docs: make Chinese README the default

2026-07-13 11:12:47 +00:00
parent 9b4c40f58c
commit 2b91a42d89
1 changed files with 74 additions and 76 deletions
@@ -1,3 +1,9 @@
+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/GreyDGL/PentestGPT) · [上游 README](https://github.com/GreyDGL/PentestGPT/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
 <!-- Improved compatibility of back to top link: See: https://github.com/othneildrew/Best-README-Template/pull/73 -->
 <a name="readme-top"></a>

@@ -16,19 +22,19 @@
 <h3 align="center">PentestGPT</h3>

  <p align="center">
-    AI-Powered Autonomous Penetration Testing Agent
+    AI 驱动的自主渗透测试智能体
    <br />
-    <strong>Published at USENIX Security 2024</strong>
+    <strong>发表于 USENIX Security 2024</strong>
    <br />
    <br />
-    <a href="https://pentestgpt.com"><strong>Official Website: pentestgpt.com »</strong></a>
+    <a href="https://pentestgpt.com"><strong>官方网站：pentestgpt.com »</strong></a>
    <br />
    <br />
-    <a href="https://www.usenix.org/conference/usenixsecurity24/presentation/deng">Research Paper</a>
+    <a href="https://www.usenix.org/conference/usenixsecurity24/presentation/deng">研究论文</a>
    ·
-    <a href="https://github.com/GreyDGL/PentestGPT/issues">Report Bug</a>
+    <a href="https://github.com/GreyDGL/PentestGPT/issues">报告 Bug</a>
    ·
-    <a href="https://github.com/GreyDGL/PentestGPT/issues">Request Feature</a>
+    <a href="https://github.com/GreyDGL/PentestGPT/issues">请求功能</a>
  </p>
 </div>

@@ -37,51 +43,49 @@

 ---

-## Demo
+## 演示

-### Installation
+### 安装
 [![Installation Demo](https://asciinema.org/a/761661.svg)](https://asciinema.org/a/761661)

-[Watch on YouTube](https://www.youtube.com/watch?v=RUNmoXqBwVg)
+[在 YouTube 观看](https://www.youtube.com/watch?v=RUNmoXqBwVg)

-### PentestGPT in Action
+### PentestGPT 实战
 [![PentestGPT Demo](https://asciinema.org/a/761663.svg)](https://asciinema.org/a/761663)

-[Watch on YouTube](https://www.youtube.com/watch?v=cWi3Yb7RmZA)
+[在 YouTube 观看](https://www.youtube.com/watch?v=cWi3Yb7RmZA)

 ---

-## What's New in v1.0 (Agentic Upgrade)
+## v1.0 新特性（Agentic 升级）

- **Iteration Loop** - The agent runs continuously, maintains a context file with progress, and restarts with prior context when hitting limits. Loop terminates on flag capture or max iterations.
- **Autonomous Agent** - Agentic pipeline for intelligent, autonomous penetration testing
- **Session Persistence** - Save and resume penetration testing sessions
+- **迭代循环（Iteration Loop）** - 智能体持续运行，维护记录进度的上下文文件，并在触及限制时携带先前上下文重启。循环在捕获 flag 或达到最大迭代次数时终止。
+- **自主智能体（Autonomous Agent）** - 用于智能、自主渗透测试的智能体流水线
+- **会话持久化（Session Persistence）** - 保存并恢复渗透测试会话

-> **Multi-model support** is available today in the interactive **modernized legacy** mode
-> (`pentestgpt-legacy`) — OpenAI, Anthropic, Google Gemini, DeepSeek, xAI, Qwen, Moonshot, and
-> local Ollama. See [Interactive Multi-LLM Mode](#interactive-multi-llm-mode-modernized-legacy).
+> 交互式**现代化遗留（modernized legacy）**模式现已支持**多模型**（`pentestgpt-legacy`）—— OpenAI、Anthropic、Google Gemini、DeepSeek、xAI、Qwen、Moonshot 以及本地 Ollama。参见[交互式多 LLM 模式](#interactive-multi-llm-mode-modernized-legacy)。

 ---

-## Features
+## 功能特性

- **AI-Powered Challenge Solver** - Leverages LLM advanced reasoning to perform penetration testing and CTFs
- **Live Walkthrough** - Tracks steps in real-time as the agent works through challenges
- **Multi-Category Support** - Web, Crypto, Reversing, Forensics, PWN, Privilege Escalation
- **Real-Time Feedback** - Watch the AI work with live activity updates
- **Extensible Architecture** - Clean, modular design ready for future enhancements
+- **AI 驱动的挑战求解器** - 利用 LLM 的高级推理能力执行渗透测试与 CTF
+- **实时演练（Live Walkthrough）** - 在智能体攻克挑战时实时跟踪步骤
+- **多类别支持** - Web、Crypto、Reversing、Forensics、PWN、权限提升（Privilege Escalation）
+- **实时反馈** - 通过实时活动更新观察 AI 的工作过程
+- **可扩展架构** - 简洁、模块化的设计，便于未来增强

