Skip to main content

The Decompiler Artificial Intelligence Language Assistant (DAILA) is a tool for adding AI to decompilers.

Project description

DAILA

The Decompiler Artificial Intelligence Language Assistant (DAILA) is a unified interface for AI systems to be used in decompilers. Using DAILA, you can utilize various AI systems, like local and remote LLMs, all in the same scripting and GUI interfaces across many decompilers. DAILA was featured in the keynote talk at HITCON CMT 2023.

Supported Decompilers and AI Systems

DAILA interacts with the decompiler abstractly through the LibBS library. This allows DAILA to support the following decompilers:

  • IDA Pro: >= 8.4
  • Ghidra: >= 11.1
  • Binary Ninja: >= 2.4
  • angr-management: >= 9.0

DAILA supports any LLM supported in LiteLLM, such as:

  • ChatGPT
  • Claude
  • Llama2
  • Gemini
  • and more...

DAILA also supports local models of different types, like VarBERT, a local model for renaming variables in decompilation published in S&P 2024.

Installation

Install our library backend through pip and our decompiler plugin through our installer:

pip3 install dailalib && daila --install 

This is the light mode. If you want to use VarBERT, you must install the full version:

pip3 install 'dailalib[full]' && daila --install 

This will also download the VarBERT models for you through the VarBERT API. If you happen to be installing DAILA on a machine that won't have internet access, like a secure network, you can use our Docker image in the Docker Container section.

Ghidra Extra Steps

You need to do a few extra steps to get Ghidra working. Next, enable the DAILA plugin:

  1. Start Ghidra and open a binary
  2. Goto the Windows > Script Manager menu
  3. Search for daila and enable the script

You must have python3 in your path for the Ghidra version to work. We quite literally call it from inside Python 2. You may also need to enable the $USER_HOME/ghidra_scripts as a valid scripts path in Ghidra.

Manual Install (if above fails)

If the above fails, you will need to manually install. To manually install, first pip3 install dailalib on the repo, then copy the daila_plugin.py file to your decompiler's plugin directory.

Usage

DAILA is designed to be used in two ways:

  1. As a decompiler plugin with a GUI
  2. As a scripting library in your decompiler

Decompiler GUI

With the exception of Ghidra (see below), when you start your decompiler you will have a new context menu which you can access when you right-click anywhere in a function:

DAILA context menu

If you are using Ghidra, go to Tools->DAILA->Start DAILA Backend to start the backend server. After you've done this, you can use the context menu as shown above.

Scripting

You can use DAILA in your own scripts by importing the dailalib package. Here is an example using the OpenAI API:

from dailalib import LiteLLMAIAPI
from libbs.api import DecompilerInterface

deci = DecompilerInterface.discover()
ai_api = LiteLLMAIAPI(decompiler_interface=deci)
for function in deci.functions:
    summary = ai_api.summarize_function(function)

Docker Container

If you are attempting to install DAILA for a one-shot install that will not use the internet after install, like on a secure network, you can use our Docker container. You should either build the container yourself, save the image to a tarball, and then load it on the target machine, or you can use our pre-built image. You can build the container yourself by running docker build -t daila . in the root of this repo. You can also download our pre-built image by running docker pull binsync/daila:latest (the image is for x86_64 Linux). The container contains DAILA and a copy of Ghidra.

Now you need to foward X11 to the container so that you can see the GUI. To do this, you need to run the container with the following flags:

docker run -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix binsync/daila:latest

In the container, you can launch ghidra from /tools/ghidra_10.4_PUBLIC/ghidraRun. Now follow the Ghidra Extra Steps to enable the DAILA plugin and you're good to go!

Supported AI Backends

LiteLLM (many backends)

DAILA supports the LiteLLM API, which in turn supports various backends like OpenAI. To use a commercial LLM API, you must provide your own API key. As an example, to use the OpenAI API, you must have an OpenAI API key. If your decompiler does not have access to the OPENAI_API_KEY environment variable, then you must use the decompiler option from DAILA to set the API key.

Currently, DAILA supports the following prompts:

  • Summarize a function
  • Rename variables
  • Rename function
  • Identify the source of a function
  • Find potential vulnerabilities in a function
  • Summarize the man page of a library call
  • Free prompting... just type in your own prompt!

VarBERT

VarBERT is a local BERT model from the S&P 2024 paper ""Len or index or count, anything but v1": Predicting Variable Names in Decompilation Output with Transfer Learning". VarBERT is for renaming variables (both stack, register, and arguments) in decompilation. To understand how to use VarBERT as a library, please see the VarBERT API documentation. Using it in DAILA is a simple as using the GUI context-menu when clicking on a function.

Demo

You can find a demo of VarBERT running inside DAILA below:

VarBERT Demo

Supported Decompilers

  • IDA

  • Binja

  • Ghidra

  • angr management

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dailalib-3.10.2.tar.gz (33.6 kB view details)

Uploaded Source

Built Distribution

dailalib-3.10.2-py3-none-any.whl (40.1 kB view details)

Uploaded Python 3

File details

Details for the file dailalib-3.10.2.tar.gz.

File metadata

  • Download URL: dailalib-3.10.2.tar.gz
  • Upload date:
  • Size: 33.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.20

File hashes

Hashes for dailalib-3.10.2.tar.gz
Algorithm Hash digest
SHA256 7b5783ba10d0cb4b82207517facd1a92114178b41b37eefc2c22e245714eb5c8
MD5 86a39d9d5b35161b10f184ce07459aef
BLAKE2b-256 70f093ab789dd8799268676859274d1b45ef6043218e26284ffa079baceea837

See more details on using hashes here.

File details

Details for the file dailalib-3.10.2-py3-none-any.whl.

File metadata

  • Download URL: dailalib-3.10.2-py3-none-any.whl
  • Upload date:
  • Size: 40.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.20

File hashes

Hashes for dailalib-3.10.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8f793b5ab67d91534164f3c58fd83d8f8e325fb8a19b5e1b462561f54d58f4a5
MD5 9352c3afbc65bd65a2422d5a58c45b89
BLAKE2b-256 82f0f5fd15e315d3452628da62f3f3c55836fedc61e6f9a33fcf144ca9d45268

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page