FIX Honor score feedback and handle zero-vector similarity

doc/scanner/2_pyrit_shell.md

@@ -42,8 +42,8 @@ Once starting the shell, you will see the list of commands you have access to. S
 | `list-targets` | List all available targets from the registry |
 | `list-converters` | List all registered converter instances |
 | `run <scenario> [options]` | Run a scenario with optional parameters |
-| `scenario-history` | List all previous scenario runs in this session |
-| `print-scenario [N]` | Print detailed results for scenario run(s) |
+| `scenario-history [N]` | List recent scenario runs and their IDs |
+| `scenario-results <id> [options]` | Inspect overview or attack-level results for a scenario run |
 | `help [command]` | Show help for a command |
 | `clear` | Clear the screen |
 | `exit` (or `quit`, `q`) | Exit the shell |
@@ -118,14 +118,11 @@ Track and review all scenario runs in your session:
 # Show all runs from this session
 pyrit> scenario-history
 
-# Print details of the most recent run
-pyrit> print-scenario
+# Print an overview for a run using its scenario result ID
+pyrit> scenario-results 2a1f91a0-28bf-4f48-bd54-8f12451cf7af
 
-# Print details of a specific run (by number from history)
-pyrit> print-scenario 1
-
-# Print all runs
-pyrit> print-scenario
+# Inspect attack-level results for that run
+pyrit> scenario-results 2a1f91a0-28bf-4f48-bd54-8f12451cf7af --view attacks
 ```
 
 Example output:
@@ -135,14 +132,12 @@ pyrit> scenario-history
 
 Scenario Run History:
 ================================================================================
-1) foundry.red_team_agent --initializers target --techniques base64
-2) garak.encoding --initializers target --techniques rot13
-3) foundry.red_team_agent --initializers target -t jailbreak
+  1) [COMPLETED] foundry.red_team_agent (id: 2a1f91a0-28bf-4f48-bd54-8f12451cf7af) — 12 attacks, 33.3% success — 2026-08-16T01:15:00+00:00
+  2) [COMPLETED] garak.encoding (id: 9b27f101-1440-4454-9609-b307230f36a9) — 8 attacks, 25.0% success — 2026-08-16T01:10:00+00:00
+  3) [COMPLETED] foundry.red_team_agent (id: 40624391-c9d3-492d-b3e4-2c15202ade62) — 12 attacks, 16.7% success — 2026-08-16T01:05:00+00:00
 ================================================================================
 
 Total runs: 3
-
-Use 'print-scenario <number>' to view detailed results for a specific run.
 ```
 
