Burpgpt –  Integrate OpenAI GPT with Burp Suite to Discover Highly Bespoke Vulnerabilities

Burpgpt - Connect OpenAI gpt with burp suite to detect security vulnerabilities that traditional scanners might miss

Burpgpt is Burp Suite extension that integrates OpenAI’s GPT to perform an additional passive scan for discovering highly bespoke vulnerabilities, and enables running traffic-based analysis of any type.

Overview

Burpgpt leverages the power of AI to detect security vulnerabilities that traditional scanners might miss. It sends web traffic to an OpenAI model specified by the user, enabling sophisticated analysis within the passive scanner. This extension offers customisable prompts that enable tailored web traffic analysis to meet the specific needs of each user.

The extension generates an automated security report that summarises potential security issues based on the user’s prompt and real-time data from Burp-issued requests. By leveraging AI and natural language processing, the extension streamlines the security assessment process and provides security professionals with a higher-level overview of the scanned application or endpoint. This enables them to more easily identify potential security issues and prioritise their analysis, while also covering a larger potential attack surface.

Warning:

  • Data traffic is sent to OpenAI for analysis. If you have concerns about this or are using the extension for security-critical applications, it is important to carefully consider this and review OpenAI’s Privacy Policy for further information.
  • While the report is automated, it still requires triaging and post-processing by security professionals, as it may contain false positives.
  • The effectiveness of this extension is heavily reliant on the quality and precision of the prompts created by the user for the selected GPT model. This targeted approach will help ensure the GPT model generates accurate and valuable results for your security analysis.

Features

  • Adds a passive scan check, allowing users to submit HTTP data to an OpenAI-controlled GPT model for analysis through a placeholder system.
  • Leverages the power of OpenAI's GPT models to conduct comprehensive traffic analysis, enabling detection of various issues beyond just security vulnerabilities in scanned applications.
  • Enables granular control over the number of GPT tokens used in the analysis by allowing for precise adjustments of the maximum prompt length.
  • Offers users multiple OpenAI models to choose from, allowing them to select the one that best suits their needs.
  • Empowers users to customise prompts and unleash limitless possibilities for interacting with OpenAI models. See through the Example Use Cases bellow for inspiration.
  • Integrates with Burp Suite, providing all native features for pre- and post-processing, including displaying analysis results directly within the Burp UI for efficient analysis.
  • Provides troubleshooting functionality via the native Burp Event Log, enabling users to quickly resolve communication issues with the OpenAI API.

Requirements

1. System requirements

  • Operating System: Compatible with LinuxmacOS, and Windows operating systems.
  • Java Development Kit (JDK): Version 11 or later.
  • Burp Suite Professional or Community Edition: Version 2023.3.2 or later.
    • Please note that using any version lower than 2023.3.2 may result in a java.lang.NoSuchMethodError. It is crucial to use the specified version or a more recent one to avoid this issue.

2. Build tool

  • Gradle: Version 6.9 or later (recommended). The build.gradle file is provided in the project repository.

3. Environment variables

  • Set up the JAVA_HOME environment variable to point to the JDK installation directory.

Please ensure that all system requirements, including a compatible version of Burp Suite, are met before building and running the project. Note that the project’s external dependencies will be automatically managed and installed by Gradle during the build process. Adhering to the requirements will help avoid potential issues and reduce the need for opening new issues in the project repository.

Burpgpt Installation

1. Compilation

  1. Ensure you have Gradle installed and configured.
  2. Download the burpgpt repository:
git clone https://github.com/aress31/burpgpt cd .\burpgpt\

  1. Build the standalone jar:
./gradlew shadowJar

2. Loading the Extension Into Burp Suite

To install burpgpt in Burp Suite, first go to the Extensions tab and click on the Add button. Then, select the burpgpt-all jar file located in the .\lib\build\libs folder to load the extension.

