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Agent Skill · 研究检索

ctf-malware(CTF 恶意软件)

ctf-malware 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ctf-malware 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 66,577。

总安装 261周安装 11GitHub Stars 1下载 92核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ctf-malware(CTF 恶意软件)
来源仓库:https://github.com/ramzxy/ctf
仓库路径:skills/ctf-malware
安装命令:
npx skills add https://github.com/ramzxy/ctf --skill ctf-malware
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ramzxy/ctf --skill ctf-malware

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

ctf-malware 用于查找、检索和筛选与 CTF 恶意软件相关的信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。安装前需确认权限范围和维护状态,注意可能触发联网或文件操作。

建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/ctf-malware

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ramzxy/ctf --skill ctf-malware;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ctf-malware 怎么安装?

在终端执行 npx skills add https://github.com/ramzxy/ctf --skill ctf-malware。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ctf-malware 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ctf-malware 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

ctf-malware 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ctf-malware 用的人多吗?

公开数据是累计安装 261 次,近一周安装 11 次,下载 92 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ctf-malware 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ctf-malware

CTF 恶意软件 · 本页

2611接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

CTF Malware & Network Analysis

Obfuscated Scripts

  • Replace eval/bash with echo to print underlying code
  • Extract base64/hex blobs and analyze with file
  • Common deobfuscation chain: base64 decode → gzip decode → reverse → base64 decode

Debian Package Analysis

ar -x package.deb           # Unpack debian package
tar -xf control.tar.xz      # Check control files
# Look for postinst scripts that execute payloads

Custom Crypto Protocols

  • Stream ciphers may share keystream state for both directions
  • Concatenate ALL payloads chronologically before decryption
  • Look for hardcoded keys in .rodata
  • ChaCha20 keystream extraction: Send large nullbytes payload (0 XOR anything = anything)
  • Alternative: Pipe ciphertext from pcap directly into the binary

PCAP Analysis

tshark -r file.pcap -Y "tcp.stream eq X" -T fields -e tcp.payload

Look for C2 communication patterns on unusual ports (e.g., port 21 not for FTP).

Hex-Encoded Payloads

  • Convert hex to bytes, try common transformations: subtract 1, XOR with key

JavaScript Deobfuscation

// Replace eval with console.log
eval = console.log;
// Then run the obfuscated code

// Common patterns
unescape()           // URL decoding
String.fromCharCode() // Char codes
atob()               // Base64

PowerShell Analysis

# Common obfuscation
-enc / -EncodedCommand  # Base64 encoded
IEX / Invoke-Expression # Eval equivalent
[System.Text.Encoding]::Unicode.GetString([System.Convert]::FromBase64String($encoded))

PE Analysis

peframe malware.exe      # Quick triage
pe-sieve                 # Runtime analysis
pestudio                 # Static analysis (Windows)

Sandbox Evasion Checks

Look for:

  • VM detection (VMware, VirtualBox artifacts)
  • Debugger detection (IsDebuggerPresent)
  • Timing checks (sleep acceleration)
  • Environment checks (username, computername)
  • File/registry checks for analysis tools

Network Indicators

# Extract IPs/domains
strings malware | grep -E '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
strings malware | grep -E '[a-zA-Z0-9.-]+\.(com|net|org|io)'

# DNS queries
tshark -r capture.pcap -Y "dns.qry.name" -T fields -e dns.qry.name | sort -u

C2 Traffic Patterns

  • Beaconing: regular intervals
  • Domain generation algorithms (DGA)
  • Encoded/encrypted payloads
  • HTTP(S) with custom headers
  • DNS tunneling

Junk Code Detection

Pattern: Obfuscation adds meaningless instructions around real code

Identification:

  • NOP sleds, push/pop pairs that cancel
  • Arithmetic that results in zero/identity
  • Dead writes (register written but never read before next write)
  • Unconditional jumps to next instruction

Filtering technique:

# Identify real calls by looking for patterns
# junk, junk, junk, CALL target, junk, junk
# Extract call targets, ignore surrounding noise

def extract_real_calls(disassembly):
    calls = []
    for instr in disassembly:
        if instr.mnemonic == 'call' and not is_junk_target(instr.operand):
            calls.append(instr)
    return calls

.NET DNS-based C2

Pattern: Deobfuscated.NET malware with DNS C2

Analysis with dnSpy:

  1. Find network functions (TcpClient, DnsClient, etc.)
  2. Identify encoding/encryption wrappers
  3. Look for command dispatch (switch on opcode)

AsmResolver for programmatic analysis:

using AsmResolver.DotNet;
var module = ModuleDefinition.FromFile("malware.dll");
foreach (var type in module.GetAllTypes()) {
    foreach (var method in type.Methods) {
        // Analyze method body
    }
}

AES-CBC in Malware

Common key derivation:

