Njones17 Analyzing Golang Malware with Ghidra
Overview
Go (Golang) has become a popular language for malware authors due to its cross-compilation capabilities, static linking that produces self-contained binaries, and the complexity it introduces for reverse engineering. Go binaries contain the entire runtime, standard library, and all dependencies statically linked, resulting in large binaries (often 5-15MB) with thousands of functions. Ghidra struggles with Go-specific string formats (non-null-terminated), stripped function names, and goroutine concurrency patterns. Specialized tools like GoResolver (Volexity, 2025) use control-flow graph similarity to automatically deobfuscate and recover function names in stripped or obfuscated Go binaries.
Prerequisites
- Ghidra 11.0+ with JDK 17+
- GoResolver plugin (for function name recovery)
- Go Reverse Engineering Tool Kit (go-re.tk)
- Python 3.9+ for helper scripts
- Understanding of Go runtime internals (goroutines, channels, interfaces)
- Familiarity with Go binary structure (pclntab, moduledata, itab)
Key Concepts
Go Binary Structure
Go binaries embed rich metadata in the pclntab (PC Line Table) structure, which maps program counters to function names, source files, and line numbers. Even stripped binaries retain this metadata. The moduledata structure contains pointers to type information, itabs (interface tables), and the pclntab itself. Go strings are stored as a pointer-length pair rather than null-terminated C strings.
Function Recovery in Stripped Binaries
Despite stripping symbol tables, Go binaries retain function names within the pclntab. However, obfuscation tools like garble rename functions to random strings. GoResolver addresses this by computing control-flow graph signatures of obfuscated functions and matching them against a database of known Go standard library and third-party package functions.
Crate/Dependency Extraction
Go's dependency management embeds module paths and version strings in the binary. Extracting these reveals the malware's third-party dependencies (HTTP libraries, encryption packages, C2 frameworks), which provides insight into capabilities without full reverse engineering.
Practical Steps
Step 1: Initial Binary Analysis
#!/usr/bin/env python3
"""Analyze Go binary metadata for malware analysis."""
import struct
import sys
import re
def find_go_build_info(data):
"""Extract Go build information from binary."""
# Go buildinfo magic: \xff Go buildinf:
magic = b'\xff Go buildinf:'
offset = data.find(magic)
if offset == -1:
return None
print(f"[+] Go build info at offset 0x{offset:x}")
# Extract Go version string nearby
go_version = re.search(rb'go\d+\.\d+(?:\.\d+)?', data[offset:offset+256])
if go_version:
print(f" Go Version: {go_version.group().decode()}")
return offset
def find_pclntab(data):
"""Locate the pclntab (PC Line Table) structure."""
# pclntab magic bytes vary by Go version
magics = {
b'\xfb\xff\xff\xff\x00\x00': "Go 1.2-1.15",
b'\xfa\xff\xff\xff\x00\x00': "Go 1.16-1.17",
b'\xf1\xff\xff\xff\x00\x00': "Go 1.18-1.19",
b'\xf0\xff\xff\xff\x00\x00': "Go 1.20+",
}
for magic, version in magics.items():
offset = data.find(magic)
if offset != -1:
print(f"[+] pclntab found at 0x{offset:x} ({version})")
return offset, version
return None, None
def extract_function_names(data, pclntab_offset):
"""Extract function names from pclntab."""
if pclntab_offset is None:
return []
functions = []
# Function name strings follow specific patterns
func_pattern = re.compile(
rb'(?:main|runtime|fmt|net|os|crypto|encoding|io|sync|'
rb'syscall|reflect|strings|bytes|path|time|math|sort|'
rb'github\.com|golang\.org)[/\.][\w/.]+',
)
for match in func_pattern.finditer(data):
name = match.group().decode('utf-8', errors='replace')
if len(name) > 4 and len(name) < 200:
functions.append(name)
return sorted(set(functions))
def extract_go_strings(data):
"""Extract Go-style strings (pointer+length pairs)."""
