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Base Attacks

BaseAttack 

BaseAttack(
    task_suite: TaskSuite,
    target_pipeline: BasePipelineElement,
)

Bases: ABC

Base class for attacks.

Parameters:

  • task_suite (TaskSuite) –

    The task suite with the user and injection tasks being used for the benchmark.

  • target_pipeline (BasePipelineElement) –

    The target pipeline that is attacked.

Source code in src/agentdojo/attacks/base_attacks.py 
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def __init__(self, task_suite: TaskSuite, target_pipeline: BasePipelineElement) -> None:
    self.task_suite = task_suite
    self.target_pipeline = target_pipeline
    injection_defaults = task_suite.get_injection_vector_defaults()
    self.canary_injections = {inj: f"<CANARY---{inj}--->" for inj in injection_defaults}

is_dos_attack class-attribute instance-attribute 

is_dos_attack: bool = False

Whether the attack is a DOS attack. If True, then the benchmarking will be done with only one injection task.

name instance-attribute 

name: str

The name of the attack.

get_injection_candidates cached 

get_injection_candidates(
    user_task: BaseUserTask,
) -> list[str]

"Given a user task ID, it returns the list of keys of the injection placeholders that are seen by the LLM when executing the task correctly.

Source code in src/agentdojo/attacks/base_attacks.py 
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@lru_cache
def get_injection_candidates(self, user_task: BaseUserTask) -> list[str]:
    """ "Given a user task ID, it returns the list of keys of the injection placeholders
    that are seen by the LLM when executing the task correctly."""
    gt_pipeline = GroundTruthPipeline(user_task)
    runtime = FunctionsRuntime(self.task_suite.tools)
    environment = self.task_suite.load_and_inject_default_environment(self.canary_injections)
    _, _, _, responses, _ = gt_pipeline.query(user_task.PROMPT, runtime, environment)

    injection_candidates = []
    for inj in self.canary_injections:
        found = False
        for response in responses:
            if response["content"] is not None and self.canary_injections[inj] in response["content"]:
                found = True
        if found:
            injection_candidates.append(inj)
    if len(injection_candidates) == 0:
        raise ValueError(f"{user_task.ID} is not injectable.")
    return injection_candidates

attack 

attack(
    user_task: BaseUserTask,
    injection_task: BaseInjectionTask,
) -> dict[str, str]

Given a user task and an injection task, it returns a dictionary containing the injection placeholders that are seen by the agent when execuring the task correctly, and the corresponsing injections.

Parameters:

  • user_task (BaseUserTask) –

    The user task.

  • injection_task (BaseInjectionTask) –

    The injection task. It contains the GOAL attribute, that should be used by the attack to instruct the model to execute the injection task.

Source code in src/agentdojo/attacks/base_attacks.py 
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def attack(self, user_task: BaseUserTask, injection_task: BaseInjectionTask) -> dict[str, str]:
    """Given a user task and an injection task, it returns a dictionary containing the
    injection placeholders that are seen by the agent when execuring the task correctly, and
    the corresponsing injections.

    Args:
        user_task: The user task.
        injection_task: The injection task. It contains the [`GOAL`][agentdojo.base_tasks.BaseInjectionTask.GOAL]
            attribute, that should be used by the attack to instruct the model to execute the injection task.

    """

    ...

DEFAULT_USER_NAME module-attribute 

DEFAULT_USER_NAME = 'the user'

Default name of the victim user.

DEFAULT_MODEL_NAME module-attribute 

DEFAULT_MODEL_NAME = 'the AI language model'

Default name of the victim model.

FixedJailbreakAttack 

FixedJailbreakAttack(
    jailbreak: str,
    task_suite: TaskSuite,
    target_pipeline: BasePipelineElement,
)

Bases: BaseAttack

Attack which uses a fixed template (e.g., f"ignore previous instructions, do {injection_task.GOAL} instead"). The attack method will substitute {goal}, {user}, {model}, and {task} in the jailbreak string with the given values. Subclasses can override summarize_task to provide a human-readable summary of the task.

Source code in src/agentdojo/attacks/base_attacks.py 
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def __init__(self, jailbreak: str, task_suite: TaskSuite, target_pipeline: BasePipelineElement) -> None:
    super().__init__(task_suite, target_pipeline)
    self.jailbreak = jailbreak

user_name class-attribute instance-attribute 

user_name: str = DEFAULT_USER_NAME

The name of the user. This will be substituted in the jailbreak string to the {user} placeholder if present in the string.

model_name class-attribute instance-attribute 

model_name: str = DEFAULT_MODEL_NAME

The name of the model. This will be substituted in the jailbreak string to the {model} placeholder if present in the string.