandalf_scorer.py
@@ -11,7 +11,7 @@
 from pyrit.exceptions import PyritException, pyrit_target_retry
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import Message, MessagePiece, Score
-from pyrit.prompt_target import GandalfLevel, PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, GandalfLevel, PromptTarget
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 from pyrit.score.true_false.true_false_score_aggregator import (
     TrueFalseAggregatorFunc,
@@ -30,12 +30,13 @@ class GandalfScorer(TrueFalseScorer):
     """
 
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator(supported_data_types=["text"])
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
         level: GandalfLevel,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         validator: Optional[ScorerPromptValidator] = None,
         score_aggregator: TrueFalseAggregatorFunc = TrueFalseScoreAggregator.OR,
     ) -> None:
@@ -44,12 +45,18 @@ def __init__(
 
         Args:
             level (GandalfLevel): The Gandalf challenge level to score against.
-            chat_target (PromptChatTarget): The chat target used for password extraction.
+            chat_target (PromptTarget): The chat target to use for the scorer. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             validator (Optional[ScorerPromptValidator]): Custom validator. Defaults to text data type validator.
             score_aggregator (TrueFalseAggregatorFunc): Aggregator for combining scores. Defaults to
                 TrueFalseScoreAggregator.OR.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, score_aggregator=score_aggregator)
+        super().__init__(
+            validator=validator or self._DEFAULT_VALIDATOR,
+            score_aggregator=score_aggregator,
+            chat_target=chat_target,
+        )
 
         self._prompt_target = chat_target
         self._defender = level.value
diff --git a/pyrit/score/true_false/self_ask_category_scorer.py b/pyrit/score/true_false/self_ask_category_scorer.py
index 7102ba3af6..6f1bc8e49d 100644
--- a/pyrit/score/true_false/self_ask_category_scorer.py
+++ b/pyrit/score/true_false/self_ask_category_scorer.py
@@ -11,7 +11,7 @@
 from pyrit.common.path import SCORER_CONTENT_CLASSIFIERS_PATH
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt, UnvalidatedScore
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 from pyrit.score.true_false.true_false_score_aggregator import (
     TrueFalseAggregatorFunc,
@@ -37,11 +37,12 @@ class SelfAskCategoryScorer(TrueFalseScorer):
     """
 
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator()
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         content_classifier_path: Union[str, Path],
         score_aggregator: TrueFalseAggregatorFunc = TrueFalseScoreAggregator.OR,
         validator: Optional[ScorerPromptValidator] = None,
@@ -50,13 +51,19 @@ def __init__(
         Initialize a new instance of the SelfAskCategoryScorer class.
 
         Args:
-            chat_target (PromptChatTarget): The chat target to interact with.
+            chat_target (PromptTarget): The chat target to use for the scorer. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             content_classifier_path (Union[str, Path]): The path to the classifier YAML file.
             score_aggregator (TrueFalseAggregatorFunc): The aggregator function to use.
                 Defaults to TrueFalseScoreAggregator.OR.
             validator (Optional[ScorerPromptValidator]): Custom validator. Defaults to None.
         """
-        super().__init__(score_aggregator=score_aggregator, validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(
+            score_aggregator=score_aggregator,
+            validator=validator or self._DEFAULT_VALIDATOR,
+            chat_target=chat_target,
+        )
 
         self._prompt_target = chat_target
 
diff --git a/pyrit/score/true_false/self_ask_general_true_false_scorer.py b/pyrit/score/true_false/self_ask_general_true_false_scorer.py
index 44bb362748..b3d3a080da 100644
--- a/pyrit/score/true_false/self_ask_general_true_false_scorer.py
+++ b/pyrit/score/true_false/self_ask_general_true_false_scorer.py
@@ -5,6 +5,7 @@
 
 from typing import TYPE_CHECKING, Optional
 
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 from pyrit.score.true_false.true_false_score_aggregator import (
     TrueFalseAggregatorFunc,
@@ -15,7 +16,7 @@
 if TYPE_CHECKING:
     from pyrit.identifiers import ComponentIdentifier
     from pyrit.models import MessagePiece, Score, UnvalidatedScore
-    from pyrit.prompt_target import PromptChatTarget
+    from pyrit.prompt_target import PromptTarget
 
 
 class SelfAskGeneralTrueFalseScorer(TrueFalseScorer):
@@ -28,11 +29,12 @@ class SelfAskGeneralTrueFalseScorer(TrueFalseScorer):
         supported_data_types=["text"],
         is_objective_required=False,
     )
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         system_prompt_format_string: str,
         prompt_format_string: Optional[str] = None,
         category: Optional[str] = None,
@@ -55,7 +57,9 @@ def __init__(
         in the response, the provided `category` argument will be applied.
 
