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2 changes: 2 additions & 0 deletions pyrit/datasets/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@
fetch_jbb_behaviors_by_harm_category,
fetch_jbb_behaviors_by_jbb_category,
)
from pyrit.datasets.fetch_jailbreakv_28k_dataset import fetch_jailbreakv_28k_dataset


__all__ = [
Expand Down Expand Up @@ -64,4 +65,5 @@
"fetch_jbb_behaviors_dataset",
"fetch_jbb_behaviors_by_harm_category",
"fetch_jbb_behaviors_by_jbb_category",
"fetch_jailbreakv_28k_dataset",
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mind keeping these alphabetical? I realize we missed out on that before but no better time to fix it than now 🙂

]
200 changes: 200 additions & 0 deletions pyrit/datasets/fetch_jailbreakv_28k_dataset.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,200 @@
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

import logging
import uuid
from typing import Dict, List, Literal, Optional

from datasets import load_dataset
from huggingface_hub import HfApi, hf_hub_download

from pyrit.models import SeedPrompt, SeedPromptDataset

logger = logging.getLogger(__name__)

HarmLiteral = Literal[
"Unethical Behavior",
"Economic Harm",
"Hate Speech",
"Government Decision",
"Physical Harm",
"Fraud",
"Political Sensitivity",
"Malware",
"Illegal Activity",
"Bias",
"Violence",
"Animal Abuse",
"Tailored Unlicensed Advice",
"Privacy Violation",
"Health Consultation",
"Child Abuse Content",
]


def fetch_jailbreakv_28k_dataset(
*,
data_home: Optional[str] = None,
split: Literal["JailBreakV_28K", "mini_JailBreakV_28K"] = "mini_JailBreakV_28K",
text_field: Literal["jailbreak_query", "redteam_query"] = "redteam_query",
harm_categories: Optional[List[HarmLiteral]] = None,
) -> SeedPromptDataset:
"""
Fetch examples from the JailBreakV 28k Dataset with optional filtering and create a SeedPromptDataset.
Args:
data_home: Directory used as cache_dir in call to HF to store cached data. Defaults to None.
split (str): The split of the dataset to fetch. Defaults to "mini_JailBreakV_28K".
Options are "JailBreakV_28K" and "mini_JailBreakV_28K".
text_field (str): The field to use as the prompt text. Defaults to "redteam_query".
Options are "jailbreak_query" and "redteam_query".
harm_categories: List of harm categories to filter the examples.
Defaults to None, which means all categories are included.
Otherwise, only prompts with at least one matching category are included.
Returns:
SeedPromptDataset: A SeedPromptDataset containing the filtered examples.
Note:
For more information and access to the original dataset and related materials, visit:
https://huggingface.co/datasets/JailbreakV-28K/JailBreakV-28k/blob/main/README.md \n
Related paper: https://arxiv.org/abs/2404.03027 \n
The dataset license: mit
authors: Weidi Luo, Siyuan Ma, Xiaogeng Liu, Chaowei Xiao, Xiaoyu Guo
Comment on lines +62 to +63
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Suggested change
The dataset license: mit
authors: Weidi Luo, Siyuan Ma, Xiaogeng Liu, Chaowei Xiao, Xiaoyu Guo
The dataset license: MIT
Authors: Weidi Luo, Siyuan Ma, Xiaogeng Liu, Chaowei Xiao, Xiaoyu Guo

Warning:
Due to the nature of these prompts, it may be advisable to consult your relevant legal
department before testing them with LLMs to ensure compliance and reduce potential risks.
"""

source = "JailbreakV-28K/JailBreakV-28k"

try:
logger.info(f"Loading JailBreakV-28k dataset from {source}")

# Normalize the harm categories to match pyrit harm category conventions
harm_categories_normalized = (
None if not harm_categories else [_normalize_policy(policy) for policy in harm_categories]
)

