Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add killvxk/cybersecurity-skills-zh --skill analyzing-golang-malware-with-ghidragit clone --depth 1 https://github.com/killvxk/cybersecurity-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-golang-malware-with-ghidra)<a href="https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-golang-malware-with-ghidra"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-golang-malware-with-ghidra/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-golang-malware-with-ghidra"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-golang-malware-with-ghidra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.02888 |
| Opus 5 | $0.00028 | $0.01444 |
| Sonnet 5 | $0.00011 | $0.00578 |
| Haiku 4.5 | $0.00006 | $0.00289 |
Grade A, and why
analyzing-golang-malware-with-ghidra scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.
使用 Ghidra 分析 Golang 恶意软件
概述
Go(Golang)因其跨平台编译能力、生成自包含二进制文件的静态链接以及逆向工程的复杂性,成为恶意软件作者的热门语言。Go 二进制文件包含整个运行时、标准库和所有依赖项的静态链接,产生大型二进制文件(通常 5-15MB),包含数千个函数。Ghidra 在处理 Go 特有的字符串格式(非空终止符)、去符号的函数名和 goroutine 并发模式时存在困难。Volexity 开发的 GoResolver 等专用工具使用控制流图相似性在去符号或混淆的 Go 二进制文件中自动去混淆并恢复函数名。
前置条件
- Ghidra 11.0+,配合 JDK 17+
- GoResolver 插件(用于函数名恢复)
- Go 逆向工程工具包(go-re.tk)
- Python 3.9+(用于辅助脚本)
- 了解 Go 运行时内部机制(goroutine、channel、interface)
- 熟悉 Go 二进制文件结构(pclntab、moduledata、itab)
核心概念
Go 二进制文件结构
Go 二进制文件在 pclntab(PC 行表)结构中嵌入了丰富的元数据,将程序计数器映射到函数名、源文件和行号。即使去符号表的二进制文件也保留此元数据。moduledata 结构包含指向类型信息、itab(接口表)和 pclntab 本身的指针。Go 字符串以指针-长度对的形式存储,而非以空字符结尾的 C 字符串。
去符号表二进制文件中的函数恢复
尽管去除了符号表,Go 二进制文件仍在 pclntab 中保留函数名。然而,garble 等混淆工具会将函数重命名为随机字符串。GoResolver 通过计算混淆函数的控制流图签名,并与已知 Go 标准库和第三方包函数的数据库进行匹配来解决此问题。
包/依赖项提取
Go 的依赖管理将模块路径和版本字符串嵌入二进制文件。提取这些信息可揭示恶意软件的第三方依赖(HTTP 库、加密包、C2 框架),在不进行完整逆向工程的情况下了解其能力。
实操步骤
步骤 1:初始二进制分析
#!/usr/bin/env python3
"""分析 Go 二进制文件元数据用于恶意软件分析。"""
import struct
import sys
import re
def find_go_build_info(data):
"""从二进制文件提取 Go 构建信息。"""
# Go buildinfo 魔数:\xff Go buildinf:
magic = b'\xff Go buildinf:'
offset = data.find(magic)
if offset == -1:
return None
print(f"[+] Go 构建信息位于偏移 0x{offset:x}")
# 提取附近的 Go 版本字符串
go_version = re.search(rb'go\d+\.\d+(?:\.\d+)?', data[offset:offset+256])
if go_version:
print(f" Go 版本:{go_version.group().decode()}")
return offset
def find_pclntab(data):
"""定位 pclntab(PC 行表)结构。"""
# pclntab 魔数字节随 Go 版本而变化
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 位于 0x{offset:x}({version})")
return offset, version
return None, None
def extract_function_names(data, pclntab_offset):
"""从 pclntab 提取函数名。"""
if pclntab_offset is None:
return []
functions = []
# 函数名字符串遵循特定模式
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):
"""提取 Go 风格字符串(指针+长度对)。"""
# Go 字符串不以空字符结尾;提取可读序列
strings = []
ascii_pattern = re.compile(rb'[\x20-\x7e]{10,}')
for match in ascii_pattern.finditer(data):
s = match.group().decode('ascii')
# 过滤出有趣的恶意软件字符串
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):
"""从二进制文件提取 Go 模块依赖项。"""
deps = []
# 模块路径遵循模式: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):
"""对 Go 恶意软件二进制文件进行完整分析。"""
with open(filepath, 'rb') as f:
data = f.read()
print(f"[+] 正在分析 Go 二进制文件:{filepath}")
print(f" 文件大小:{len(data):,} 字节")
print("=" * 60)
# 构建信息
find_go_build_info(data)
# pclntab
pclntab_offset, go_version = find_pclntab(data)
# 函数
functions = extract_function_names(data, pclntab_offset)
print(f"\n[+] 恢复了 {len(functions)} 个函数名")
# 分类函数
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)} 个函数):")
for fn in funcs[:10]:
print(f" {fn}")
# 依赖项
deps = extract_dependencies(data)
print(f"\n[+] 依赖项({len(deps)} 个):")
for dep in deps[:20]:
print(f" {dep}")
# 可疑字符串
sus_strings = extract_go_strings(data)
print(f"\n[+] 可疑字符串({len(sus_strings)} 个):")
for s in sus_strings[:20]:
print(f" {s}")
if __name__ == "__main__":
if len(sys.argv) < 2:
print(f"用法:{sys.argv[0]} <go_binary>")
sys.exit(1)
analyze_go_binary(sys.argv[1])
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 291 lines · 56 tokens per session scan A 7d0fc8252baf
analyzing-golang-malware-with-ghidra is a skill published in the GitHub repository killvxk/cybersecurity-skills-zh (45 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 2,888 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware in Ghidra by parsing Go buildinfo and pclntab structures, recovering stripped/obfuscated function names (e.g. via GoResolver), and extracting embedded module/dependency strings and types from Go binaries. Use when analyzing a Go-language malware sample, deobfuscating a…
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.
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.
analyzing-golang-malware-with-ghidra
Use when reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries. Use when reverseing engineer go-compiled malware using ghidra with specialized scripts for.
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.
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.