实例探究Python以并发方式编写高性能端口扫描器的方法
关于端口扫描器
端口扫描工具(Port Scanner)指用于探测服务器或主机开放端口情况的工具。常被计算机管理员用于确认安全策略,同时被攻击者用于识别目标主机上的可运作的网络服务。
端口扫描定义是客户端向一定范围的服务器端口发送对应请求,以此确认可使用的端口。虽然其本身并不是恶意的网络活动,但也是网络攻击者探测目标主机服务,以利用该服务的已知漏洞的重要手段。端口扫描的主要用途仍然只是确认远程机器某个服务的可用性。
扫描多个主机以获取特定的某个端口被称为端口清扫(Portsweep),以此获取特定的服务。例如,基于SQL服务的计算机蠕虫就会清扫大量主机的同一端口以在 1433 端口上建立TCP连接。
Python实现
端口扫描器原理很简单,无非就是操作socket,能connect就认定这个端口开放着。
import socket def scan(port): s = socket.socket() if s.connect_ex(('localhost', port)) == 0: print port, 'open' s.close() if __name__ == '__main__': map(scan,range(1,65536))
这样一个最简单的端口扫描器出来了。
等等喂,半天都没反应,那是因为socket是阻塞的,每次连接要等很久才超时。
我们自己给它加上的超时。
s.settimeout(0.1)
再跑一遍,感觉快多了。
多线程版本
import socket import threading def scan(port): s = socket.socket() s.settimeout(0.1) if s.connect_ex(('localhost', port)) == 0: print port, 'open' s.close() if __name__ == '__main__': threads = [threading.Thread(target=scan, args=(i,)) for i in xrange(1,65536)] map(lambda x:x.start(),threads)
运行一下,哇,好快,快到抛出错误了。thread.error: can't start new thread。
想一下,这个进程开启了65535个线程,有两种可能,一种是超过最大线程数了,一种是超过最大socket句柄数了。在linux可以通过ulimit来修改。
如果不修改最大限制,怎么用多线程不报错呢?
加个queue,变成生产者-消费者模式,开固定线程。
多线程+队列版本
import socket import threading from Queue import Queue def scan(port): s = socket.socket() s.settimeout(0.1) if s.connect_ex(('localhost', port)) == 0: print port, 'open' s.close() def worker(): while not q.empty(): port = q.get() try: scan(port) finally: q.task_done() if __name__ == '__main__': q = Queue() map(q.put,xrange(1,65535)) threads = [threading.Thread(target=worker) for i in xrange(500)] map(lambda x:x.start(),threads) q.join()
这里开500个线程,不停的从队列取任务来做。
multiprocessing+队列版本
总不能开65535个进程吧?还是用生产者消费者模式
import multiprocessing def scan(port): s = socket.socket() s.settimeout(0.1) if s.connect_ex(('localhost', port)) == 0: print port, 'open' s.close() def worker(q): while not q.empty(): port = q.get() try: scan(port) finally: q.task_done() if __name__ == '__main__': q = multiprocessing.JoinableQueue() map(q.put,xrange(1,65535)) jobs = [multiprocessing.Process(target=worker, args=(q,)) for i in xrange(100)] map(lambda x:x.start(),jobs)
注意这里把队列作为一个参数传入到worker中去,因为是process safe的queue,不然会报错。
还有用的是JoinableQueue(),顾名思义就是可以join()的。
gevent的spawn版本
from gevent import monkey; monkey.patch_all(); import gevent import socket ... if __name__ == '__main__': threads = [gevent.spawn(scan, i) for i in xrange(1,65536)] gevent.joinall(threads)
注意monkey patch必须在被patch的东西之前import,不然会Exception KeyError.比如不能先import threading,再monkey patch.
gevent的Pool版本
from gevent import monkey; monkey.patch_all(); import socket from gevent.pool import Pool ... if __name__ == '__main__': pool = Pool(500) pool.map(scan,xrange(1,65536)) pool.join()
concurrent.futures版本
import socket from Queue import Queue from concurrent.futures import ThreadPoolExecutor ... if __name__ == '__main__': q = Queue() map(q.put,xrange(1,65536)) with ThreadPoolExecutor(max_workers=500) as executor: for i in range(500): executor.submit(worker,q)

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

VS Code is available on Mac. It has powerful extensions, Git integration, terminal and debugger, and also offers a wealth of setup options. However, for particularly large projects or highly professional development, VS Code may have performance or functional limitations.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.
