PentestGPT/README.md
Grey_D 8d3a863db0 feat: 🎸 separate prompts from script
Now prompts under `prompts`. Also some minor bugs are fixed.

 Closes: #5
2023-04-10 13:38:33 +08:00

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# PentestGPT
v0.1, 09/04/2023
## Introduction
**PentestGPT** is a penetration testing tool empowered by **ChatGPT**. It is designed to automate the penetration testing process. It is built on top of ChatGPT and operate in an interactive mode to guide penetration testers in both overall progress and specific operations.
## Contribute
The project is still in its early stage. Feel free to raise any issues when using the tool.
## Installation
1. Install `requirements.txt` with `pip install -r requirements.txt`
2. Install `chatgpt-wrapper` if you're non-plus members: `pip install git+https://github.com/mmabrouk/chatgpt-wrapper`. More details at: https://github.com/mmabrouk/chatgpt-wrapper. Note that the support for non-plus members are not optimized.
3. Configure the keys in `config`. You may follow a sample by `cp config/chatgpt_config_sample.py. config/chatgpt_config.py`.
## Examples
1. To start, run `python3 main.py`.
2. The tool works similar to *msfconsole*. Follow the guidance to perform penetration testing.
## Development
- [ ] Add chunk processing
- [ ] Add prompt optimization
- [ ] Test scenarios beyond web testing
## Design Documentation
The current design is mainly for web penetration testing
### General Design
PentestGPT provides a unified terminal input handler, and backed by three main components:
- A test generation module which generates the exact penetration testing commands or operations for the users to execute.
- A test reasoning module which conducts the reasoning of the test, guiding the penetration testers on what to do next.
- A parsing module which parses the output of the penetration tools and the contents on the webUI.
### Function Design
The handler is the main entry point of the penetration testing tool. It allows pentesters to perform the following operations:
1. (initialize itself with some pre-designed prompts.)
2. Start a new penetration testing session by providing the target information.
3. Ask for todo-list, and acquire the next step to perform.
4. After completing the operation, pass the information to PentestGPT.
1. Pass a tool output.
2. Pass a webpage content.
3. Pass a human description.
### System Design
#### Logic Flow Design
1. User initializes all the sessions. (**prompt**)
2. User initializes the task by
1. **User** provides the target information to the **ReasoningSession**.
2. The **ReasoningSession** generates a *task-tree* based on the target information.
3. The **ReasoningSession** decides the first todo, and passes the information to the **GenerationSession**.
4. The **GenerationSession** generates the exact command for the user to execute, and passes it to the **User**.
3. Go into the main loop. The **User** can pick to:
1. Provide todo execution results to PentestGPT.
1. The **User** provides the output of the tool to the **ParsingSession**.
2. The **ParsingSession** parses the output, and passes the information to the **ReasoningSession**.
3. The **ReasoningSession** updates the *task-tree* based on the information.
4. Do step 3.2.1-3.2.3
2. Ask for todos.
1. The **ReasoningSession** analyzes the *task-tree*. It decides the next todo, including (1) a natural language description, and (2) the exact command to execute.
2. The **ReasoningSession** passes the information to the **GenerationSession** for further verification.
3. The **GenerationSession** generates the exact command for the user to execute, and passes it to the **User**.
3. Discuss with PentestGPT by providing arbitrary information.
1. The **User** provides the information to the **ParsingSession**.
2. The **ParsingSession** parses the information:
- If it is too long, summarize it.
- Otherwise, just rephrase it.
3. The **ReasoningSession** analyzes the information, and updates the *task-tree*.
- Exit the program.
A flow-chart is shown below:
```mermaid
sequenceDiagram
participant User
participant ReasoningSession
participant GenerationSession
participant ParsingSession
User->>+ReasoningSession: 1.1 Provides target information
ReasoningSession->>+ReasoningSession: 2.1 Generates task-tree
ReasoningSession->>+GenerationSession: 2.2 Decides first todo
GenerationSession->>+User: 2.3 Generates command
loop Main Loop
User->>+ParsingSession: 3.1 Provides todo execution results or arbitrary information
alt Provides todo execution results
ParsingSession->>+ReasoningSession: 3.2 Parses output
ReasoningSession->>+ReasoningSession: 3.3 Updates task-tree
ReasoningSession->>+GenerationSession: 3.4 Analyzes task-tree for next todo
GenerationSession->>+User: 3.5 Generates command
else Asks for todos
ReasoningSession->>+ReasoningSession: 3.2 Analyzes task-tree
ReasoningSession->>+GenerationSession: 3.3 Decides next todo
GenerationSession->>+User: 3.4 Generates command
else Discusses with PentestGPT
ParsingSession->>+ReasoningSession: 3.2 Parses information
opt Information is too long
ParsingSession->>+ParsingSession: 3.2.1 Summarizes information
end
ReasoningSession->>+ReasoningSession: 3.3 Analyzes information
end
User->>-ParsingSession: 3.1 Provides todo execution results or arbitrary information
end
User->>-PentestGPT: 4. Exit
```
#### Prompts
The prompts are stored in the `prompts/prompt_class.py`.