mirror of
https://github.com/trustedsec/hate_crack.git
synced 2026-07-30 15:40:31 -07:00
feat: add PassGPT model fine-tuning and training menu integration
Add ability to fine-tune PassGPT models on custom password wordlists. Models save locally to ~/.hate_crack/passgpt/ with no data uploaded to HuggingFace (push_to_hub=False, HF_HUB_DISABLE_TELEMETRY=1). The PassGPT menu now shows available models (default + local fine-tuned) and a training option. Adds datasets to [ml] deps and passgptTrainingList config key. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Justin Bollinger
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
f0b512a079
commit
c3c4d9da60
+185
-18
@@ -1,3 +1,4 @@
|
||||
import os
|
||||
import sys
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
@@ -78,8 +79,99 @@ class TestHcatPassGPT:
|
||||
assert "512" in gen_cmd
|
||||
|
||||
|
||||
class TestHcatPassGPTTrain:
|
||||
def test_builds_correct_subprocess_command(self, main_module, tmp_path):
|
||||
training_file = tmp_path / "wordlist.txt"
|
||||
training_file.write_text("password123\nabc456\n")
|
||||
|
||||
with patch.object(
|
||||
main_module, "passgptModel", "javirandor/passgpt-10characters"
|
||||
), patch("hate_crack.main.subprocess.Popen") as mock_popen:
|
||||
mock_proc = MagicMock()
|
||||
mock_proc.returncode = 0
|
||||
mock_proc.wait.return_value = None
|
||||
mock_popen.return_value = mock_proc
|
||||
|
||||
with patch.object(
|
||||
main_module,
|
||||
"_passgpt_model_dir",
|
||||
return_value=str(tmp_path / "models"),
|
||||
):
|
||||
result = main_module.hcatPassGPTTrain(str(training_file))
|
||||
|
||||
assert result is not None
|
||||
assert mock_popen.call_count == 1
|
||||
cmd = mock_popen.call_args[0][0]
|
||||
assert cmd[0] == sys.executable
|
||||
assert "-m" in cmd
|
||||
assert "hate_crack.passgpt_train" in cmd
|
||||
assert "--training-file" in cmd
|
||||
assert str(training_file) in cmd
|
||||
assert "--base-model" in cmd
|
||||
assert "javirandor/passgpt-10characters" in cmd
|
||||
assert "--output-dir" in cmd
|
||||
|
||||
def test_missing_training_file(self, main_module, capsys):
|
||||
result = main_module.hcatPassGPTTrain("/nonexistent/wordlist.txt")
|
||||
assert result is None
|
||||
captured = capsys.readouterr()
|
||||
assert "Training file not found" in captured.out
|
||||
|
||||
def test_custom_base_model(self, main_module, tmp_path):
|
||||
training_file = tmp_path / "wordlist.txt"
|
||||
training_file.write_text("test\n")
|
||||
|
||||
with patch("hate_crack.main.subprocess.Popen") as mock_popen:
|
||||
mock_proc = MagicMock()
|
||||
mock_proc.returncode = 0
|
||||
mock_proc.wait.return_value = None
|
||||
mock_popen.return_value = mock_proc
|
||||
|
||||
with patch.object(
|
||||
main_module,
|
||||
"_passgpt_model_dir",
|
||||
return_value=str(tmp_path / "models"),
|
||||
):
|
||||
main_module.hcatPassGPTTrain(
|
||||
str(training_file), base_model="custom/base-model"
|
||||
)
|
||||
|
||||
cmd = mock_popen.call_args[0][0]
|
||||
assert "custom/base-model" in cmd
|
||||
|
||||
def test_training_failure_returns_none(self, main_module, tmp_path):
|
||||
training_file = tmp_path / "wordlist.txt"
