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Binary Ninja

Safety: 65/100

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Binary Ninja MCP enables seamless integration between Binary Ninja and LLM clients, enhancing reverse engineering workflows with AI assistance.

MCP ServersFreemium

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Overview

Binary Ninja MCP enables seamless integration between Binary Ninja and LLM clients, enhancing reverse engineering workflows with AI assistance.

Binary Ninja MCP is generally safe for reverse engineering tasks when used with caution. The read-only operations pose minimal risk, but users should exercise care when using tools that modify the binary analysis or create new functions. It is risky if combined with an untrusted LLM that could generate malicious modifications.

Performance depends on the size and complexity of the binary being analyzed. Decompilation and cross-reference analysis can be time-consuming for large binaries.

No direct cost associated with the plugin itself. However, using LLM clients may incur costs depending on the service and usage.

CloudPython226 starsGPL-3.0Released 12/16/2025CI/CD

Connections & Capabilities

Connects To

GitHub

Capabilities

ReadWrite

Client Compatibility

Claude Desktop

full

Cursor

full

Windsurf

full

VS Code (Copilot)

untested

Quickstart

Install

pip install -r

Claude Desktop Config

{
    "mcpServers": {
        "binary_ninja_mcp": {
            "command": "/ABSOLUTE/PATH/TO/Binary Ninja/plugins/repositories/community/plugins/fosdickio_binary_ninja_mcp/.venv/bin/python",
            "args": [
                "/ABSOLUTE/PATH/TO/Binary Ninja/plugins/repositories/community/plugins/fosdickio_binary_ninja_mcp/bridge/binja_mcp_bridge.py"
            ]
        }
    }
}

Tools (7)

safe

decompile_function

Decompiles a function by name or address, returning HLIL-like code.

Read-only operation that retrieves decompiled code.

safe

get_assembly_function

Retrieves the assembly representation of a function by name or address.

Read-only operation that retrieves assembly code.

moderate

define_types

Adds type definitions from a C string type definition.

Modifies the binary analysis by adding type information.

high

make_function_at

Creates a function at a specified address.

Can create new functions, potentially altering program control flow.

safe

get_xrefs_to

Get all cross references (code and data) to an address.

Read-only operation that retrieves cross-reference information.

safe

get_comment

Get the comment at a specific address.

Read-only operation that retrieves comments.

moderate

delete_comment

Delete the comment at a specific address.

Deletes a comment at a specific address.

Security

Auth Method

None

Data Locality

cloud

Known Risks

!LLM prompt injection could lead to unintended modifications of the binary analysis.
!Improperly defined types could cause analysis errors or crashes.
!Creating functions at arbitrary addresses could lead to code execution vulnerabilities.
!Over-reliance on LLM suggestions without manual verification could lead to incorrect analysis.

Safety Score

moderate risk

Positive

+Primarily focuses on reverse engineering tasks.
+Requires user interaction to initiate actions.
+No direct internet access from the core plugin.
+Most operations are read-only, retrieving information from the binary.

Risks

-Includes tools that can modify the binary analysis (e.g., adding comments, defining types).
-Potential for misuse if combined with unrestricted LLM prompts.
-Requires careful handling of user-defined types and comments to avoid unintended consequences.
-The `make_function_at` tool could lead to unexpected code execution if used improperly.

Use Cases

Reverse Engineering

-Automated function decompilation and analysis
-Identifying cross-references and data dependencies
-Automated malware analysis and vulnerability discovery

CTF Challenge Solving

-Automated binary analysis to identify flags and vulnerabilities
-Generating exploit code based on identified vulnerabilities
-Automated code deobfuscation and simplification

Vulnerability Research

-Identifying potential vulnerabilities in closed-source binaries
-Automated patch analysis and reverse engineering
-Generating proof-of-concept exploits for identified vulnerabilities

Who Is This For?

Best For

Reverse engineers
Security researchers
CTF players
Malware analysts
Vulnerability researchers

Not Ideal For

Users unfamiliar with reverse engineering concepts
Automated deployment in critical production environments without thorough testing
Analyzing extremely large or complex binaries without sufficient resources

Autonomy & Execution

Default ModeRead and Write enabled

Destructive Tools

Autonomy is dependent on the LLM client and the prompts provided. Exercise caution when granting full autonomy to the LLM.

StatelessYes

Retry LogicNot documented

ConcurrencySingle-threaded

Production Tip

Start with read-only operations and gradually introduce write operations as you gain confidence in the LLM's capabilities.

FAQ

What MCP clients are supported?

The plugin supports any MCP client, with auto-setup for Cline, Roo Code, Claude Desktop, Cursor, Windsurf, Claude Code, and LM Studio.

How do I install the plugin?

You can install it through the Binary Ninja Plugin Manager or manually by copying the repository into the Binary Ninja plugins folder.

Do I need to manually configure the MCP client?

No, if you use a supported MCP client and follow the installation steps, auto-setup should handle the configuration.

What kind of prompts can I use?

You can use prompts related to CTF challenges, malware analysis, vulnerability research, and general reverse engineering tasks.

What if my MCP client is not auto-configured?

You can manually configure it using the provided JSON configuration snippet and the `mcp_client_installer.py` script.

How can I ensure the safety of using this plugin with an LLM?

Start with read-only operations, carefully review LLM suggestions, and avoid granting full autonomy to the LLM without thorough testing.

Can I use this plugin to analyze any type of binary?

The plugin supports a wide range of binary formats, but performance may vary depending on the size and complexity of the binary.

Key Features

MCP Server Integration - Allows standard-compliant communication between Binary Ninja and any MCP-compatible LLM client.

Seamless LLM Interoperability - Enables users to choose their preferred AI client while maintaining direct access to binary data.

Reverse Engineering Workflow Automation - Facilitates faster analysis by connecting binary function data directly to AI reasoning engines.

Contextual Data Exchange - Bridges the gap between static binary analysis and AI-driven insights for improved code understanding.

Use Cases & Problems Solved

Use Cases

•Use when you need an LLM to explain complex binary functions directly within your Binary Ninja workspace.
•Perfect for automating the generation of function names or variable types by querying AI models during reverse engineering.
•Ideal if you need to bridge the gap between static analysis results in Binary Ninja and conversational AI reasoning capabilities.
•Great for streamlining the analysis of obfuscated code snippets by feeding them into an LLM via the MCP protocol.
•Use when building custom AI-assisted workflows that require real-time interaction between binary analysis data and Large Language Models.
•Perfect for security researchers who want to speed up vulnerability discovery by using AI to identify patterns across multiple decompiled functions.

Problems Solved

✓Eliminates the manual effort of copying and pasting binary code snippets between Binary Ninja and external AI chat interfaces.
✓Reduces the context-switching overhead that occurs when moving from static analysis tools to separate AI-assisted documentation or analysis tools.
✓Removes the friction of manually formatting binary data for AI prompts by utilizing the structured MCP protocol.
✓Solves the challenge of integrating proprietary or local LLMs directly into established reverse engineering pipelines.

Who It's For

Security researchers specializing in malware analysisReverse engineers working on firmware vulnerability assessmentVulnerability analysts performing manual code auditingCybersecurity students learning to optimize decompilation workflowsAutomated exploit developers building AI-integrated toolchains

Metrics

Discovered2/14/2026

Reviews0

Saved By0 users

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