 ---

-## Quick Start
+## 快速开始

-### Prerequisites
+### 前置条件

 - **Python 3.12+**
- **[uv](https://docs.astral.sh/uv/)** - Python package manager
- **Claude Code CLI** (`claude`) - installed and authenticated. See [Claude Code docs](https://docs.anthropic.com/en/docs/claude-code)
+- **[uv](https://docs.astral.sh/uv/)** - Python 包管理器
+- **Claude Code CLI** (`claude`) - 已安装并完成认证。参见 [Claude Code 文档](https://docs.anthropic.com/en/docs/claude-code)

-### Installation
+### 安装

 ```bash
 git clone https://github.com/GreyDGL/PentestGPT.git
@@ -89,18 +93,18 @@ cd PentestGPT
 make install    # runs uv sync
 ```

-### Commands Reference
+### 命令参考

 | Command | Description |
 |---------|-------------|
-| `make install` | Install dependencies |
-| `make test` | Run all tests |
-| `make check` | Run lint + typecheck |
-| `make build` | Build distributable package |
+| `make install` | 安装依赖 |
+| `make test` | 运行全部测试 |
+| `make check` | 运行 lint + typecheck |
+| `make build` | 构建可分发包 |

 ---

-## Usage
+## 用法

 ```bash
 # Run against a target
@@ -113,29 +117,24 @@ pentestgpt --target 10.10.11.50 --instruction "WordPress site, focus on plugin v
 pentestgpt --target 10.10.11.234 --max-iterations 5
 ```

-The agent runs in an **iteration loop**: it works autonomously, maintains a context file with progress, and restarts with prior context when hitting limits. The loop terminates on flag capture or max iterations (default: 10).
+智能体在**迭代循环**中运行：它自主工作，维护记录进度的上下文文件，并在触及限制时携带先前上下文重启。循环在捕获 flag 或达到最大迭代次数（默认：10）时终止。

 ---

-## Interactive Multi-LLM Mode (modernized legacy)
+## 交互式多 LLM 模式（现代化遗留）

-The classic, human-in-the-loop PentestGPT from the USENIX 2024 paper is preserved and
-modernized as `pentestgpt-legacy`. It runs three cooperating LLM sessions —
-**reasoning / generation / parsing** — that maintain a **Pentesting Task Tree (PTT)** while you
-drive the session interactively (`next`, `more`, `todo`, `discuss`). Unlike the autonomous agent
-(Claude-only), this mode talks **natively** to many providers via their official SDKs.
+USENIX 2024 论文中的经典人机协同 PentestGPT 得以保留，并现代化为 `pentestgpt-legacy`。它运行三个协作的 LLM 会话——**推理 / 生成 / 解析**——在由你交互式驱动会话的同时（`next`、`more`、`todo`、`discuss`）维护**渗透测试任务树（Pentesting Task Tree，PTT）**。与自主智能体（仅 Claude）不同，此模式通过各提供商的官方 SDK **原生**对接多家提供商。

-### Configure providers
+### 配置提供商

-Set an API key for any provider you want to use (in your environment or `.env` — see
-`.env.example`). Only the providers you configure are enabled.
+为要使用的任意提供商设置 API 密钥（在环境变量中或 `.env` 中——参见 `.env.example`）。仅启用已配置的提供商。

 ```bash
 OPENAI_API_KEY=...        ANTHROPIC_API_KEY=...     GEMINI_API_KEY=...   # or GOOGLE_API_KEY
 DEEPSEEK_API_KEY=...      GROK_API_KEY=...          QWEN_API_KEY=...     KIMI_API_KEY=...
 ```

-### Run
+### 运行

 ```bash
 # Auto-pick the best available models for each session
@@ -154,10 +153,9 @@ pentestgpt-legacy --list-models
 pentestgpt-legacy --smoke-test
 ```

-### Supported models (web-verified June 2026)
+### 支持的模型（2026 年 6 月经网页核实）

-`pentestgpt-legacy --list-models` always renders the live registry. Re-run `--smoke-test`
-after model IDs change. Current snapshot:
+`pentestgpt-legacy --list-models` 始终渲染实时注册表。模型 ID 变更后请重新运行 `--smoke-test`。当前快照：