# Load the dataset from HuggingFace
data = load_dataset(source, "JailBreakV_28K", cache_dir=data_home)

dataset_split = data[split]

per_call_cache: Dict[str, str] = {}

seed_prompts = []

# Define common metadata that will be used across all seed prompts
common_metadata = {
"dataset_name": "JailbreakV-28K",
"authors": ["Weidi Luo", "Siyuan Ma", "Xiaogeng Liu", "Chaowei Xiao", "Xiaoyu Guo"],
"description": (
"Benchmark for Assessing the Robustness of "
"Multimodal Large Language Models against Jailbreak Attacks. "
),
"groups": ["The Ohio State University", "Peking University", "University of Wisconsin-Madison"],
"source": "https://huggingface.co/datasets/JailbreakV-28K/JailBreakV-28k",
"name": "JailBreakV-28K",
}

# tracker for items in the dataset where image_path does not match an image in the repo
missing_images = 0

for item in dataset_split:
policy = _normalize_policy(item.get("policy", ""))
# Skip if user requested policy filter and items policy does not match
if not (harm_categories_normalized) or policy in harm_categories_normalized:
image_rel_path = item.get("image_path", "")
image_abs_path = ""
if image_rel_path:
image_abs_path = _resolve_image_path(
image_rel_path, repo_id=source, data_home=data_home, call_cache=per_call_cache
)
if image_abs_path:
group_id = uuid.uuid4()
text_seed_prompt = SeedPrompt(
value=item.get(text_field, ""),
harm_categories=[policy],
prompt_group_id=group_id,
data_type="text",
**common_metadata, # type: ignore[arg-type]
)
image_seed_prompt = SeedPrompt(
value=image_abs_path,
harm_categories=[policy],
prompt_group_id=group_id,
data_type="image_path",
**common_metadata, # type: ignore[arg-type]
)
seed_prompts.append(text_seed_prompt)
seed_prompts.append(image_seed_prompt)
else:
missing_images += 1
Comment on lines +115 to +134
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Suggested change
if image_abs_path:
group_id = uuid.uuid4()
text_seed_prompt = SeedPrompt(
value=item.get(text_field, ""),
harm_categories=[policy],
prompt_group_id=group_id,
data_type="text",
**common_metadata, # type: ignore[arg-type]
)
image_seed_prompt = SeedPrompt(
value=image_abs_path,
harm_categories=[policy],
prompt_group_id=group_id,
data_type="image_path",
**common_metadata, # type: ignore[arg-type]
)
seed_prompts.append(text_seed_prompt)
seed_prompts.append(image_seed_prompt)
else:
missing_images += 1
if not image_abs_path:
missing_images += 1
continue
group_id = uuid.uuid4()
text_seed_prompt = SeedPrompt(
value=item.get(text_field, ""),
harm_categories=[policy],
prompt_group_id=group_id,
data_type="text",
**common_metadata, # type: ignore[arg-type]
)
image_seed_prompt = SeedPrompt(
value=image_abs_path,
harm_categories=[policy],
prompt_group_id=group_id,
data_type="image_path",
**common_metadata, # type: ignore[arg-type]
)
seed_prompts.append(text_seed_prompt)
seed_prompts.append(image_seed_prompt)

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i.e., move the second case to first and remove indentation

except Exception as e:
logger.error(f"Failed to load JailBreakV-28K dataset: {str(e)}")
raise Exception(f"Error loading JailBreakV-28K dataset: {str(e)}")
if missing_images:
logger.warning(f"Failed to resolve {missing_images} image paths in JailBreakV-28K dataset")
if not seed_prompts:
raise ValueError(
"JailBreakV-28K fetch produced 0 prompts. "
"Likely caused by all items returned after filtering having invalid image paths."
)
Comment on lines +140 to +144
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how many are currently missing? Should we have a cutoff (>0) at which point it should error out?

