pyrit.executor.attack.CrescendoAttackResult#

class CrescendoAttackResult(conversation_id: str, objective: str, attack_identifier: Optional[AttackIdentifier] = None, last_response: Optional[MessagePiece] = None, last_score: Optional[Score] = None, executed_turns: int = 0, execution_time_ms: int = 0, outcome: AttackOutcome = AttackOutcome.UNDETERMINED, outcome_reason: Optional[str] = None, related_conversations: set[ConversationReference] = <factory>, metadata: Dict[str, Any] = <factory>)[source]#

Bases: AttackResult

Result of the Crescendo attack strategy execution.

__init__(conversation_id: str, objective: str, attack_identifier: Optional[AttackIdentifier] = None, last_response: Optional[MessagePiece] = None, last_score: Optional[Score] = None, executed_turns: int = 0, execution_time_ms: int = 0, outcome: AttackOutcome = AttackOutcome.UNDETERMINED, outcome_reason: Optional[str] = None, related_conversations: set[ConversationReference] = <factory>, metadata: Dict[str, Any] = <factory>) None#

Methods

__init__(conversation_id, objective[, ...])

duplicate()

Create a deep copy of the result.

get_conversations_by_type(conversation_type)

Return all related conversations of the requested type.

Attributes

attack_identifier

backtrack_count

Get the number of backtracks performed during the attack.

executed_turns

execution_time_ms

last_response

last_score

outcome

outcome_reason

conversation_id

objective

related_conversations

metadata

property backtrack_count: int#

Get the number of backtracks performed during the attack.

Returns:

The number of backtracks.

Return type:

int

conversation_id: str#
metadata: Dict[str, Any]#
objective: str#
related_conversations: set[ConversationReference]#