 | Provider | Current models | Legacy (kept) | Env key |
 |----------|----------------|---------------|---------|
@@ -166,25 +164,25 @@ after model IDs change. Current snapshot:
 | **Google Gemini** | `gemini-3.1-pro`, `gemini-3.5-flash`, `gemini-3-pro`, `gemini-3.1-flash-lite` | `gemini-2.5-pro`, `gemini-2.5-flash` | `GEMINI_API_KEY` / `GOOGLE_API_KEY` |
 | **DeepSeek** | `deepseek-v4-flash`, `deepseek-v4-pro` | `deepseek-chat`, `deepseek-reasoner` | `DEEPSEEK_API_KEY` |
 | **xAI Grok** | `grok-4.3` | — | `GROK_API_KEY` / `XAI_API_KEY` |
-| **Alibaba Qwen** | `qwen3.7-max`, `qwen3.5-flash` | `qwen3-max` | `QWEN_API_KEY` / `DASHSCOPE_API_KEY` |
-| **Moonshot Kimi** | `kimi-k2.6` | — | `KIMI_API_KEY` (`.cn` default; set `MOONSHOT_BASE_URL` for `.ai`) |
+| **Alibaba Qwen** | `qwen3.7-max`, `qwen3.5-flash`, `qwen3-max` | `QWEN_API_KEY` / `DASHSCOPE_API_KEY` |
+| **Moonshot Kimi** | `kimi-k2.6` | — | `KIMI_API_KEY` (`.cn` 默认；设置 `MOONSHOT_BASE_URL` 以使用 `.ai`) |
 | **Local (Ollama)** | `ollama:<model>` (e.g. `ollama:qwen3`) | — | none (`OLLAMA_BASE_URL`) |

-> The registry lives in `pentestgpt_legacy/llm/registry.py` (the single source of truth).
-> Adding a model is one `ModelSpec` entry; OpenAI-compatible providers reuse one connector.
+> 注册表位于 `pentestgpt_legacy/llm/registry.py`（唯一真实来源）。
+> 添加模型只需一条 `ModelSpec` 条目；OpenAI 兼容提供商复用同一连接器。

 ---

-## Telemetry
+## 遥测（Telemetry）

-PentestGPT collects anonymous usage data to help improve the tool. This data is sent to our [Langfuse](https://langfuse.com) project and includes:
- Session metadata (target type, duration, completion status)
- Tool execution patterns (which tools are used, not the actual commands)
- Flag detection events (that a flag was found, not the flag content)
+PentestGPT 收集匿名使用数据以帮助改进工具。这些数据会发送至我们的 [Langfuse](https://langfuse.com) 项目，包括：
+- 会话元数据（目标类型、持续时间、完成状态）
+- 工具执行模式（使用了哪些工具，而非实际命令）
+- Flag 检测事件（检测到 flag，而非 flag 内容）

-**No sensitive data is collected** - command outputs, credentials, or actual flag values are never transmitted.
+**不收集敏感数据** - 命令输出、凭据或实际 flag 值绝不会被传输。

-### Opting Out
+### 选择退出

 ```bash
 # Via command line flag
@@ -196,22 +194,22 @@ export LANGFUSE_ENABLED=false

 ---

-## Benchmarks
+## 基准测试

-PentestGPT achieved an **86.5% success rate** (90/104 benchmarks) on the XBOW validation suite:
+PentestGPT 在 XBOW 验证套件上达到 **86.5% 成功率**（104 项基准中的 90 项）：

- **Cost**: Average $1.11, Median $0.42 per successful benchmark
- **Time**: Average 6.1 minutes, Median 3.3 minutes per successful benchmark
- **Success rates by difficulty**:
-  - Level 1: 91.1%
-  - Level 2: 74.5%
-  - Level 3: 62.5%
+- **成本**：每项成功基准平均 $1.11，中位数 $0.42
+- **时间**：每项成功基准平均 6.1 分钟，中位数 3.3 分钟
+- **按难度划分的成功率**：
+  - Level 1：91.1%
+  - Level 2：74.5%
+  - Level 3：62.5%

 ---

-## Citation
+## 引用

-If you use PentestGPT in your research, please cite our paper:
+若你在研究中使用 PentestGPT，请引用我们的论文：

 ```bibtex
@inproceedings{299699,
@@ -230,19 +228,19 @@ If you use PentestGPT in your research, please cite our paper:

 ---

-## License
+## 许可证

-Distributed under the MIT License. See `LICENSE.md` for more information.
+根据 MIT License 发布。更多信息请参见 `LICENSE.md`。

-**Disclaimer**: This tool is for educational purposes and authorized security testing only. The authors do not condone any illegal use. Use at your own risk.
+**免责声明**：本工具仅供教育用途和经授权的安全测试（authorized security testing）使用。作者不赞成任何非法用途。使用风险自负。

 ---

-## Acknowledgments
+## 致谢

- Research supported by [Quantstamp](https://www.quantstamp.com/) and [NTU Singapore](https://www.ntu.edu.sg/)
+- 研究得到 [Quantstamp](https://www.quantstamp.com/) 与 [NTU Singapore](https://www.ntu.edu.sg/) 的支持

-<p align="right">(<a href="#readme-top">back to top</a>)</p>
+<p align="right">(<a href="#readme-top">返回顶部</a>)</p>

 <!-- MARKDOWN LINKS & IMAGES -->
 [contributors-shield]: https://img.shields.io/github/contributors/GreyDGL/PentestGPT.svg?style=for-the-badge