         Args:
-            chat_target (PromptChatTarget): The chat target used to score.
+            chat_target (PromptTarget): The chat target used to score. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             system_prompt_format_string (str): System prompt template with placeholders for
                 objective, task (alias of objective), prompt, and message_piece.
             prompt_format_string (Optional[str]): User prompt template with the same placeholders.
@@ -73,7 +77,11 @@ def __init__(
         Raises:
             ValueError: If system_prompt_format_string is not provided or empty.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, score_aggregator=score_aggregator)
+        super().__init__(
+            validator=validator or self._DEFAULT_VALIDATOR,
+            score_aggregator=score_aggregator,
+            chat_target=chat_target,
+        )
         self._prompt_target = chat_target
         if not system_prompt_format_string:
             raise ValueError("system_prompt_format_string must be provided and non-empty.")
diff --git a/pyrit/score/true_false/self_ask_question_answer_scorer.py b/pyrit/score/true_false/self_ask_question_answer_scorer.py
index bf1c017dde..c6d35cdfe8 100644
--- a/pyrit/score/true_false/self_ask_question_answer_scorer.py
+++ b/pyrit/score/true_false/self_ask_question_answer_scorer.py
@@ -18,7 +18,7 @@
     import pathlib
 
     from pyrit.models import MessagePiece, Score, UnvalidatedScore
-    from pyrit.prompt_target import PromptChatTarget
+    from pyrit.prompt_target import PromptTarget
 
 
 class SelfAskQuestionAnswerScorer(SelfAskTrueFalseScorer):
@@ -37,7 +37,7 @@ class SelfAskQuestionAnswerScorer(SelfAskTrueFalseScorer):
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         true_false_question_path: Optional[pathlib.Path] = None,
         validator: Optional[ScorerPromptValidator] = None,
         score_aggregator: TrueFalseAggregatorFunc = TrueFalseScoreAggregator.OR,
@@ -46,7 +46,9 @@ def __init__(
         Initialize the SelfAskQuestionAnswerScorer object.
 
         Args:
-            chat_target (PromptChatTarget): The chat target to use for the scorer.
+            chat_target (PromptTarget): The chat target to use for the scorer. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             true_false_question_path (Optional[pathlib.Path]): The path to the true/false question file.
                 Defaults to None, which uses the default question_answering.yaml file.
             validator (Optional[ScorerPromptValidator]): Custom validator. Defaults to None.
diff --git a/pyrit/score/true_false/self_ask_refusal_scorer.py b/pyrit/score/true_false/self_ask_refusal_scorer.py
index cf9b30f1d8..c7d2010011 100644
--- a/pyrit/score/true_false/self_ask_refusal_scorer.py
+++ b/pyrit/score/true_false/self_ask_refusal_scorer.py
@@ -8,7 +8,7 @@
 from pyrit.common.path import SCORER_SEED_PROMPT_PATH
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt, UnvalidatedScore
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 from pyrit.score.true_false.true_false_score_aggregator import (
     TrueFalseAggregatorFunc,
@@ -64,11 +64,12 @@ class SelfAskRefusalScorer(TrueFalseScorer):
     """
 
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator()
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         refusal_system_prompt_path: Union[RefusalScorerPaths, Path, str] = RefusalScorerPaths.OBJECTIVE_STRICT,
         prompt_format_string: Optional[str] = None,
         validator: Optional[ScorerPromptValidator] = None,
@@ -78,7 +79,9 @@ def __init__(
         Initialize the SelfAskRefusalScorer.
 
         Args:
-            chat_target (PromptChatTarget): The endpoint that will be used to score the prompt.
+            chat_target (PromptTarget): The chat target to use for the scorer. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             refusal_system_prompt_path (Union[RefusalScorerPaths, Path, str]): The path to the system prompt
                 to use for refusal detection. Can be a RefusalScorerPaths enum value, a Path, or a string path.
                 Defaults to RefusalScorerPaths.OBJECTIVE_STRICT.
@@ -100,7 +103,11 @@ def __init__(
             result_file="refusal_scorer/refusal_metrics.jsonl",
         )
 
-        super().__init__(score_aggregator=score_aggregator, validator=validator or self._DEFAULT_VALIDATOR)
+        super().__init__(
+            score_aggregator=score_aggregator,
+            validator=validator or self._DEFAULT_VALIDATOR,
+            chat_target=chat_target,
+        )
 
         self._prompt_target = chat_target
 
diff --git a/pyrit/score/true_false/self_ask_true_false_scorer.py b/pyrit/score/true_false/self_ask_true_false_scorer.py
index d79060fcb4..fcf714f339 100644
--- a/pyrit/score/true_false/self_ask_true_false_scorer.py
+++ b/pyrit/score/true_false/self_ask_true_false_scorer.py
@@ -12,7 +12,7 @@
 from pyrit.common.path import SCORER_SEED_PROMPT_PATH
 from pyrit.identifiers import ComponentIdentifier
 from pyrit.models import MessagePiece, Score, SeedPrompt
-from pyrit.prompt_target import PromptChatTarget
+from pyrit.prompt_target import CHAT_CONSUMER_REQUIREMENTS, PromptTarget
 from pyrit.score.scorer_prompt_validator import ScorerPromptValidator
 from pyrit.score.true_false.true_false_score_aggregator import (
     TrueFalseAggregatorFunc,
@@ -93,11 +93,12 @@ class SelfAskTrueFalseScorer(TrueFalseScorer):
     _DEFAULT_VALIDATOR: ScorerPromptValidator = ScorerPromptValidator(
         supported_data_types=["text", "image_path"],
     )
+    TARGET_REQUIREMENTS = CHAT_CONSUMER_REQUIREMENTS
 