|
||||
training_file.write_text("test\n")
|
||||
|
||||
with patch.object(
|
||||
main_module, "passgptModel", "javirandor/passgpt-10characters"
|
||||
), patch("hate_crack.main.subprocess.Popen") as mock_popen:
|
||||
mock_proc = MagicMock()
|
||||
mock_proc.returncode = 1
|
||||
mock_proc.wait.return_value = None
|
||||
mock_popen.return_value = mock_proc
|
||||
|
||||
with patch.object(
|
||||
main_module,
|
||||
"_passgpt_model_dir",
|
||||
return_value=str(tmp_path / "models"),
|
||||
):
|
||||
result = main_module.hcatPassGPTTrain(str(training_file))
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestPassGPTModelDir:
|
||||
def test_creates_directory(self, main_module, tmp_path):
|
||||
target = str(tmp_path / "passgpt_models")
|
||||
with patch("hate_crack.main.os.path.expanduser", return_value=str(tmp_path)):
|
||||
result = main_module._passgpt_model_dir()
|
||||
assert os.path.isdir(result)
|
||||
assert result.endswith("passgpt")
|
||||
|
||||
|
||||
class TestPassGPTAttackHandler:
|
||||
def test_prompts_and_calls_hcatPassGPT(self):
|
||||
def _make_ctx(self, model_dir=None):
|
||||
ctx = MagicMock()
|
||||
ctx.HAS_ML_DEPS = True
|
||||
ctx.passgptMaxCandidates = 1000000
|
||||
@@ -87,8 +179,21 @@ class TestPassGPTAttackHandler:
|
||||
ctx.passgptBatchSize = 1024
|
||||
ctx.hcatHashType = "1000"
|
||||
ctx.hcatHashFile = "/tmp/hashes.txt"
|
||||
ctx.hcatWordlists = "/tmp/wordlists"
|
||||
if model_dir is None:
|
||||
ctx._passgpt_model_dir.return_value = "/nonexistent/empty"
|
||||
else:
|
||||
ctx._passgpt_model_dir.return_value = model_dir
|
||||
return ctx
|
||||
|
||||
with patch("builtins.input", return_value=""):
|
||||
def test_select_default_model_and_generate(self):
|
||||
ctx = self._make_ctx()
|
||||
|
||||
# "1" selects default model, "" accepts default max candidates
|
||||
inputs = iter(["1", ""])
|
||||
with patch("builtins.input", side_effect=inputs), patch(
|
||||
"hate_crack.attacks.os.path.isdir", return_value=False
|
||||
):
|
||||
from hate_crack.attacks import passgpt_attack
|
||||
|
||||
passgpt_attack(ctx)
|
||||
@@ -101,28 +206,70 @@ class TestPassGPTAttackHandler:
|
||||
batch_size=1024,
|
||||
)
|
||||
|
||||
def test_custom_values(self):
|
||||
ctx = MagicMock()
|
||||
ctx.HAS_ML_DEPS = True
|
||||
ctx.passgptMaxCandidates = 1000000
|
||||
ctx.passgptModel = "javirandor/passgpt-10characters"
|
||||
ctx.passgptBatchSize = 1024
|
||||
ctx.hcatHashType = "1000"
|
||||
ctx.hcatHashFile = "/tmp/hashes.txt"
|
||||
def test_select_local_model(self, tmp_path):
|
||||
# Create a fake local model directory
|
||||
model_dir = tmp_path / "passgpt"
|
||||
local_model = model_dir / "my_model"
|
||||
local_model.mkdir(parents=True)
|
||||
(local_model / "config.json").write_text("{}")
|
||||
|
||||
inputs = iter(["500000", "custom/model"])
|
||||
with patch("builtins.input", side_effect=inputs):
|
||||
ctx = self._make_ctx(model_dir=str(model_dir))
|
||||
|
||||
# "2" selects the local model, "" accepts default max candidates
|
||||
inputs = iter(["2", ""])
|
||||
with patch("builtins.input", side_effect=inputs), patch(
|
||||
