Malimite integrates with large language models to help you make sense of decompiled code. Three built-in AI actions are available from the Function Assist panel in the analysis window: Auto Fix, Summarize, and Find Vulnerabilities.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/LaurieWired/Malimite/llms.txt
Use this file to discover all available pages before exploring further.
Overview of AI actions
| Action | What it does |
|---|---|
| Auto Fix | Translates decompiled functions back into idiomatic Swift or Objective-C |
| Summarize | Describes what the selected functions do and identifies known library patterns |
| Find Vulnerabilities | Performs a security analysis and identifies exploitable issues |
Auto Fix
Auto Fix translates decompiled output back to readable source code. Malimite detects whether the binary was compiled from Swift or Objective-C by scanning for Swift runtime markers (_swift_, _$s, SwiftCore, Swift Runtime) in the Mach-O binary, then targets that language automatically.
The prompt instructs the model to:
- Preserve method names and global variables exactly
- Adjust local variable names for readability
- Return only the translated functions — no additional methods or global definitions
- Wrap each function with
BEGIN_FUNCTION/END_FUNCTIONmarkers so the result can be written back into the editor
Summarize
Summarize asks the model to describe what the selected functions do, highlight key functionality, note any notable patterns, and identify whether the code belongs to a well-known library. The response is formatted in markdown and displayed in a dialog.Find Vulnerabilities
Find Vulnerabilities asks the model to analyze the selected functions for security issues. The prompt instructs the model to consider:- Memory safety problems
- Input validation weaknesses
- Authentication bypass possibilities
- Common coding pitfalls
Supported models
- OpenAI
- Local model
Malimite supports the following OpenAI models:
GPT-4 Turbo is the default model.Requests are sent to
| Display name | Model ID |
|---|---|
| OpenAI GPT-4 Turbo | gpt-4-turbo |
| OpenAI GPT-4 Mini | gpt-4-mini |
https://api.openai.com/v1/chat/completions using the standard chat completions API.Processing large binaries with many functions can consume a significant number of tokens. Consider selecting only the functions most relevant to your analysis to manage API costs.
Setting up API keys
Enter your API key
Paste your OpenAI API key into the OpenAI API Key field. Keys are encrypted before being written to disk using Malimite’s built-in key encryption.
Setting up a local model
Start your local inference server
Launch LM Studio, Text Generation WebUI, Ollama, or another OpenAI-compatible server and load a model.
Set the Local Model URL
Enter the full URL of your server’s completion endpoint in the Local Model URL field (for example,
http://localhost:1234).Running an AI action
Select a class in the tree
Click a class node in the Classes tree. The Function Assist panel on the right populates with the functions belonging to that class.
Select functions
Check individual functions in the function list, or use Select All to include every function in the class. You must select at least one function before executing.
Execute
Click Execute. A confirmation dialog shows which functions will be sent and to which model.
- Click Confirm to send the request immediately.
- Click Edit Prompt to review and modify the assembled prompt before sending.