 ## Interactive Exploration
@@ -161,8 +156,8 @@ pyrit> run garak.encoding --techniques morse_code
 
 # Review and compare
 pyrit> scenario-history
-pyrit> print-scenario 1
-pyrit> print-scenario 2
+pyrit> scenario-results 2a1f91a0-28bf-4f48-bd54-8f12451cf7af
+pyrit> scenario-results 9b27f101-1440-4454-9609-b307230f36a9
 ```
 
 ## Shell Benefits
@@ -190,10 +185,10 @@ pyrit> print-scenario 2
    pyrit> scenario-history
    ```
 
-4. **Print specific results** to compare outcomes:
+4. **Inspect specific results** to compare outcomes:
    ```bash
-   pyrit> print-scenario 1  # baseline run
-   pyrit> print-scenario 3  # modified run
+   pyrit> scenario-results 2a1f91a0-28bf-4f48-bd54-8f12451cf7af  # baseline run
+   pyrit> scenario-results 40624391-c9d3-492d-b3e4-2c15202ade62  # modified run
    ```
 
 ## Exit the Shell

pyrit/analytics/conversation_analytics.py

@@ -106,5 +106,7 @@ def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:
 
     dot_product = np.dot(a, b)
     norms = np.linalg.norm(a) * np.linalg.norm(b)
+    if norms == 0:
+        return 0.0
 
     return float(dot_product / norms)

pyrit/executor/attack/multi_turn/crescendo.py

@@ -565,20 +565,21 @@ def _build_adversarial_prompt(
                     f"{refused_text}\n",
                 ]
             )
-        elif context.last_score and context.last_response:
+        elif context.last_response:
             # Get the last assistant response directly from the response object
             last_message_value = context.last_response.get_value()
 
             if last_message_value:
-                score_value = normalize_score_to_float(context.last_score)
-                prompt_parts.extend(
-                    [
-                        f"\nThe target responded to the last question with: {last_message_value}",
-                        "\n--------------------------------",
-                        f"\nThis response received a score of: {score_value:.2f} on a scale of 0.0 to 1.0",
-                        f"Rationale: {context.last_score.score_rationale}\n",
-                    ]
-                )
+                prompt_parts.append(f"\nThe target responded to the last question with: {last_message_value}")
+                if self._use_score_as_feedback and context.last_score:
+                    score_value = normalize_score_to_float(context.last_score)
+                    prompt_parts.extend(
+                        [
+                            "\n--------------------------------",
+                            f"\nThis response received a score of: {score_value:.2f} on a scale of 0.0 to 1.0",
+                            f"Rationale: {context.last_score.score_rationale}\n",
+                        ]
+                    )
 
         return " ".join(prompt_parts)
 

pyrit/executor/attack/multi_turn/tree_of_attacks.py

@@ -338,6 +338,7 @@ def __init__(
         attack_id: ComponentIdentifier,
         attack_strategy_name: str,
         modality_router: _ModalityFeedbackRouter,
+        use_score_as_feedback: bool = True,
         memory_labels: dict[str, str] | None = None,
         parent_id: str | None = None,
         prompt_normalizer: PromptNormalizer | None = None,
@@ -364,6 +365,8 @@ def __init__(
                 whether prior media should travel back to the adversarial chat or forward to
                 the objective target, and fills adversarial-placeholder pieces in seed
                 messages. Typically shared across all nodes of the same attack.
+            use_score_as_feedback (bool): Whether subsequent adversarial prompts include
+                the objective score. Defaults to True.
             memory_labels (dict[str, str] | None): Labels for memory storage.
             parent_id (str | None): ID of the parent node, if this is a child node
             prompt_normalizer (PromptNormalizer | None): Normalizer for handling prompts and responses.
@@ -386,6 +389,7 @@ def __init__(
         self._attack_strategy_name = attack_strategy_name
         self._memory_labels = memory_labels or {}
         self._modality_router = modality_router
+        self._use_score_as_feedback = use_score_as_feedback
 
         # Initialize utilities
         self._memory = CentralMemory.get_memory_instance()
@@ -876,6 +880,7 @@ def duplicate(self) -> _TreeOfAttacksNode:
             attack_id=self._attack_id,
             attack_strategy_name=self._attack_strategy_name,
             modality_router=self._modality_router,
+            use_score_as_feedback=self._use_score_as_feedback,
             memory_labels=self._memory_labels,
             desired_response_prefix=self._desired_response_prefix,
             parent_id=self.node_id,
@@ -1170,7 +1175,9 @@ async def _generate_subsequent_turn_prompt_async(self, objective: str) -> str:
         logger.debug(f"Node {self.node_id}: Using response {target_response_piece.id} for next prompt")
 
         # Get score for the response
-        score = await self._get_response_score_async(str(target_response_piece.id))