     def __init__(
         self,
         *,
-        chat_target: PromptChatTarget,
+        chat_target: PromptTarget,
         true_false_question_path: Optional[Union[str, Path]] = None,
         true_false_question: Optional[TrueFalseQuestion] = None,
         true_false_system_prompt_path: Optional[Union[str, Path]] = None,
@@ -108,7 +109,9 @@ def __init__(
         Initialize the SelfAskTrueFalseScorer.
 
         Args:
-            chat_target (PromptChatTarget): The chat target to interact with.
+            chat_target (PromptTarget): The chat target to use for the scorer. Must satisfy
+                CHAT_CONSUMER_REQUIREMENTS (multi-turn + editable history capabilities,
+                possibly via normalization-pipeline adaptation).
             true_false_question_path (Optional[Union[str, Path]]): The path to the true/false question file.
             true_false_question (Optional[TrueFalseQuestion]): The true/false question object.
             true_false_system_prompt_path (Optional[Union[str, Path]]): The path to the system prompt file.
@@ -120,7 +123,11 @@ def __init__(
             ValueError: If both true_false_question_path and true_false_question are provided.
             ValueError: If required keys are missing in true_false_question.
         """
-        super().__init__(validator=validator or self._DEFAULT_VALIDATOR, score_aggregator=score_aggregator)
+        super().__init__(
+            validator=validator or self._DEFAULT_VALIDATOR,
+            score_aggregator=score_aggregator,
+            chat_target=chat_target,
+        )
 
         self._prompt_target = chat_target
 
diff --git a/pyrit/score/true_false/true_false_scorer.py b/pyrit/score/true_false/true_false_scorer.py
index b0c90c0737..6b6e79815e 100644
--- a/pyrit/score/true_false/true_false_scorer.py
+++ b/pyrit/score/true_false/true_false_scorer.py
@@ -12,6 +12,7 @@
 )
 
 if TYPE_CHECKING:
+    from pyrit.prompt_target import PromptTarget
     from pyrit.score.scorer_evaluation.scorer_evaluator import ScorerEvalDatasetFiles
     from pyrit.score.scorer_evaluation.scorer_metrics import ObjectiveScorerMetrics
 
@@ -33,6 +34,7 @@ def __init__(
         *,
         validator: ScorerPromptValidator,
         score_aggregator: TrueFalseAggregatorFunc = TrueFalseScoreAggregator.OR,
+        chat_target: Optional["PromptTarget"] = None,
     ) -> None:
         """
         Initialize the TrueFalseScorer.
@@ -41,6 +43,8 @@ def __init__(
             validator (ScorerPromptValidator): Custom validator.
             score_aggregator (TrueFalseAggregatorFunc): The aggregator function to use.
                 Defaults to TrueFalseScoreAggregator.OR.
+            chat_target (Optional[PromptTarget]): Optional chat target used by the scorer,
+                forwarded to the base class for validation against ``TARGET_REQUIREMENTS``.
         """
         self._score_aggregator = score_aggregator
 
@@ -55,7 +59,7 @@ def __init__(
                 result_file="objective/objective_achieved_metrics.jsonl",
             )
 
-        super().__init__(validator=validator)
+        super().__init__(validator=validator, chat_target=chat_target)
 
     def validate_return_scores(self, scores: list[Score]) -> None:
         """
diff --git a/tests/unit/backend/test_converter_service.py b/tests/unit/backend/test_converter_service.py
index 418441385e..385ddb7d5f 100644
--- a/tests/unit/backend/test_converter_service.py
+++ b/tests/unit/backend/test_converter_service.py
@@ -413,6 +413,7 @@ def _try_instantiate_converter(converter_name: str):
 
     from pyrit.common.apply_defaults import _RequiredValueSentinel
     from pyrit.prompt_target.common.prompt_chat_target import PromptChatTarget
+    from pyrit.prompt_target.common.prompt_target import PromptTarget
 
     # Converters requiring external credentials or resources that can't be mocked
     # at the constructor level — these validate env vars / files in __init__ body
@@ -461,11 +462,18 @@ def _try_instantiate_converter(converter_name: str):
         ann = param.annotation
         ann_str = str(ann) if ann is not inspect.Parameter.empty else ""
 
