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llvm-obfuscationllvm 混淆

Agent Skill

llvm-obfuscation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

873

周安装

36

GitHub Stars

827

下载量

285
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:llvm-obfuscation(llvm 混淆)
来源仓库:https://github.com/gmh5225/awesome-llvm-security
仓库路径:skills/llvm-obfuscation
安装命令:
npx skills add https://github.com/gmh5225/awesome-llvm-security --skill llvm-obfuscation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/gmh5225/awesome-llvm-security --skill llvm-obfuscation

简介

用于处理 LLVM 混淆相关开发任务的命令行工具。

  • 适合围绕 GitHub 仓库和代码变更进行信息整理。
  • 通过 GitHub 安装,需参考原始文档验证具体能力。
  • 建议在使用前评估对编译流程的影响。llvm-obfuscation 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 注意权限控制,防止误操作破坏源代码结构。

SKILL.md

LLVM Code Obfuscation Skill

This skill provides comprehensive knowledge of LLVM-based code obfuscation frameworks and techniques for software protection and anti-reverse engineering.

Core Obfuscation Techniques

Control Flow Obfuscation

  • Control Flow Flattening (CFF): Transform structured control flow into a single dispatcher loop with state machine
  • Bogus Control Flow (BCF): Insert opaque predicates and dead code paths
  • CFG Randomization: Randomize basic block ordering and add fake edges

Data Obfuscation

  • String Encryption: Encrypt string literals at compile-time, decrypt at runtime
  • Constant Substitution: Replace constants with complex expressions
  • Variable Splitting: Split variables into multiple components

Code Transformation

  • Instruction Substitution: Replace standard instructions with equivalent complex sequences
  • MBA (Mixed Boolean-Arithmetic): Use mixed boolean-arithmetic expressions for obfuscation
  • Virtualization (VMP): Convert code into custom bytecode executed by embedded VM

Major OLLVM Frameworks

Classic OLLVM

Modern Variants

  • Hikari: Advanced features including function wrapper, anti-class-dump
  • Pluto-Obfuscator: Well-maintained with MBA, indirect branch, global encryption
  • Arkari: Modern implementation with enhanced features
  • o-mvll: Mobile-focused obfuscator for iOS/Android

Specialized Tools

  • IR VMP: GANGE666/xVMP, NiTianErXing666/SmallVmp for virtualization
  • Warbird: Microsoft's commercial obfuscation technology

Implementation Guidelines

Creating Custom LLVM Obfuscation Pass

#include "llvm/Pass.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/Instructions.h"

class MyObfuscationPass : public llvm::FunctionPass {
public:
    static char ID;
    MyObfuscationPass() : FunctionPass(ID) {}

    bool runOnFunction(llvm::Function &F) override {
        // Implement obfuscation logic
        for (auto &BB : F) {
            for (auto &I : BB) {
                // Transform instructions
            }
        }
        return true;
    }
};

Best Practices

  1. Preserve Semantics: Ensure transformations don't break program correctness
  2. Randomization: Use seeded random number generators for reproducible builds
  3. Layered Approach: Combine multiple obfuscation techniques
  4. Performance Balance: Consider runtime overhead vs protection level
  5. Testing: Extensive testing across different inputs and platforms

Toolchain Integration

NDK Integration

  • OLLVM with Android NDK (r17-r23+)
  • Examples: android-ndk-aarch64-host-LLVM6.0-Ollvm-Armariris

Compiler Toolchains

  • ollvm-mingw: Windows cross-compilation
  • ollvm-rust: Rust toolchain integration
  • Swift integration: swift-Ollvm11

Anti-Deobfuscation Considerations

When implementing obfuscation:

  • Consider resistance to symbolic execution (SymCC, KLEE)
  • Add protection against pattern matching deobfuscators
  • Implement anti-debugging checks
  • Use dynamic dispatch to hinder static analysis

Resources

Refer to the main README.md for a comprehensive list of OLLVM implementations and related tools.

Getting Detailed Information

When you need detailed and up-to-date resource links, tool lists, or project references, fetch the latest data from:

https://raw.githubusercontent.com/gmh5225/awesome-llvm-security/refs/heads/main/README.md

This README contains comprehensive curated lists of:

  • 80+ OLLVM implementations and forks (OLLVM section)
  • MSVC Warbird obfuscation tools (MSVC Warbird section)
  • IR-based VMP and virtualization projects
  • NDK integration examples for different versions

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36%
按下载量换算103

Claude

31.28%
按下载量换算89

Cursor

16.85%
按下载量换算48

Gemini CLI

9.97%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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