feat: add PassGPT attack (#17) - GPT-2 based ML password generator

Add PassGPT as attack mode 17, using a GPT-2 model trained on leaked
password datasets to generate candidate passwords. The generator pipes
candidates to hashcat via stdin, matching the existing OMEN pipe pattern.

- Add standalone generator module (python -m hate_crack.passgpt_generate)
- Add [ml] optional dependency group (torch, transformers)
- Add config keys: passgptModel, passgptMaxCandidates, passgptBatchSize
- Wire up menu entries in main.py, attacks.py, and hate_crack.py
- Auto-detect GPU (CUDA/MPS) with CPU fallback
- Add unit tests for pipe construction, handler, and ML deps check

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

tests/test_passgpt_attack.py

@@ -0,0 +1,138 @@
+import sys
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+
+@pytest.fixture
+def main_module(hc_module):
+    """Return the underlying hate_crack.main module for direct patching."""
+    return hc_module._main
+
+
+class TestHcatPassGPT:
+    def test_builds_correct_pipe_commands(self, main_module):
+        with patch.object(main_module, "hcatBin", "hashcat"), patch.object(
+            main_module, "hcatTuning", "--force"
+        ), patch.object(main_module, "hcatPotfilePath", ""), patch.object(
+            main_module, "hcatHashFile", "/tmp/hashes.txt", create=True
+        ), patch.object(
+            main_module, "passgptModel", "javirandor/passgpt-10characters"
+        ), patch.object(main_module, "passgptBatchSize", 1024), patch(
+            "hate_crack.main.subprocess.Popen"
+        ) as mock_popen:
+            mock_gen_proc = MagicMock()
+            mock_gen_proc.stdout = MagicMock()
+            mock_hashcat_proc = MagicMock()
+            mock_hashcat_proc.wait.return_value = None
+            mock_gen_proc.wait.return_value = None
+            mock_popen.side_effect = [mock_gen_proc, mock_hashcat_proc]
+
+            main_module.hcatPassGPT("1000", "/tmp/hashes.txt", 500000)
+
+            assert mock_popen.call_count == 2
+            # First call: passgpt generator
+            gen_cmd = mock_popen.call_args_list[0][0][0]
+            assert gen_cmd[0] == sys.executable
+            assert "-m" in gen_cmd
+            assert "hate_crack.passgpt_generate" in gen_cmd
+            assert "--num" in gen_cmd
+            assert "500000" in gen_cmd
+            assert "--model" in gen_cmd
+            assert "javirandor/passgpt-10characters" in gen_cmd
+            assert "--batch-size" in gen_cmd
+            assert "1024" in gen_cmd
+            # Second call: hashcat
+            hashcat_cmd = mock_popen.call_args_list[1][0][0]
+            assert hashcat_cmd[0] == "hashcat"
+            assert "1000" in hashcat_cmd
+            assert "/tmp/hashes.txt" in hashcat_cmd
+
+    def test_custom_model_and_batch_size(self, main_module):
+        with patch.object(main_module, "hcatBin", "hashcat"), patch.object(
+            main_module, "hcatTuning", "--force"
+        ), patch.object(main_module, "hcatPotfilePath", ""), patch.object(
+            main_module, "hcatHashFile", "/tmp/hashes.txt", create=True
+        ), patch.object(
+            main_module, "passgptModel", "javirandor/passgpt-10characters"
+        ), patch.object(main_module, "passgptBatchSize", 1024), patch(
+            "hate_crack.main.subprocess.Popen"
+        ) as mock_popen:
+            mock_gen_proc = MagicMock()
+            mock_gen_proc.stdout = MagicMock()
+            mock_hashcat_proc = MagicMock()
+            mock_hashcat_proc.wait.return_value = None
+            mock_gen_proc.wait.return_value = None
+            mock_popen.side_effect = [mock_gen_proc, mock_hashcat_proc]
+
+            main_module.hcatPassGPT(
+                "1000",
+                "/tmp/hashes.txt",
+                100000,
+                model_name="custom/model",
+                batch_size=512,
+            )
+
+            gen_cmd = mock_popen.call_args_list[0][0][0]
+            assert "custom/model" in gen_cmd
+            assert "512" in gen_cmd
+
+
+class TestPassGPTAttackHandler:
+    def test_prompts_and_calls_hcatPassGPT(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"
+
+        with patch("builtins.input", return_value=""):
+            from hate_crack.attacks import passgpt_attack
+
+            passgpt_attack(ctx)
+
+        ctx.hcatPassGPT.assert_called_once_with(
+            "1000",
+            "/tmp/hashes.txt",
+            1000000,
+            model_name="javirandor/passgpt-10characters",
+            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"
+
+        inputs = iter(["500000", "custom/model"])
+        with patch("builtins.input", side_effect=inputs):
+            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,
+        )
+
+    def test_ml_deps_missing(self, capsys):
+        ctx = MagicMock()
+        ctx.HAS_ML_DEPS = False
+
+        from hate_crack.attacks import passgpt_attack
+
+        passgpt_attack(ctx)
+
+        captured = capsys.readouterr()
+        assert "ML dependencies" in captured.out
+        assert "uv pip install" in captured.out
+        ctx.hcatPassGPT.assert_not_called()