-        # PromptChatTarget — mock it with a proper identifier
+        # PromptChatTarget / PromptTarget — mock it with a proper identifier
         if ann is not inspect.Parameter.empty and (
-            (isinstance(ann, type) and issubclass(ann, PromptChatTarget)) or "PromptChatTarget" in ann_str
+            (isinstance(ann, type) and issubclass(ann, PromptTarget))
+            or "PromptChatTarget" in ann_str
+            or "PromptTarget" in ann_str
         ):
-            mock_target = MagicMock(spec=PromptChatTarget)
+            spec_cls = (
+                PromptChatTarget
+                if (isinstance(ann, type) and issubclass(ann, PromptChatTarget)) or "PromptChatTarget" in ann_str
+                else PromptTarget
+            )
+            mock_target = MagicMock(spec=spec_cls)
             mock_target.__class__.__name__ = "MockChatTarget"
             # Configure get_identifier() to return a proper identifier-like object
             # so that _create_identifier can extract class_name, model_name, etc.
diff --git a/tests/unit/executor/attack/component/test_conversation_manager.py b/tests/unit/executor/attack/component/test_conversation_manager.py
index c86e741e9c..5c2f0f4c79 100644
--- a/tests/unit/executor/attack/component/test_conversation_manager.py
+++ b/tests/unit/executor/attack/component/test_conversation_manager.py
@@ -94,7 +94,13 @@ def mock_chat_target() -> MagicMock:
 @pytest.fixture
 def mock_prompt_target() -> MagicMock:
     """Create a mock prompt target (non-chat) for testing."""
+    from pyrit.prompt_target.common.target_capabilities import TargetCapabilities
+    from pyrit.prompt_target.common.target_configuration import TargetConfiguration
+
     target = MagicMock(spec=PromptTarget)
+    target.configuration = TargetConfiguration(
+        capabilities=TargetCapabilities(supports_multi_turn=False, supports_system_prompt=False),
+    )
     target.get_identifier.return_value = _mock_target_id("MockTarget")
     return target
 
@@ -1059,7 +1065,7 @@ async def test_non_chat_target_behavior_raise_explicit(
         config = PrependedConversationConfig(non_chat_target_behavior="raise")
 
         with pytest.raises(
-            ValueError, match="prepended_conversation requires the objective target to be a PromptChatTarget"
+            ValueError, match="prepended_conversation requires the objective target to be a chat-capable"
         ):
             await manager.initialize_context_async(
                 context=context,
diff --git a/tests/unit/executor/attack/multi_turn/test_supports_multi_turn_attacks.py b/tests/unit/executor/attack/multi_turn/test_supports_multi_turn_attacks.py
index 3baeaf463c..9de79ab384 100644
--- a/tests/unit/executor/attack/multi_turn/test_supports_multi_turn_attacks.py
+++ b/tests/unit/executor/attack/multi_turn/test_supports_multi_turn_attacks.py
@@ -27,6 +27,7 @@ def _make_strategy(*, supports_multi_turn: bool):
 
     target = MagicMock()
     target.capabilities.supports_multi_turn = supports_multi_turn
+    target.configuration.includes.return_value = supports_multi_turn
     target.get_identifier.return_value = MagicMock()
 
     with patch.multiple(
@@ -376,6 +377,7 @@ def _make_tap_node(self, *, supports_multi_turn: bool):
 
         target = MagicMock()
         target.capabilities.supports_multi_turn = supports_multi_turn
+        target.configuration.includes.return_value = supports_multi_turn
         target.get_identifier.return_value = MagicMock()
 
         adversarial_chat = MagicMock()
@@ -684,8 +686,14 @@ class TestValueErrorGuards:
     """Test that incompatible attacks raise ValueError for single-turn targets."""
 
     def _make_single_turn_target(self):
+        from pyrit.prompt_target.common.target_capabilities import TargetCapabilities
+        from pyrit.prompt_target.common.target_configuration import TargetConfiguration
+
         target = MagicMock()
         target.capabilities.supports_multi_turn = False
+        target.configuration = TargetConfiguration(
+            capabilities=TargetCapabilities(supports_multi_turn=False, supports_system_prompt=True),
+        )
         target.get_identifier.return_value = MagicMock()
         return target
 
@@ -706,52 +714,34 @@ def _make_scoring_config(self):
 
     @pytest.mark.asyncio
     async def test_crescendo_raises_for_single_turn_target(self):
-        from pyrit.executor.attack.multi_turn.crescendo import CrescendoAttack, CrescendoAttackContext
+        from pyrit.executor.attack.multi_turn.crescendo import CrescendoAttack
 
         target = self._make_single_turn_target()
-        attack = CrescendoAttack(
-            objective_target=target,
-            attack_adversarial_config=self._make_adversarial_config(),
-            attack_scoring_config=self._make_scoring_config(),
-        )
-
-        context = CrescendoAttackContext(
-            params=AttackParameters(objective="Test"),
-        )
 
