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.
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/reverse-engineering-rust-malware/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How reverse-engineering-rust-malware Compares
| Feature / Agent | reverse-engineering-rust-malware | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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.
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
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