  • MD5/SHA256 of hardcoded string
  • Derived from timestamp or PID
  • Password-based (PBKDF2)

Analysis approach:

from Crypto.Cipher import AES
from Crypto.Util.Padding import unpad
import hashlib

# Common pattern: key = MD5(password)
password = b"hardcoded_password"
key = hashlib.md5(password).digest()

# IV often first 16 bytes of ciphertext
iv = ciphertext[:16]
ct = ciphertext[16:]

cipher = AES.new(key, AES.MODE_CBC, iv)
plaintext = unpad(cipher.decrypt(ct), 16)

Password Rotation in C2

Pattern: C2 uses rotating passwords based on time/sequence

Analysis:

  1. Find password generation function
  2. Identify rotation trigger (time-based, message count)
  3. Sync your decryptor with the rotation
def get_current_password(timestamp):
    # Password changes every hour
    hour_bucket = timestamp // 3600
    return hashlib.sha256(f"seed_{hour_bucket}".encode()).digest()

Malware Configuration Extraction

Common storage locations:

  • .data section (hardcoded)
  • Resources (PE resources,.NET resources)
  • Registry keys written at install
  • Encrypted config file dropped to disk

Extraction tools:

# PE resources
wrestool -x -t 10 malware.exe -o config.bin

# .NET resources
monodis --mresources malware.exe

# Strings in .rdata/.data
objdump -s -j .rdata malware.exe

Identifying Encryption Algorithms

By constants:

  • AES: 0x637c777b, 0x63636363 (S-box)
  • ChaCha20: expand 32-byte k or 0x61707865
  • RC4: Sequential S-box initialization
  • TEA/XTEA: 0x9E3779B9 (golden ratio)

By structure:

  • Block cipher: Fixed-size blocks, padding
  • Stream cipher: Byte-by-byte, no padding
  • Hash: Mixing functions, rounds, constants

.NET Malware Analysis (C2 Extraction)

Tools: ILSpy, dnSpy, dotPeek

LimeRAT C2 extraction (Whisper Of The Pain):

  1. Open.NET binary in dnSpy
  2. Find configuration class with Base64 encoded string
  3. Identify decryption method (typically AES-256-ECB with derived key)
  4. Key derivation: MD5 of hardcoded string → first 15 + full 16 bytes + null = 32-byte key
  5. Decrypt: Base64 decode → AES-ECB decrypt → reveals C2 IP/domain
from Crypto.Cipher import AES
import hashlib, base64

key_source = '${8\',`d0}n,~@J;oZ"9a'
md5 = hashlib.md5(key_source.encode()).hexdigest()
# Key = md5[:30] + md5 + '\x00' (32 bytes total as hex → 16 bytes binary)
key = bytes.fromhex(md5[:30] + md5 + '00')[:32]

cipher = AES.new(key, AES.MODE_ECB)
plaintext = cipher.decrypt(base64.b64decode(encrypted_b64))

Telegram Bot API for Evidence Recovery

Pattern (Stomaker): Malware uses Telegram bot to exfiltrate stolen data.

Recover exfiltrated data via bot token:

# If you have the bot API token from malware source:
import requests

TOKEN = "bot_token_here"
# Get updates (message history)
r = requests.get(f"https://api.telegram.org/bot{TOKEN}/getUpdates")
# Download files sent to bot
file_id = "..."
r = requests.get(f"https://api.telegram.org/bot{TOKEN}/getFile?file_id={file_id}")
file_path = r.json()['result']['file_path']
requests.get(f"https://api.telegram.org/file/bot{TOKEN}/{file_path}")

RC4-Encrypted WebSocket C2 Traffic

Pattern (Tampered Seal): Malware uses WSS over non-standard port with RC4 encryption.

Decryption workflow:

  1. Identify C2 port from malware source (not standard 443)
  2. Remap port with tcprewrite so Wireshark decodes TLS
  3. Add RSA key for TLS decryption → reveals WebSocket frames
  4. Find RC4 key hardcoded in malware binary
  5. Decrypt each WebSocket payload with RC4 via CyberChef

Malware communication patterns:

  • Registration message: hostname, OS, username, privileges
  • Exfiltration: screenshots, keylog data, file contents
  • Commands: reverse shell, file download, process list

PyInstaller + PyArmor Unpacking

# Step 1: Extract PyInstaller archive
python pyinstxtractor.py malware.exe
# Look for main .pyc file in extracted directory

# Step 2: If PyArmor-protected, use unpacker
# github.com/Svenskithesource/PyArmor-Unpacker
# Three methods available; choose based on PyArmor version

# Step 3: Clean up deobfuscated source
# Remove fake/dead-code functions (confusion code)
# Identify core encryption/exfiltration logic

平台分布

Codex

39.16%
按下载量换算36

Claude

29.42%
按下载量换算27

Cursor

20.35%
按下载量换算19

Gemini CLI

8.75%
按下载量换算8

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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