-        with pytest.raises(ValueError, match="CrescendoAttack requires a multi-turn target"):
-            await attack._setup_async(context=context)
+        with pytest.raises(ValueError, match="supports_multi_turn"):
+            CrescendoAttack(
+                objective_target=target,
+                attack_adversarial_config=self._make_adversarial_config(),
+                attack_scoring_config=self._make_scoring_config(),
+            )
 
     @pytest.mark.asyncio
     async def test_multi_prompt_sending_raises_for_single_turn_target(self):
         from pyrit.executor.attack.multi_turn.multi_prompt_sending import MultiPromptSendingAttack
 
         target = self._make_single_turn_target()
-        attack = MultiPromptSendingAttack(objective_target=target)
-
-        context = MultiTurnAttackContext(
-            params=AttackParameters(objective="Test"),
-        )
 
-        with pytest.raises(ValueError, match="MultiPromptSendingAttack requires a multi-turn target"):
-            await attack._setup_async(context=context)
+        with pytest.raises(ValueError, match="supports_multi_turn"):
+            MultiPromptSendingAttack(objective_target=target)
 
     @pytest.mark.asyncio
     async def test_chunked_request_raises_for_single_turn_target(self):
-        from pyrit.executor.attack.multi_turn.chunked_request import (
-            ChunkedRequestAttack,
-            ChunkedRequestAttackContext,
-        )
+        from pyrit.executor.attack.multi_turn.chunked_request import ChunkedRequestAttack
 
         target = self._make_single_turn_target()
-        attack = ChunkedRequestAttack(objective_target=target)
-
-        context = ChunkedRequestAttackContext(
-            params=AttackParameters(objective="Test"),
-        )
 
-        with pytest.raises(ValueError, match="ChunkedRequestAttack requires a multi-turn target"):
-            await attack._setup_async(context=context)
+        with pytest.raises(ValueError, match="supports_multi_turn"):
+            ChunkedRequestAttack(objective_target=target)
 
 
 @pytest.mark.usefixtures("patch_central_database")
@@ -764,6 +754,7 @@ def _make_tap_node(self, *, supports_multi_turn: bool):
 
         target = MagicMock()
         target.capabilities.supports_multi_turn = supports_multi_turn
+        target.configuration.includes.return_value = supports_multi_turn
         target.get_identifier.return_value = MagicMock()
 
         adversarial_chat = MagicMock()
diff --git a/tests/unit/prompt_converter/test_prompt_converter.py b/tests/unit/prompt_converter/test_prompt_converter.py
index 35dc595339..e19682a4e2 100644
--- a/tests/unit/prompt_converter/test_prompt_converter.py
+++ b/tests/unit/prompt_converter/test_prompt_converter.py
@@ -2,6 +2,7 @@
 # Licensed under the MIT license.
 
 import re
+from unittest.mock import patch
 
 import pytest
 from unit.mocks import MockPromptTarget
@@ -579,3 +580,22 @@ def test_llm_based_converters_supported_types(
     converter = converter_class(**converter_args)
     assert sorted(converter.supported_input_types) == sorted(expected_input_types)
     assert sorted(converter.supported_output_types) == sorted(expected_output_types)
+
+
+@pytest.mark.parametrize(
+    "converter_class, converter_args",
+    [
+        (LLMGenericTextConverter, {"prompt_template": SeedPrompt(data_type="text", value="test template")}),
+        (MaliciousQuestionGeneratorConverter, {}),
+        (MathPromptConverter, {}),
+        (PersuasionConverter, {"persuasion_technique": "misrepresentation"}),
+        (TranslationConverter, {"language": "es"}),
+        (VariationConverter, {}),
+    ],
+)
+def test_llm_based_converters_validate_target_requirements(setup_memory, converter_class, converter_args):
+    """Ensure LLM-based converters validate their target via TARGET_REQUIREMENTS on construction."""
+    converter_args["converter_target"] = setup_memory
+    with patch("pyrit.prompt_target.common.target_requirements.TargetRequirements.validate") as mock_validate:
+        converter_class(**converter_args)
+    mock_validate.assert_called_once_with(target=setup_memory)
diff --git a/tests/unit/prompt_target/target/test_target_requirements.py b/tests/unit/prompt_target/target/test_target_requirements.py
index 002ccf086c..fdba9410cb 100644
--- a/tests/unit/prompt_target/target/test_target_requirements.py
+++ b/tests/unit/prompt_target/target/test_target_requirements.py
@@ -1,131 +1,120 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT license.
 
