reverse-engineering-rust-malware

Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.

4,032 stars

Best use case

reverse-engineering-rust-malware is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.

Teams using reverse-engineering-rust-malware should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/reverse-engineering-rust-malware/SKILL.md --create-dirs "https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/reverse-engineering-rust-malware/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/reverse-engineering-rust-malware/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How reverse-engineering-rust-malware Compares

Feature / Agentreverse-engineering-rust-malwareStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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

```python
#!/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

- [Binary Defense - Extracting Secrets from Rust Malware](https://binarydefense.com/resources/blog/digging-through-rust-to-find-gold-extracting-secrets-from-rust-malware)
- [Ghidra Extension for Rust Analysis](https://cir.nii.ac.jp/crid/1050302237609671296)
- [Fuzzing Labs - Reversing Modern Binaries](https://fuzzinglabs.com/reversing-modern-binaries/)
- [Bishop Fox - Rust for Malware Development](https://bishopfox.com/blog/rust-for-malware-development)

Related Skills

reverse-engineering-ransomware-encryption-routine

4032
from mukul975/Anthropic-Cybersecurity-Skills

Reverse engineer ransomware encryption routines to identify cryptographic algorithms, key generation flaws, and potential decryption opportunities using static and dynamic analysis.

reverse-engineering-malware-with-ghidra

4032
from mukul975/Anthropic-Cybersecurity-Skills

Reverse engineers malware binaries using NSA's Ghidra disassembler and decompiler to understand internal logic, cryptographic routines, C2 protocols, and evasion techniques at the assembly and pseudo-C level. Activates for requests involving malware reverse engineering, disassembly analysis, decompilation, binary analysis, or understanding malware internals.

reverse-engineering-ios-app-with-frida

4032
from mukul975/Anthropic-Cybersecurity-Skills

Reverse engineers iOS applications using Frida dynamic instrumentation to understand internal logic, extract encryption keys, bypass security controls, and discover hidden functionality without source code access. Use when performing authorized iOS penetration testing, analyzing proprietary protocols, understanding obfuscated logic, or extracting runtime secrets from iOS binaries. Activates for requests involving iOS reverse engineering, Frida iOS hooking, Objective-C/Swift method tracing, or iOS binary analysis.

reverse-engineering-dotnet-malware-with-dnspy

4032
from mukul975/Anthropic-Cybersecurity-Skills

Reverse engineers .NET malware using dnSpy decompiler and debugger to analyze C#/VB.NET source code, identify obfuscation techniques, extract configurations, and understand malicious functionality including stealers, RATs, and loaders. Activates for requests involving .NET malware analysis, C# malware decompilation, managed code reverse engineering, or .NET obfuscation analysis.

reverse-engineering-android-malware-with-jadx

4032
from mukul975/Anthropic-Cybersecurity-Skills

Reverse engineers malicious Android APK files using JADX decompiler to analyze Java/Kotlin source code, identify malicious functionality including data theft, C2 communication, privilege escalation, and overlay attacks. Examines manifest permissions, receivers, services, and native libraries. Activates for requests involving Android malware analysis, APK reverse engineering, mobile malware investigation, or Android threat analysis.

performing-static-malware-analysis-with-pe-studio

4032
from mukul975/Anthropic-Cybersecurity-Skills

Performs static analysis of Windows PE (Portable Executable) malware samples using PEStudio to examine file headers, imports, strings, resources, and indicators without executing the binary. Identifies suspicious characteristics including packing, anti-analysis techniques, and malicious imports. Activates for requests involving static malware analysis, PE file inspection, Windows executable analysis, or pre-execution malware triage.

performing-malware-triage-with-yara

4032
from mukul975/Anthropic-Cybersecurity-Skills

Performs rapid malware triage and classification using YARA rules to match file patterns, strings, byte sequences, and structural characteristics against known malware families and suspicious indicators. Covers rule writing, scanning, and integration with analysis pipelines. Activates for requests involving YARA rule creation, malware classification, pattern matching, sample triage, or signature-based detection.

performing-malware-persistence-investigation

4032
from mukul975/Anthropic-Cybersecurity-Skills

Systematically investigate all persistence mechanisms on Windows and Linux systems to identify how malware survives reboots and maintains access.

performing-malware-ioc-extraction

4032
from mukul975/Anthropic-Cybersecurity-Skills

Malware IOC extraction is the process of analyzing malicious software to identify actionable indicators of compromise including file hashes, network indicators (C2 domains, IP addresses, URLs), regist

performing-malware-hash-enrichment-with-virustotal

4032
from mukul975/Anthropic-Cybersecurity-Skills

Enrich malware file hashes using the VirusTotal API to retrieve detection rates, behavioral analysis, YARA matches, and contextual threat intelligence for incident triage and IOC validation.

performing-firmware-malware-analysis

4032
from mukul975/Anthropic-Cybersecurity-Skills

Analyzes firmware images for embedded malware, backdoors, and unauthorized modifications targeting routers, IoT devices, UEFI/BIOS, and embedded systems. Covers firmware extraction, filesystem analysis, binary reverse engineering, and bootkit detection. Activates for requests involving firmware security analysis, IoT malware investigation, UEFI rootkit detection, or embedded device compromise assessment.

performing-automated-malware-analysis-with-cape

4032
from mukul975/Anthropic-Cybersecurity-Skills

Deploy and operate CAPEv2 sandbox for automated malware analysis with behavioral monitoring, payload extraction, configuration parsing, and anti-evasion capabilities.