analyzing-golang-malware-with-ghidra

Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.

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Install Skill

Run in your terminal

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-golang-malware-with-ghidra

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Installation Guide

How to use analyzing-golang-malware-with-ghidra on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add analyzing-golang-malware-with-ghidra
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-golang-malware-with-ghidra

Fetches analyzing-golang-malware-with-ghidra from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
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4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/analyzing-golang-malware-with-ghidra

Restart Cursor to activate analyzing-golang-malware-with-ghidra. Access via /analyzing-golang-malware-with-ghidra in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

name
analyzing-golang-malware-with-ghidra
description
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
domain
cybersecurity
subdomain
malware-analysis
tags
- golang - ghidra - reverse-engineering - malware-analysis - binary-analysis - go-malware - disassembly
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- DE.AE-02 - RS.AN-03 - ID.RA-01 - DE.CM-01

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.

When to Use

  • When investigating security incidents that require analyzing golang malware with ghidra
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

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.

Workflow

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

References

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.828 reviews
  • H
    Hiroshi NdlovuDec 20, 2024

    analyzing-golang-malware-with-ghidra is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • N
    Nikhil RaoDec 16, 2024

    Useful defaults in analyzing-golang-malware-with-ghidra — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Y
    Yusuf MartinezNov 11, 2024

    analyzing-golang-malware-with-ghidra reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • A
    Anaya BansalNov 7, 2024

    I recommend analyzing-golang-malware-with-ghidra for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Y
    Yusuf RobinsonOct 26, 2024

    analyzing-golang-malware-with-ghidra reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • A
    Anaya AgarwalOct 2, 2024

    I recommend analyzing-golang-malware-with-ghidra for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • T
    Tariq SmithSep 9, 2024

    Solid pick for teams standardizing on skills: analyzing-golang-malware-with-ghidra is focused, and the summary matches what you get after install.

  • S
    Sakshi PatilSep 5, 2024

    Keeps context tight: analyzing-golang-malware-with-ghidra is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • R
    Rahul SantraSep 1, 2024

    analyzing-golang-malware-with-ghidra fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • M
    Michael PatelAug 28, 2024

    We added analyzing-golang-malware-with-ghidra from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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