+from unittest.mock import MagicMock
+
 import pytest
 
+from pyrit.prompt_target import (
+    CHAT_CONSUMER_REQUIREMENTS,
+    CapabilityName,
+    TargetRequirements,
+)
 from pyrit.prompt_target.common.target_capabilities import (
     CapabilityHandlingPolicy,
-    CapabilityName,
     TargetCapabilities,
     UnsupportedCapabilityBehavior,
 )
 from pyrit.prompt_target.common.target_configuration import TargetConfiguration
-from pyrit.prompt_target.common.target_requirements import TargetRequirements
-
-
-@pytest.fixture
-def adapt_all_policy():
-    return CapabilityHandlingPolicy(
-        behaviors={
-            CapabilityName.SYSTEM_PROMPT: UnsupportedCapabilityBehavior.ADAPT,
-            CapabilityName.MULTI_TURN: UnsupportedCapabilityBehavior.ADAPT,
-            CapabilityName.JSON_SCHEMA: UnsupportedCapabilityBehavior.RAISE,
-            CapabilityName.JSON_OUTPUT: UnsupportedCapabilityBehavior.RAISE,
-            CapabilityName.MULTI_MESSAGE_PIECES: UnsupportedCapabilityBehavior.RAISE,
-            CapabilityName.EDITABLE_HISTORY: UnsupportedCapabilityBehavior.RAISE,
-        }
-    )
 
 
-# ---------------------------------------------------------------------------
-# Construction
-# ---------------------------------------------------------------------------
+def _make_target(*, configuration: TargetConfiguration) -> MagicMock:
+    target = MagicMock()
+    target.configuration = configuration
+    return target
 
 
-def test_init_default_has_empty_capabilities():
-    reqs = TargetRequirements()
-    assert reqs.required_capabilities == frozenset()
+def test_default_requirements_require_nothing():
+    assert TargetRequirements().required == frozenset()
 
 
-def test_init_with_capabilities():
+def test_construction_from_frozenset():
     reqs = TargetRequirements(
-        required_capabilities=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT})
+        required=frozenset({CapabilityName.MULTI_TURN, CapabilityName.JSON_OUTPUT}),
     )
-    assert CapabilityName.MULTI_TURN in reqs.required_capabilities
-    assert CapabilityName.SYSTEM_PROMPT in reqs.required_capabilities
+    assert reqs.required == {CapabilityName.MULTI_TURN, CapabilityName.JSON_OUTPUT}
 
 
-# ---------------------------------------------------------------------------
-# validate — all pass
-# ---------------------------------------------------------------------------
+def test_chat_consumer_requirements_shape():
+    assert CHAT_CONSUMER_REQUIREMENTS.required == {
+        CapabilityName.EDITABLE_HISTORY,
+        CapabilityName.MULTI_TURN,
+    }
 
 
-def test_validate_passes_when_target_supports_all_natively():
-    caps = TargetCapabilities(supports_multi_turn=True, supports_system_prompt=True)
-    config = TargetConfiguration(capabilities=caps)
-    reqs = TargetRequirements(
-        required_capabilities=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT})
-    )
-    reqs.validate(configuration=config)
+def test_requirements_are_frozen():
+    reqs = TargetRequirements(required=frozenset({CapabilityName.MULTI_TURN}))
+    with pytest.raises(Exception):
+        reqs.required = frozenset()  # type: ignore[misc]
 
 
-def test_validate_passes_when_policy_is_adapt(adapt_all_policy):
-    caps = TargetCapabilities(supports_multi_turn=False, supports_system_prompt=False)
-    config = TargetConfiguration(capabilities=caps, policy=adapt_all_policy)
-    reqs = TargetRequirements(
-        required_capabilities=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT})
+def test_validate_passes_on_native_support():
+    target = _make_target(
+        configuration=TargetConfiguration(
+            capabilities=TargetCapabilities(
+                supports_multi_turn=True,
+                supports_editable_history=True,
+            ),
+        ),
     )
-    reqs.validate(configuration=config)
-
-
-def test_validate_passes_with_empty_requirements():
-    caps = TargetCapabilities(supports_multi_turn=True, supports_system_prompt=True)
-    config = TargetConfiguration(capabilities=caps)
-    reqs = TargetRequirements()
-    reqs.validate(configuration=config)
-
 
