Metadata-Version: 2.4
Name: llmasm-ananya
Version: 0.4.0
Summary: LLM Attack Surface Mapper for AI Security Testing
Author: Ananya Chatterjee
Requires-Python: >=3.9
Description-Content-Type: text/markdown

```text
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██║     ██║     ████╗ ████║██╔══██╗██╔════╝████╗ ████║
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██║     ██║     ██║╚██╔╝██║██╔══██║╚════██║██║╚██╔╝██║
███████╗███████╗██║ ╚═╝ ██║██║  ██║███████║██║ ╚═╝ ██║
╚══════╝╚══════╝╚═╝     ╚═╝╚═╝  ╚═╝╚══════╝╚═╝     ╚═╝

LLM Attack Surface Mapper
````

<div align="center">

# LLMASM

### Discover • Intercept • Exploit • Verify

Mapping the hidden attack surface of AI-powered applications.

</div>

<p align="center">

<img src="https://img.shields.io/badge/Python-3.10+-3776AB?style=for-the-badge&logo=python&logoColor=white">
<img src="https://img.shields.io/badge/AI-Security-red?style=for-the-badge">
<img src="https://img.shields.io/badge/OWASP-LLM-green?style=for-the-badge">
<img src="https://img.shields.io/badge/CLI-Tool-black?style=for-the-badge">
<img src="https://img.shields.io/badge/License-MIT-yellow?style=for-the-badge">
<img src="https://img.shields.io/badge/Research-Security-purple?style=for-the-badge">
<img src="https://img.shields.io/badge/Contributions-Welcome-brightgreen?style=for-the-badge">
<img src="https://img.shields.io/badge/Security-Policy-red?style=for-the-badge">

</p>

---

## Tech Stack

<p align="center">

<img src="https://img.shields.io/badge/Python-3776AB?style=flat-square&logo=python&logoColor=white">
<img src="https://img.shields.io/badge/Playwright-2EAD33?style=flat-square&logo=playwright&logoColor=white">
<img src="https://img.shields.io/badge/Requests-000000?style=flat-square">
<img src="https://img.shields.io/badge/Typer-009639?style=flat-square">
<img src="https://img.shields.io/badge/Plotly-3F4F75?style=flat-square&logo=plotly">
<img src="https://img.shields.io/badge/HTML-Report-E34F26?style=flat-square&logo=html5">

</p>

---

## Why LLMASM?

Traditional scanners treat AI applications as black boxes.

LLMASM treats them as attack surfaces.

* Hidden AI endpoint discovery
* Prompt injection testing
* AI proxy detection
* Tool chain mapping
* Dynamic traffic interception
* LLM-assisted verification

---

## Architecture

```text
        ┌───────────────────┐
        │   Target Website  │
        └─────────┬─────────┘
                  │
     ┌────────────┴────────────┐
     │                         │

┌─────────────┐        ┌─────────────┐
│ JS Recon    │        │ Browser     │
│ Engine      │        │ Interceptor │
└──────┬──────┘        └──────┬──────┘
       │                      │
       └──────────┬───────────┘
                  │
          ┌───────▼───────┐
          │ AI Discovery  │
          └───────┬───────┘
                  │
          ┌───────▼───────┐
          │ Active Tests  │
          └───────┬───────┘
                  │
          ┌───────▼───────┐
          │ LLM Judge     │
          └───────┬───────┘
                  │
          ┌───────▼───────┐
          │ HTML Reports  │
          └───────────────┘
```

---

## Installation

```bash
git clone https://github.com/yourusername/llmasm

cd llmasm

pip install -r requirements.txt
```

---

## Usage

```bash
llmasm scan https://target-ai-app.com --stealth
```

---

## Example Output

```text
=========================================

Target      : https://target.com
AI Score    : 92
API Score   : 85

Findings:

[HIGH] Prompt Injection Surface
[HIGH] Internal AI Proxy
[MEDIUM] Hidden API Endpoint
[LOW] Framework Fingerprint

=========================================
```

---

## Features

* Static JavaScript Analysis
* Dynamic Network Interception
* Prompt Injection Testing
* AI Endpoint Discovery
* WAF Evasion
* LLM-as-a-Judge
* Interactive Reports
* Relationship Graphs

---

## Research Areas

* Prompt Injection
* System Prompt Leakage
* Hidden AI APIs
* Tool Abuse
* RAG Exposure
* Agent Chains
* Context Leakage

---

## Community & Security

LLMASM welcomes contributions, security research, and responsible disclosure.

### Contributing

Interested in improving LLMASM?

* Add new payloads
* Improve detection engines
* Enhance reports
* Contribute research
* Fix bugs and documentation

Please read:

* [CONTRIBUTING.md](CONTRIBUTING.md)

before submitting a pull request.

---

### Security Reporting

If you discover a vulnerability within LLMASM itself, please follow the responsible disclosure process described in:

* [SECURITY.md](SECURITY.md)

Please do not publicly disclose unpatched vulnerabilities.

---

## Disclaimer

This project is intended for:

* Authorized security testing
* Security research
* Educational use
* Bug bounty programs

Unauthorized testing of systems without permission may be illegal.

---

<div align="center">

### AI applications are not black boxes.

# They are attack surfaces.

⭐ Star the repository if you find it useful.

</div>