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Currently, the vast majority are missing, making this dataset not as useful as previously expected. I have started a discussion on HF about adding the full images folder which currently is only contained a zip file held in a separate cloud drive.

seed_prompt_dataset = SeedPromptDataset(prompts=seed_prompts)
return seed_prompt_dataset


def _normalize_policy(policy: str) -> str:
"""Create a machine-friendly variant alongside the human-readable policy."""
return policy.strip().lower().replace(" ", "_").replace("-", "_")


def _resolve_image_path(
rel_path: str,
repo_id: str,
data_home: Optional[str],
call_cache: Dict[str, str] = {},
) -> str:
"""
Resolve a repo-relative image path to a local absolute path using hf_hub_download.
Uses a cache (module-level by default) to avoid re-downloading the same file.
Args:
rel_path: path relative to the dataset repository root (e.g., "images/0001.png").
repo_id: HF dataset repo id, e.g., "JailbreakV-28K/JailBreakV-28k".
data_home: optional cache directory.
cache: optional dict to use instead of the module-level cache.
Returns:
Absolute local path if resolved, else None (and caches the miss).
"""
if not rel_path:
return ""

# check if image has already been cached
if rel_path in call_cache:
return call_cache[rel_path]
path_root = "JailBreakV_28K"
hf_path = f"{path_root}/{rel_path}"
try:
# first check if the path exists using HFApi()
repo_file_list = HfApi().list_repo_files(repo_id=repo_id, repo_type="dataset")
if hf_path not in repo_file_list:
logger.debug(f"File {hf_path} not found in dataset {repo_id}")
call_cache[rel_path] = ""
return ""
# download the image
abs_path = hf_hub_download(
repo_id=repo_id,
repo_type="dataset",
filename=hf_path,
cache_dir=data_home,
)
call_cache[rel_path] = abs_path
return abs_path
except Exception as e:
logger.error(f"Failed to download image {rel_path}: {str(e)}")
call_cache[rel_path] = ""
return ""
27 changes: 27 additions & 0 deletions tests/integration/datasets/test_fetch_datasets.py
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
fetch_equitymedqa_dataset_unique_values,
fetch_forbidden_questions_dataset,
fetch_harmbench_dataset,
fetch_jailbreakv_28k_dataset,
fetch_jbb_behaviors_by_harm_category,
fetch_jbb_behaviors_by_jbb_category,
fetch_jbb_behaviors_dataset,
Expand Down Expand Up @@ -46,6 +47,7 @@
(fetch_equitymedqa_dataset_unique_values, True),
(fetch_forbidden_questions_dataset, True),
(fetch_harmbench_dataset, True),
(fetch_jailbreakv_28k_dataset, True),
(fetch_jbb_behaviors_dataset, True),
(fetch_librAI_do_not_answer_dataset, True),
(fetch_llm_latent_adversarial_training_harmful_dataset, True),
Expand Down Expand Up @@ -94,3 +96,28 @@ def test_fetch_jbb_behaviors_by_jbb_category():
assert len(hate_prompts.prompts) > 0
except Exception as e:
pytest.skip(f"Integration test skipped due to: {e}")


def test_fetch_jailbreakv_28k_dataset():
"""Integration test for fetching jailbreakv_28k dataset with real data."""
try:
jailbreakv_28k = fetch_jailbreakv_28k_dataset()
assert isinstance(jailbreakv_28k, SeedPromptDataset)
assert len(jailbreakv_28k.prompts) > 0
assert sum(p.data_type == "text" for p in jailbreakv_28k.prompts) == len(jailbreakv_28k.prompts) / 2
assert sum(p.data_type == "image_path" for p in jailbreakv_28k.prompts) == len(jailbreakv_28k.prompts) / 2
except Exception as e:
pytest.skip(f"Integration test skipped due to: {e}")
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skip? why not fail?