+        score = (
+            await self._get_response_score_async(str(target_response_piece.id)) if self._use_score_as_feedback else ""
+        )
 
         # Generate prompt using template
         return self._adversarial_chat_prompt_template.render_template_value(
@@ -2090,6 +2097,7 @@ def _create_attack_node(
             attack_id=self.get_identifier(),
             attack_strategy_name=self.__class__.__name__,
             modality_router=self._modality_router,
+            use_score_as_feedback=self._attack_scoring_config.use_score_as_feedback,
             memory_labels=context.memory_labels,
             desired_response_prefix=self._configuration.desired_response_prefix,
             parent_id=parent_id,

tests/unit/analytics/test_conversation_analytics.py

@@ -4,9 +4,10 @@
 from collections.abc import Sequence
 from unittest.mock import MagicMock
 
+import numpy as np
 import pytest
 
-from pyrit.analytics.conversation_analytics import ConversationAnalytics
+from pyrit.analytics.conversation_analytics import ConversationAnalytics, cosine_similarity
 from pyrit.memory.memory_interface import MemoryInterface
 from pyrit.memory.memory_models import EmbeddingDataEntry
 from pyrit.models import MessagePiece, flatten_to_message_pieces
@@ -70,3 +71,15 @@ def test_get_similar_chat_messages_by_embedding(mock_memory_interface, sample_me
     assert len(similar_messages) == 1
     assert similar_messages[0].score >= 0.99
     assert similar_messages[0].metric == "cosine_similarity"
+
+
+@pytest.mark.parametrize(
+    "a,b",
+    [
+        (np.array([0.0, 0.0]), np.array([1.0, 2.0])),
+        (np.array([1.0, 2.0]), np.array([0.0, 0.0])),
+        (np.array([0.0, 0.0]), np.array([0.0, 0.0])),
+    ],
+)
+def test_cosine_similarity_zero_vector_returns_zero(a: np.ndarray, b: np.ndarray) -> None:
+    assert cosine_similarity(a, b) == 0.0

tests/unit/executor/attack/multi_turn/test_crescendo.py

@@ -923,6 +923,29 @@ async def test_build_adversarial_prompt_with_objective_score(
         assert "0.30" in result  # Score value
         assert failure_objective_score.score_rationale in result
 
+    def test_build_adversarial_prompt_without_score_feedback(
+        self,
+        mock_objective_target: MagicMock,
+        mock_adversarial_chat: MagicMock,
+        basic_context: CrescendoAttackContext,
+        sample_response: Message,
+        failure_objective_score: Score,
+    ):
+        """The response remains available when objective-score feedback is disabled."""
+        attack = CrescendoAttack(
+            objective_target=mock_objective_target,
+            attack_adversarial_config=AttackAdversarialConfig(target=mock_adversarial_chat),
+            attack_scoring_config=AttackScoringConfig(use_score_as_feedback=False),
+        )
+        basic_context.last_response = sample_response
+        basic_context.last_score = failure_objective_score
+
+        result = attack._build_adversarial_prompt(context=basic_context, refused_text="")
+
+        assert "Test response" in result
+        assert "received a score of" not in result
+        assert failure_objective_score.score_rationale not in result
+
     async def test_generate_next_prompt_raises_when_adversarial_chat_returns_no_response(
         self,
         mock_objective_target: MagicMock,

tests/unit/executor/attack/multi_turn/test_tree_of_attacks.py

@@ -1581,6 +1581,29 @@ def test_node_initialization(self, node_components):
         assert node.auxiliary_scores == {}
         assert node.error_message is None
 
+    async def test_subsequent_prompt_omits_score_when_feedback_disabled(self, node_components):
+        """A disabled score-feedback setting preserves response context without exposing the score."""
+        node = _TreeOfAttacksNode(**node_components, use_score_as_feedback=False)
+        response = MagicMock()
+        response.get_piece.return_value = MessagePiece(
+            role="assistant",
+            original_value="target response",
+            converted_value="target response",
+            conversation_id=node.objective_target_conversation_id,
+        )
+
+        with (
+            patch.object(node._memory, "get_conversation_messages", return_value=[response]),
+            patch.object(node, "_get_response_score_async", new_callable=AsyncMock) as get_score,
+        ):
+            result = await node._generate_subsequent_turn_prompt_async("test objective")
+
+        assert result == "rendered template"
+        get_score.assert_not_awaited()
+        render_kwargs = node_components["adversarial_chat_prompt_template"].render_template_value.call_args.kwargs
+        assert render_kwargs["target_response"] == "target response"
+        assert render_kwargs["score"] == ""
+
     def test_node_duplicate_creates_child(self, node_components):
         """Test that duplicate() creates a proper child node."""
         parent_node = _TreeOfAttacksNode(**node_components)