greydgl--pentestgpt
b9869307d0
* fix: 🐛 minor typo and build process * feat: 🎸 [WIP] Pentest mode * feat: 🎸 code abstraction * feat: modernize legacy PentestGPT with native multi-LLM support (#469) Rebuild the classic USENIX-2024 interactive PentestGPT (reasoning / generation / parsing sessions + Pentesting Task Tree + REPL) as a standalone `pentestgpt_legacy` package on a native per-provider LLM layer that supports the latest 2026 models. - llm/: BaseProvider + OpenAI-compatible / Anthropic / Gemini connectors, a web-verified model registry (OpenAI, Anthropic, Gemini, DeepSeek, xAI, Qwen, Moonshot, local Ollama), a factory, and an LLMClient bridging async providers to the core's synchronous send_new_message/send_message session API. - CLI `pentestgpt-legacy`: --list-models and --smoke-test (live per-model round-trip matrix), plus --reasoning-model / --parsing-model / --base-url. - Tests: 25 unit tests (mocked, no network). Live smoke test verified 22/22 models with a configured key respond. Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * fix(backend): address review on ClaudeCodeBackend subprocess handling - _build_env: pop ANTHROPIC_API_KEY instead of setting it to "", so an empty value can't shadow the CLI's own auth fallback (e.g. subscription login). - _kill_process: reap the force-killed process with os.waitpid(.., WNOHANG) instead of calling the proc.wait() coroutine without awaiting it (removes the "coroutine was never awaited" warning). - query/_drain_stderr: drain subprocess stderr in a background task so its pipe buffer can't fill and deadlock the child. Also reformats backend.py, fixing the failing Lint (ruff format) check. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * fix(docker-test): assert uv instead of Poetry in container health check The project migrated from Poetry to uv (the Dockerfile installs uv to /home/pentester/.local/bin, which is on PATH), so test_poetry_installed failed with exit 127. Replace it with test_uv_installed checking `uv --version`. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
126 行
4.3 KiB
Python
126 行
4.3 KiB
Python
#!/usr/bin/env python
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"""
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url: https://github.com/prompt-toolkit/python-prompt-toolkit/tree/master/examples/prompts/auto-completion
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Demonstration of a custom completer class and the possibility of styling
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completions independently by passing formatted text objects to the "display"
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and "display_meta" arguments of "Completion".
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"""
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from typing import ClassVar
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from prompt_toolkit.completion import Completer, Completion
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from prompt_toolkit.formatted_text import HTML
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from prompt_toolkit.shortcuts import prompt
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class localTaskCompleter(Completer):
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tasks: ClassVar[list[str]] = [
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"discuss", # discuss with pentestGPT on the local task
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"brainstorm", # let pentestGPT brainstorm on the local task
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"help", # show the help page (for this local task)
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"google", # search on Google
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"continue", # quit the local task (for this local task)
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]
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task_meta: ClassVar[dict[str, HTML]] = {
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"discuss": HTML("Discuss with <b>PentestGPT</b> about this local task."),
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"brainstorm": HTML(
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"Let <b>PentestGPT</b> brainstorm on the local task for all the possible solutions."
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),
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"help": HTML("Show the help page for this local task."),
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"google": HTML("Search on Google."),
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"continue": HTML("Quit the local task and continue the previous testing."),
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}
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task_details = """
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Below are the available tasks:
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- discuss: Discuss with PentestGPT about this local task.
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- brainstorm: Let PentestGPT brainstorm on the local task for all the possible solutions.
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- help: Show the help page for this local task.
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- google: Search on Google.
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- quit: Quit the local task and continue the testing."""
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def get_completions(self, document, complete_event):
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word = document.get_word_before_cursor()
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for task in self.tasks:
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if task.startswith(word):
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yield Completion(
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task,
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start_position=-len(word),
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display=task,
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display_meta=self.task_meta.get(task),
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)
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class mainTaskCompleter(Completer):
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tasks: ClassVar[list[str]] = [
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"next",
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"more",
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"todo",
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"discuss",
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"google",
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"help",
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"quit",
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]
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task_meta: ClassVar[dict[str, HTML]] = {
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"next": HTML("Go to the next step."),
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"more": HTML("Explain the task with more details."),
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"todo": HTML("Ask <b>PentestGPT</b> for todos."),
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"discuss": HTML("Discuss with <b>PentestGPT</b>."),
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"google": HTML("Search on Google."),
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"help": HTML("Show the help page."),
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"quit": HTML("End the current session."),
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}
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task_details = """
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Below are the available tasks:
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- next: Continue to the next step by inputting the test results.
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- more: Explain the previous given task with more details.
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- todo: Ask PentestGPT for the task list and what to do next.
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- discuss: Discuss with PentestGPT. You can ask for help, discuss the task, or give any feedbacks.
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- google: Search your question on Google. The results are automatically parsed by Google.
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- help: Show this help page.
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- quit: End the current session."""
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def get_completions(self, document, complete_event):
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word = document.get_word_before_cursor()
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for task in self.tasks:
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if task.startswith(word):
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yield Completion(
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task,
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start_position=-len(word),
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display=task,
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display_meta=self.task_meta.get(task),
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)
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def main_task_entry(text="> "):
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"""
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Entry point for the task prompt. Auto-complete
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"""
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task_completer = mainTaskCompleter()
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while True:
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result = prompt(text, completer=task_completer)
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if result not in task_completer.tasks:
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print("Invalid task, try again.")
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else:
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return result
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def local_task_entry(text="> "):
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"""
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Entry point for the task prompt. Auto-complete
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"""
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task_completer = localTaskCompleter()
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while True:
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result = prompt(text, completer=task_completer)
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if result not in task_completer.tasks:
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print("Invalid task, try again.")
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else:
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return result
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if __name__ == "__main__":
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main_task_entry()
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