"hate_crack.attacks.os.path.isdir", return_value=True
|
||||
), patch("hate_crack.attacks.os.listdir", return_value=["my_model"]), patch(
|
||||
"hate_crack.attacks.os.path.isfile", return_value=True
|
||||
), patch(
|
||||
"hate_crack.attacks.os.path.isdir",
|
||||
side_effect=lambda p: True,
|
||||
):
|
||||
from hate_crack.attacks import passgpt_attack
|
||||
|
||||
passgpt_attack(ctx)
|
||||
|
||||
ctx.hcatPassGPT.assert_called_once_with(
|
||||
"1000",
|
||||
"/tmp/hashes.txt",
|
||||
500000,
|
||||
model_name="custom/model",
|
||||
batch_size=1024,
|
||||
ctx.hcatPassGPT.assert_called_once()
|
||||
call_kwargs = ctx.hcatPassGPT.call_args
|
||||
# The model_name should be the local path
|
||||
assert call_kwargs[1]["model_name"] == str(local_model)
|
||||
|
||||
def test_train_new_model(self):
|
||||
ctx = self._make_ctx()
|
||||
ctx.select_file_with_autocomplete.return_value = "/tmp/wordlist.txt"
|
||||
ctx.hcatPassGPTTrain.return_value = "/home/user/.hate_crack/passgpt/wordlist"
|
||||
|
||||
# "T" for train, "" for default base model, "" for default max candidates
|
||||
inputs = iter(["T", "", ""])
|
||||
with patch("builtins.input", side_effect=inputs), patch(
|
||||
"hate_crack.attacks.os.path.isdir", return_value=False
|
||||
):
|
||||
from hate_crack.attacks import passgpt_attack
|
||||
|
||||
passgpt_attack(ctx)
|
||||
|
||||
ctx.hcatPassGPTTrain.assert_called_once_with(
|
||||
"/tmp/wordlist.txt", "javirandor/passgpt-10characters"
|
||||
)
|
||||
ctx.hcatPassGPT.assert_called_once()
|
||||
call_kwargs = ctx.hcatPassGPT.call_args
|
||||
assert call_kwargs[1]["model_name"] == "/home/user/.hate_crack/passgpt/wordlist"
|
||||
|
||||
def test_train_failure_aborts(self):
|
||||
ctx = self._make_ctx()
|
||||
ctx.select_file_with_autocomplete.return_value = "/tmp/wordlist.txt"
|
||||
ctx.hcatPassGPTTrain.return_value = None
|
||||
|
||||
inputs = iter(["T", ""])
|
||||
with patch("builtins.input", side_effect=inputs), patch(
|
||||
"hate_crack.attacks.os.path.isdir", return_value=False
|
||||
):
|
||||
from hate_crack.attacks import passgpt_attack
|
||||
|
||||
passgpt_attack(ctx)
|
||||
|
||||
ctx.hcatPassGPTTrain.assert_called_once()
|
||||
ctx.hcatPassGPT.assert_not_called()
|
||||
|
||||
def test_ml_deps_missing(self, capsys):
|
||||
ctx = MagicMock()
|
||||
@@ -136,3 +283,23 @@ class TestPassGPTAttackHandler:
|
||||
assert "ML dependencies" in captured.out
|
||||
assert "uv pip install" in captured.out
|
||||
ctx.hcatPassGPT.assert_not_called()
|
||||
|
||||
def test_custom_max_candidates(self):
|
||||
ctx = self._make_ctx()
|
||||
|
||||
# "1" selects default model, "500000" for custom max candidates
|
||||
inputs = iter(["1", "500000"])
|
||||
with patch("builtins.input", side_effect=inputs), patch(
|
||||
"hate_crack.attacks.os.path.isdir", return_value=False
|
||||
):
|
||||
from hate_crack.attacks import passgpt_attack
|
||||
|
||||
passgpt_attack(ctx)
|
||||
|
||||
ctx.hcatPassGPT.assert_called_once_with(
|
||||
"1000",
|
||||
"/tmp/hashes.txt",
|
||||
500000,
|
||||
model_name="javirandor/passgpt-10characters",
|
||||
batch_size=1024,
|
||||
)
|
||||
|
||||
Reference in New Issue
Block a user