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reverse-engineering-rust-malwarereverse engineering Rust malware 搜索

Agent Skill

reverse-engineering-rust-malware 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

423

周安装

18

GitHub Stars

5,882

下载量

148
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:reverse-engineering-rust-malware(reverse engineering Rust malware 搜索)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/reverse-engineering-rust-malware
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill reverse-engineering-rust-malware
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

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skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill reverse-engineering-rust-malware

简介

reverse-engineering-rust-malware 用于查找 Rust 语言编写的恶意软件逆向工程方法,适合在 Codex、Claude、Cursor、Gemini CLI 中分析现代二进制程序。

  • 支持 Rust 符号恢复、堆栈帧解析与跨平台行为追踪。
  • 输入样本路径或功能描述后,输出反编译策略与依赖库识别建议。
  • 需确保运行环境支持 Rust ABI 解析,并遵守法律合规要求。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Reverse Engineering Rust Malware

Overview

Rust has become increasingly popular for malware development due to its cross-compilation, memory safety guarantees, and the complexity it introduces for reverse engineers. Rust binaries contain the entire standard library statically linked, producing large binaries with extensive boilerplate code. Key challenges include non-null-terminated strings (Rust uses fat pointers with pointer+length), monomorphization generating duplicated generic code, complex error handling (Result/Option unwrap chains), and unfamiliar calling conventions. Decompiling Rust to C produces unhelpful output compared to C/C++ binaries. Tools like Ghidra scripts for crate extraction, and training focused on Rust-specific patterns (2024-2025) help address these challenges. Notable Rust malware includes BlackCat/ALPHV ransomware, Hive ransomware variants, and Buer Loader.

When to Use

  • When performing authorized security testing that involves reverse engineering rust malware
  • When analyzing malware samples or attack artifacts in a controlled environment
  • When conducting red team exercises or penetration testing engagements
  • When building detection capabilities based on offensive technique understanding

Prerequisites

  • IDA Pro 8.0+ or Ghidra 11.0+
  • Rust toolchain for reference compilation
  • Python 3.9+ for helper scripts
  • Understanding of Rust memory model (ownership, borrowing)
  • Familiarity with Rust string types (String, &str, CString)

Workflow

Step 1: Identify and Parse Rust Binary Metadata

#!/usr/bin/env python3
"""Analyze Rust malware binary metadata and extract crate dependencies."""
import re
import sys
import json

def identify_rust_binary(data):
    """Check if binary is Rust-compiled and extract version info."""
    indicators = {
        "rust_panic_strings": bool(re.search(rb'panicked at', data)),
        "rust_unwrap": bool(re.search(rb'called.*unwrap.*on.*None', data)),
        "core_panic": bool(re.search(rb'core::panicking', data)),
        "std_rt": bool(re.search(rb'std::rt::lang_start', data)),
        "cargo_path": bool(re.search(rb'\.cargo[/\\]registry', data)),
        "rustc_version": None,
    }

    version = re.search(rb'rustc\s+(\d+\.\d+\.\d+)', data)
    if version:
        indicators["rustc_version"] = version.group(1).decode()

    is_rust = sum(1 for v in indicators.values() if v) >= 2
    return is_rust, indicators

def extract_crates(data):
    """Extract Rust crate (dependency) names from binary strings."""
    crate_pattern = re.compile(
        rb'(?:crates\.io-[a-f0-9]+/|\.cargo/registry/src/[^/]+/)'
        rb'([\w-]+)-(\d+\.\d+\.\d+)'
    )
    crates = {}
    for match in crate_pattern.finditer(data):
        name = match.group(1).decode()
        version = match.group(2).decode()
        crates[name] = version

    # Also check for common malware-relevant crates
    suspicious_crates = {
        "reqwest": "HTTP client",
        "hyper": "HTTP library",
        "tokio": "Async runtime",
        "aes": "AES encryption",
        "chacha20": "ChaCha20 encryption",
        "rsa": "RSA encryption",
        "ring": "Crypto library",
        "base64": "Base64 encoding",
        "winapi": "Windows API bindings",
        "winreg": "Registry access",
        "sysinfo": "System information",
        "screenshots": "Screen capture",
        "clipboard": "Clipboard access",
        "keylogger": "Key logging",
    }

    capabilities = []
    for crate_name, description in suspicious_crates.items():
        if crate_name in crates:
            capabilities.append({
                "crate": crate_name,
                "version": crates[crate_name],
                "capability": description,
            })

    return crates, capabilities

def extract_rust_strings(data):
    """Extract strings handling Rust's non-null-terminated format."""
    # Rust strings are stored as pointer+length, but string literals
    # are often in .rodata as contiguous sequences
    strings = []
    ascii_pattern = re.compile(rb'[\x20-\x7e]{8,500}')
    for match in ascii_pattern.finditer(data):
        s = match.group().decode('ascii')
        # Filter for malware-relevant strings
        keywords = ['http', 'socket', 'encrypt', 'decrypt', 'shell',
                    'exec', 'cmd', 'upload', 'download', 'persist',
                    'registry', 'mutex', 'pipe', 'inject']
        if any(kw in s.lower() for kw in keywords):
            strings.append(s)

    return strings

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print(f"Usage: {sys.argv[0]} <rust_binary>")
        sys.exit(1)

    with open(sys.argv[1], 'rb') as f:
        data = f.read()

    is_rust, indicators = identify_rust_binary(data)
    print(f"[{'+'if is_rust else '-'}] Rust binary: {is_rust}")
    print(json.dumps(indicators, indent=2, default=str))

    crates, capabilities = extract_crates(data)
    print(f"\n[+] Crates ({len(crates)}):")
    for name, ver in sorted(crates.items()):
        print(f"  {name} v{ver}")

    if capabilities:
        print(f"\n[!] Suspicious capabilities:")
        for cap in capabilities:
            print(f"  {cap['crate']} -> {cap['capability']}")

    strings = extract_rust_strings(data)
    if strings:
        print(f"\n[+] Suspicious strings ({len(strings)}):")
        for s in strings[:20]:
            print(f"  {s}")

Validation Criteria

  • Binary correctly identified as Rust-compiled with version info
  • Crate dependencies extracted revealing malware capabilities
  • Rust-specific string extraction handles fat pointer format
  • Main entry point and core logic functions identified
  • Encryption, networking, and persistence code located

References

适合场景

01

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02

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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

37.35%
按下载量换算55

Claude

31.48%
按下载量换算47

Cursor

19.14%
按下载量换算28

Gemini CLI

8.08%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill reverse-engineering-rust-malware 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

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来源信息

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