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Good point, I am not sure why I was simply going off of what I thought was the convention based on previously merged custom integration tests (jbb dataset integration)



def test_fetch_jailbreakv_28k_dataset_by_harm_category():
"""Integration test for filtering jailbreakv_28k git by harm category with real data."""
try:
# Filter for a category whose items have a valid image_path
jailbreakv_28k = fetch_jailbreakv_28k_dataset(harm_categories=["Economic Harm"])
assert isinstance(jailbreakv_28k, SeedPromptDataset)
assert len(jailbreakv_28k.prompts) > 0
assert sum(p.data_type == "text" for p in jailbreakv_28k.prompts) == len(jailbreakv_28k.prompts) / 2
assert sum(p.data_type == "image_path" for p in jailbreakv_28k.prompts) == len(jailbreakv_28k.prompts) / 2
except Exception as e:
pytest.skip(f"Integration test skipped due to: {e}")
88 changes: 88 additions & 0 deletions tests/unit/datasets/test_fetch_jailbreakv_28k.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,88 @@
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

from contextlib import nullcontext
from unittest.mock import patch

import pytest

from pyrit.datasets.fetch_jailbreakv_28k_dataset import fetch_jailbreakv_28k_dataset
from pyrit.models import SeedPrompt, SeedPromptDataset


class TestFetchJailbreakv28kDataset:
"""Test suite for the fetch_jailbreakv_28k_dataset function."""

@pytest.mark.parametrize("text_field", [None, "jailbreak_query"])
@pytest.mark.parametrize(
"harm_categories",
[None, ["Economic Harm"], ["Government Decision"]],
)
@patch("pyrit.datasets.fetch_jailbreakv_28k_dataset._resolve_image_path")
@patch("pyrit.datasets.fetch_jailbreakv_28k_dataset.load_dataset")
def test_fetch_jailbreakv_28k_dataset_success(
self, mock_load_dataset, mock_resolve_image_path, text_field, harm_categories
):
# Mock dataset response
mock_dataset = {
"mini_JailBreakV_28K": [
{
"redteam_query": "test query 1",
"jailbreak_query": "jailbreak: test query 1",
"policy": "Economic Harm",
"image_path": "mock_folder/valid",
},
{
"redteam_query": "test query 2",
"jailbreak_query": "jailbreak: test query 2",
"policy": "Government Decision",
"image_path": "invalid",
},
{
"redteam_query": "test query 3",
"jailbreak_query": "jailbreak: test query 3",
"policy": "Fraud",
"image_path": "mock_folder/valid",
},
]
}
mock_load_dataset.return_value = mock_dataset

def fake_resolve_image_path(rel_path: str, **kwargs) -> str:
return "" if rel_path == "invalid" else f"mock_path/{rel_path}"

mock_resolve_image_path.side_effect = fake_resolve_image_path

# Call the function
# Select context: expect error only for this filter
expect_error = harm_categories == ["Government Decision"]
ctx = pytest.raises(ValueError) if expect_error else nullcontext()

# Single call
with ctx:
result = fetch_jailbreakv_28k_dataset(text_field=text_field, harm_categories=harm_categories)
if expect_error:
return
# Assertions

assert isinstance(result, SeedPromptDataset)
if harm_categories is None:
assert len(result.prompts) == 4
assert sum(p.data_type == "text" for p in result.prompts) == 2
assert sum(p.data_type == "image_path" for p in result.prompts) == 2
elif harm_categories == ["Economic Harm"]:
assert len(result.prompts) == 2
assert sum(p.data_type == "text" for p in result.prompts) == 1
assert sum(p.data_type == "image_path" for p in result.prompts) == 1
print(result.prompts)
assert result.prompts[0].harm_categories == ["economic_harm"]
assert all(isinstance(prompt, SeedPrompt) for prompt in result.prompts)
print(result.prompts)
if text_field == "jailbreak_query":
for prompt in result.prompts:
if prompt.data_type == "text":
assert "jailbreak" in prompt.value
else:
for prompt in result.prompts:
if prompt.data_type == "text":
assert "jailbreak" not in prompt.value