# Go strings are not null-terminated; extract readable sequences
strings = []
ascii_pattern = re.compile(rb'[\x20-\x7e]{10,}')
for match in ascii_pattern.finditer(data):
s = match.group().decode('ascii')
# Filter for interesting malware strings
interesting = [
'http', 'https', 'tcp', 'udp', 'dns',
'cmd', 'shell', 'exec', 'upload', 'download',
'encrypt', 'decrypt', 'key', 'token', 'password',
'c2', 'beacon', 'agent', 'implant', 'bot',
'mutex', 'persist', 'registry', 'scheduled',
]
if any(kw in s.lower() for kw in interesting):
strings.append(s)
return strings
def extract_dependencies(data):
"""Extract Go module dependencies from binary."""
deps = []
# Module paths follow pattern: github.com/user/repo
dep_pattern = re.compile(
rb'((?:github\.com|gitlab\.com|golang\.org|gopkg\.in|'
rb'go\.etcd\.io|google\.golang\.org)/[^\x00\s]{5,80})'
)
for match in dep_pattern.finditer(data):
dep = match.group().decode('utf-8', errors='replace')
deps.append(dep)
unique_deps = sorted(set(deps))
return unique_deps
def analyze_go_binary(filepath):
"""Full analysis of Go malware binary."""
with open(filepath, 'rb') as f:
data = f.read()
print(f"[+] Analyzing Go binary: {filepath}")
print(f" File size: {len(data):,} bytes")
print("=" * 60)
# Build info
find_go_build_info(data)
# pclntab
pclntab_offset, go_version = find_pclntab(data)
# Functions
functions = extract_function_names(data, pclntab_offset)
print(f"\n[+] Recovered {len(functions)} function names")
# Categorize functions
categories = {
"network": [], "crypto": [], "os_exec": [],
"file_io": [], "main": [], "third_party": [],
}
for f in functions:
if 'net/' in f or 'http' in f.lower():
categories["network"].append(f)
elif 'crypto' in f:
categories["crypto"].append(f)
elif 'os/exec' in f or 'syscall' in f:
categories["os_exec"].append(f)
elif 'os.' in f or 'io/' in f:
categories["file_io"].append(f)
elif f.startswith('main.'):
categories["main"].append(f)
elif 'github.com' in f or 'golang.org' in f:
categories["third_party"].append(f)
for cat, funcs in categories.items():
if funcs:
print(f"\n [{cat}] ({len(funcs)} functions):")
for fn in funcs[:10]:
print(f" {fn}")
# Dependencies
deps = extract_dependencies(data)
print(f"\n[+] Dependencies ({len(deps)}):")
for dep in deps[:20]:
print(f" {dep}")
# Suspicious strings
sus_strings = extract_go_strings(data)
print(f"\n[+] Suspicious strings ({len(sus_strings)}):")
for s in sus_strings[:20]:
print(f" {s}")
if __name__ == "__main__":
if len(sys.argv) < 2:
print(f"Usage: {sys.argv[0]} <go_binary>")
sys.exit(1)
analyze_go_binary(sys.argv[1])
Step 2: Ghidra Analysis Script
# Ghidra script (run within Ghidra's script manager)
# Save as AnalyzeGoBinary.py in Ghidra scripts directory
# @category MalwareAnalysis
# @description Analyze Go binary structure and recover metadata
def analyze_go_binary_ghidra():
"""Ghidra script for Go binary analysis."""
from ghidra.program.model.mem import MemoryAccessException
program = getCurrentProgram()
memory = program.getMemory()
listing = program.getListing()
print("[+] Go Binary Analysis Script")
print(f" Program: {program.getName()}")
# Find pclntab
pclntab_magics = [
bytes([0xf0, 0xff, 0xff, 0xff]), # Go 1.20+
bytes([0xf1, 0xff, 0xff, 0xff]), # Go 1.18-1.19
bytes([0xfa, 0xff, 0xff, 0xff]), # Go 1.16-1.17
bytes([0xfb, 0xff, 0xff, 0xff]), # Go 1.2-1.15
]
for magic in pclntab_magics:
addr = memory.findBytes(
program.getMinAddress(), magic, None, True, None
)
if addr:
print(f"[+] pclntab found at {addr}")
# Create label
program.getSymbolTable().createLabel(
addr, "go_pclntab", None,
ghidra.program.model.symbol.SourceType.ANALYSIS
)
break
# Fix Go string definitions
# Go strings are ptr+len, not null terminated
print("[+] Fixing Go string references...")
# Search for function names containing package paths
symbol_table = program.getSymbolTable()
func_count = 0
for symbol in symbol_table.getAllSymbols(True):
name = symbol.getName()
if ('.' in name and
any(pkg in name for pkg in
['main.', 'runtime.', 'net.', 'crypto.', 'os.'])):
func_count += 1
print(f"[+] Found {func_count} Go function symbols")
# Execute
analyze_go_binary_ghidra()
Validation Criteria
- Go version and build information extracted from binary
- pclntab located and parsed for function name recovery
- Third-party dependencies identified revealing malware capabilities
- Main package functions enumerated for targeted analysis
- Network, crypto, and OS exec functions categorized
- Ghidra analysis correctly labels Go runtime structures