reversing-rust-analyze
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.
- License 许可
- MIT
- 最近更新
- 2026-09-01
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- reversing-rust-analyze
- tags
- [ "rust", "reverse-engineering", "malware-analysis", "ghidra", "ida-pro", "binary-analysis", "rust-malware" ]
- capec
- []
- model
- sonnet
- tools
- [ "Read", "Bash", "Glob", "Grep" ]
- domain
- cybersecurity
- maxTurns
- 20
- nist_csf
- [ "DE.AE-02", "RS.AN-03", "ID.RA-01", "DE.CM-01" ]
- subdomain
- malware-analysis
- description
- 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.
02 资源文件 1
- 参考文档index.json672 B
03 SKILL.md 正文
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
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