-# ---------------------------------------------------------------------------
-# validate — failures
-# ---------------------------------------------------------------------------
-
-
-def test_validate_raises_when_capability_missing_and_no_policy():
-    # EDITABLE_HISTORY has no normalizer and no handling policy — validate raises.
-    caps = TargetCapabilities(supports_editable_history=False, supports_multi_turn=True, supports_system_prompt=True)
-    config = TargetConfiguration(capabilities=caps)
-    reqs = TargetRequirements(required_capabilities=frozenset({CapabilityName.EDITABLE_HISTORY}))
-    with pytest.raises(ValueError, match="supports_editable_history"):
-        reqs.validate(configuration=config)
-
-
-def test_validate_raises_when_capability_missing_and_policy_raise(adapt_all_policy):
-    # json_output is missing and the policy is RAISE — validate raises.
-    caps = TargetCapabilities(supports_multi_turn=False, supports_system_prompt=False, supports_json_output=False)
-    config = TargetConfiguration(capabilities=caps, policy=adapt_all_policy)
-    reqs = TargetRequirements(required_capabilities=frozenset({CapabilityName.JSON_OUTPUT}))
-    with pytest.raises(ValueError, match="supports_json_output"):
-        reqs.validate(configuration=config)
-
-
-def test_validate_collects_all_unsatisfied_capabilities(adapt_all_policy):
-    """When multiple capabilities are missing, validate reports all violations."""
-    caps = TargetCapabilities(
-        supports_multi_turn=False,
-        supports_system_prompt=False,
-        supports_json_output=False,
-        supports_editable_history=False,
+    CHAT_CONSUMER_REQUIREMENTS.validate(target=target)
+
+
+def test_validate_passes_when_policy_is_adapt():
+    # Note: EDITABLE_HISTORY is not adaptable, so this test uses a custom
+    # requirement over capabilities that the policy can adapt.
+    reqs = TargetRequirements(required=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT}))
+    target = _make_target(
+        configuration=TargetConfiguration(
+            capabilities=TargetCapabilities(
+                supports_multi_turn=False,
+                supports_system_prompt=False,
+            ),
+            policy=CapabilityHandlingPolicy(
+                behaviors={
+                    CapabilityName.MULTI_TURN: UnsupportedCapabilityBehavior.ADAPT,
+                    CapabilityName.SYSTEM_PROMPT: UnsupportedCapabilityBehavior.ADAPT,
+                },
+            ),
+        ),
     )
-    config = TargetConfiguration(capabilities=caps, policy=adapt_all_policy)
-    # json_output => RAISE, editable_history => no policy (raises)
-    reqs = TargetRequirements(
-        required_capabilities=frozenset({CapabilityName.JSON_OUTPUT, CapabilityName.EDITABLE_HISTORY})
-    )
-    with pytest.raises(ValueError, match="2 required capability") as exc_info:
-        reqs.validate(configuration=config)
-    assert "supports_json_output" in str(exc_info.value)
-    assert "supports_editable_history" in str(exc_info.value)
 
+    reqs.validate(target=target)
+
+
+def test_validate_raises_when_capability_neither_native_nor_adapt():
+    reqs = TargetRequirements(required=frozenset({CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT}))
+    target = _make_target(
+        configuration=TargetConfiguration(
+            capabilities=TargetCapabilities(
+                supports_multi_turn=True,
+                supports_system_prompt=False,
+            ),
+            policy=CapabilityHandlingPolicy(
+                behaviors={
+                    CapabilityName.MULTI_TURN: UnsupportedCapabilityBehavior.RAISE,
+                    CapabilityName.SYSTEM_PROMPT: UnsupportedCapabilityBehavior.RAISE,
+                },
+            ),
+        ),
+    )
 
-def test_validate_mixed_adapt_and_raise(adapt_all_policy):
-    """One capability adapts but another raises — validate should raise."""
-    caps = TargetCapabilities(supports_multi_turn=False, supports_system_prompt=False, supports_json_output=False)
-    config = TargetConfiguration(capabilities=caps, policy=adapt_all_policy)
-    # multi_turn and system_prompt => ADAPT (OK), json_output => RAISE (fail)
-    reqs = TargetRequirements(
-        required_capabilities=frozenset(
-            {CapabilityName.MULTI_TURN, CapabilityName.SYSTEM_PROMPT, CapabilityName.JSON_OUTPUT}
-        )
+    with pytest.raises(ValueError, match=CapabilityName.SYSTEM_PROMPT.value):
+        reqs.validate(target=target)
+
+
+def test_validate_empty_required_always_passes():
+    target = _make_target(
+        configuration=TargetConfiguration(
+            capabilities=TargetCapabilities(),
+            policy=CapabilityHandlingPolicy(
+                behaviors={
+                    CapabilityName.MULTI_TURN: UnsupportedCapabilityBehavior.RAISE,
+                    CapabilityName.SYSTEM_PROMPT: UnsupportedCapabilityBehavior.RAISE,
+                },
+            ),
+        ),
     )
-    with pytest.raises(ValueError, match="supports_json_output"):
-        reqs.validate(configuration=config)
+
+    TargetRequirements().validate(target=target)
diff --git a/tests/unit/scenario/test_psychosocial_harms.py b/tests/unit/scenario/test_psychosocial_harms.py
index 205d6ed3f1..4a207cc45b 100644
--- a/tests/unit/scenario/test_psychosocial_harms.py
+++ b/tests/unit/scenario/test_psychosocial_harms.py
@@ -323,6 +323,67 @@ async def test_no_target_duplication_async(
             assert scenario._objective_scorer is not None
 