Usage

To start using burpgpt, users need to complete the following steps in the Settings panel, which can be accessed from the Burp Suite menu bar:

  • Enter a valid OpenAI API key.
  • Select a model.
  • Define the max prompt size. This field controls the maximum prompt length sent to OpenAI to avoid exceeding the maxTokens of GPT models (typically around 2048 for GPT-3).
  • Adjust or create custom prompts according to your requirements.
Burpgpt - Connect OpenAI gpt with burp suite to detect security vulnerabilities that traditional scanners might miss

Once configured as outlined above, the Burp passive scanner sends each request to the chosen OpenAI model via the OpenAI API for analysis, producing Informational-level severity findings based on the results.

Burpgpt -  Integrate OpenAI GPT with Burp Suite to Discover Highly Bespoke Vulnerabilities

Prompt Configuration

Burpgpt enables users to tailor the prompt for traffic analysis using a placeholder system. To include relevant information, we recommend using these placeholders, which the extension handles directly, allowing dynamic insertion of specific values into the prompt:

PlaceholderDescription
{REQUEST}The scanned request.
{URL}The URL of the scanned request.
{METHOD}The HTTP request method used in the scanned request.
{REQUEST_HEADERS}The headers of the scanned request.
{REQUEST_BODY}The body of the scanned request.
{RESPONSE}The scanned response.
{RESPONSE_HEADERS}The headers of the scanned response.
{RESPONSE_BODY}The body of the scanned response.
{IS_TRUNCATED_PROMPT}boolean value that is programmatically set to true or false to indicate whether the prompt was truncated to the Maximum Prompt Size defined in the Settings.

These placeholders can be used in the custom prompt to dynamically generate a request/response analysis prompt that is specific to the scanned request.

Example Use Cases

The following list of example use cases showcases the bespoke and highly customisable nature of burpgpt, which enables users to tailor their web traffic analysis to meet their specific needs.

  • Identifying potential vulnerabilities in web applications that use a crypto library affected by a specific CVE:
Analyse the request and response data for potential security vulnerabilities related to the {CRYPTO_LIBRARY_NAME} crypto library affected by CVE-{CVE_NUMBER}:
Web Application URL: {URL} Crypto Library Name: {CRYPTO_LIBRARY_NAME} CVE Number: CVE-{CVE_NUMBER} Request Headers: {REQUEST_HEADERS} Response Headers: {RESPONSE_HEADERS} Request Body: {REQUEST_BODY} Response Body: {RESPONSE_BODY}
Identify any potential vulnerabilities related to the {CRYPTO_LIBRARY_NAME} crypto library affected by CVE-{CVE_NUMBER} in the request and response data and report them.

  • Scanning for vulnerabilities in web applications that use biometric authentication by analysing request and response data related to the authentication process:
Analyse the request and response data for potential security vulnerabilities related to the biometric authentication process:
Web Application URL: {URL} Biometric Authentication Request Headers: {REQUEST_HEADERS} Biometric Authentication Response Headers: {RESPONSE_HEADERS} Biometric Authentication Request Body: {REQUEST_BODY} Biometric Authentication Response Body: {RESPONSE_BODY}
Identify any potential vulnerabilities related to the biometric authentication process in the request and response data and report them.

  • Analysing the request and response data exchanged between serverless functions for potential security vulnerabilities:
Analyse the request and response data exchanged between serverless functions for potential security vulnerabilities:
Serverless Function A URL: {URL} Serverless Function B URL: {URL} Serverless Function A Request Headers: {REQUEST_HEADERS} Serverless Function B Response Headers: {RESPONSE_HEADERS} Serverless Function A Request Body: {REQUEST_BODY} Serverless Function B Response Body: {RESPONSE_BODY}
Identify any potential vulnerabilities in the data exchanged between the two serverless functions and report them.

  • Analysing the request and response data for potential security vulnerabilities specific to a Single-Page Application (SPA) framework:
Analyse the request and response data for potential security vulnerabilities specific to the {SPA_FRAMEWORK_NAME} SPA framework:
Web Application URL: {URL} SPA Framework Name: {SPA_FRAMEWORK_NAME} Request Headers: {REQUEST_HEADERS} Response Headers: {RESPONSE_HEADERS} Request Body: {REQUEST_BODY} Response Body: {RESPONSE_BODY}
Identify any potential vulnerabilities related to the {SPA_FRAMEWORK_NAME} SPA framework in the request and response data and report them.



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