 
+@pytest.mark.usefixtures(*FIXTURES)
+class TestPsychosocialTargetRequirements:
+    """Tests for Psychosocial TARGET_REQUIREMENTS declaration and enforcement."""
+
+    def test_target_requirements_declares_editable_history_natively(self):
+        """Psychosocial runs CrescendoAttack, so it must require EDITABLE_HISTORY natively."""
+        from pyrit.prompt_target.common.target_capabilities import CapabilityName
+
+        assert CapabilityName.EDITABLE_HISTORY in Psychosocial.TARGET_REQUIREMENTS.native_required
+
+    @pytest.mark.asyncio
+    async def test_initialize_async_invokes_target_requirements_validate(
+        self,
+        mock_objective_target,
+        mock_objective_scorer,
+        mock_resolved_seed_data,
+        mock_dataset_config,
+    ):
+        """initialize_async must delegate capability validation to TARGET_REQUIREMENTS.validate."""
+        with patch.object(Psychosocial, "_resolve_seed_groups", return_value=mock_resolved_seed_data):
+            scenario = Psychosocial(objective_scorer=mock_objective_scorer)
+            with patch("pyrit.prompt_target.common.target_requirements.TargetRequirements.validate") as mock_validate:
+                await scenario.initialize_async(
+                    objective_target=mock_objective_target,
+                    dataset_config=mock_dataset_config,
+                )
+
+            # Scorers / attacks also validate; ensure the scenario itself validated objective_target.
+            assert any(call.kwargs.get("target") is mock_objective_target for call in mock_validate.call_args_list), (
+                "Expected TARGET_REQUIREMENTS.validate to be called with objective_target"
+            )
+
+    @pytest.mark.asyncio
+    async def test_initialize_async_rejects_target_missing_editable_history(
+        self,
+        mock_objective_scorer,
+        mock_resolved_seed_data,
+        mock_dataset_config,
+    ):
+        """A target that does not natively support EDITABLE_HISTORY must be rejected."""
+        from pyrit.prompt_target import PromptTarget
+        from pyrit.prompt_target.common.target_capabilities import CapabilityName
+
+        non_chat_target = MagicMock(spec=PromptTarget)
+        non_chat_target.get_identifier.return_value = ComponentIdentifier(
+            class_name="NonChatTarget", class_module="test"
+        )
+        # Configuration reports no EDITABLE_HISTORY support
+        non_chat_target.configuration.includes.side_effect = (
+            lambda *, capability: capability != CapabilityName.EDITABLE_HISTORY
+        )
+
+        with patch.object(Psychosocial, "_resolve_seed_groups", return_value=mock_resolved_seed_data):
+            scenario = Psychosocial(objective_scorer=mock_objective_scorer)
+            with pytest.raises(ValueError, match="editable_history"):
+                await scenario.initialize_async(
+                    objective_target=non_chat_target,
+                    dataset_config=mock_dataset_config,
+                )
+
+
 @pytest.mark.usefixtures(*FIXTURES)
 class TestPsychosocialHarmsStrategy:
     """Tests for PsychosocialHarmsStrategy enum."""
diff --git a/tests/unit/scenario/test_scenario.py b/tests/unit/scenario/test_scenario.py
index 947cf6f645..89ebd9aaf0 100644
--- a/tests/unit/scenario/test_scenario.py
+++ b/tests/unit/scenario/test_scenario.py
@@ -292,6 +292,36 @@ async def test_initialize_async_uses_default_values(self, mock_objective_target)
         assert scenario._max_concurrency == 10
         assert scenario._memory_labels == {}
 
+    @pytest.mark.asyncio
+    async def test_initialize_async_validates_target_requirements(self, mock_objective_target):
+        """Test that initialize_async validates objective_target against TARGET_REQUIREMENTS."""
+        scenario = ConcreteScenario(name="Test Scenario", version=1)
+
+        with patch("pyrit.prompt_target.common.target_requirements.TargetRequirements.validate") as mock_validate:
+            await scenario.initialize_async(objective_target=mock_objective_target)
+
+        mock_validate.assert_called_once_with(target=mock_objective_target)
+
+    @pytest.mark.asyncio
+    async def test_initialize_async_propagates_target_requirements_error(self, mock_objective_target):
+        """Test that initialize_async surfaces errors from TARGET_REQUIREMENTS.validate."""
+        scenario = ConcreteScenario(name="Test Scenario", version=1)
+
+        with patch(
+            "pyrit.prompt_target.common.target_requirements.TargetRequirements.validate",
+            side_effect=ValueError("Target must natively support 'editable_history'"),
+        ):
+            with pytest.raises(ValueError, match="editable_history"):
+                await scenario.initialize_async(objective_target=mock_objective_target)
+
+    def test_scenario_base_target_requirements_is_empty(self):
+        """Base Scenario declares an empty TargetRequirements so it accepts any target by default."""
+        from pyrit.prompt_target.common.target_requirements import TargetRequirements
+
+        assert isinstance(Scenario.TARGET_REQUIREMENTS, TargetRequirements)
+        assert Scenario.TARGET_REQUIREMENTS.required == frozenset()
+        assert Scenario.TARGET_REQUIREMENTS.native_required == frozenset()
+
 
 @pytest.mark.usefixtures("patch_central_database")
 class TestScenarioExecution: