Python: Penetration Testing for Developers
by: Andrew Mabbitt,Cameron Buchanan,Christopher Duffy,Mohit,Terry Ip
Pages: 891 pages
Edition 版本: 1
Language 语言: English
Publisher finelybook 出版社: Packt Publishing
Released: 2016-10-21
ISBN-10: B01M5FAV4Q
ISBN-13: 9781787128187
Contents
Module 1: Learning Penetration Testing with Python
Chapter 1: Understanding the Penetration Testing Methodology
Chapter 2: The Basics of Python Scripting
Chapter 3: Identifying Targets with Nmap,Scapy,and Python
Chapter 4: Executing Credential Attacks with Python
Chapter 5: Exploiting Services with Python
Chapter 6: Assessing Web Applications with Python
Chapter 7: Cracking the Perimeter with Python
Chapter 8: Exploit Development with Python,Metasploit,and Immunity
Chapter 9: Automating Reports and Tasks with Python
Chapter 10: Adding Permanency to Python Tools
Module 2: Python Penetration Testing Essentials
Chapter 1: Python with Penetration Testing and Networking
Chapter 2: Scanning Pentesting
Chapter 3: Sniffing and Penetration Testing
Chapter 4: Wireless Pentesting
Chapter 5: Foot Printing of a Web Server and a Web Application
Chapter 6: Client-side and DDoS Attacks
Chapter 7: Pentesting of SQLI and XSS
Module 3: Python Web Penetration Testing Cookbook
Chapter 1: Gathering Open Source Intelligence
Chapter 2: Enumeration
Chapter 3: Vulnerability Identification
Chapter 4: SQL Injection
Chapter 5: Web Header Manipulation
Chapter 6: Image Analysis and Manipulation
Chapter 7: Encryption and Encoding
Chapter 8: Payloads and Shells
Chapter 9: Reporting
Python: Penetration Testing for Developers
相关推荐
Natural Language Processing with Python Updated Edition: From Basics to Advanced Projects
Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
Python Network Programming: Conquer all your networking challenges with the powerful Python language
The Nature of Code: Simulating Natural Systems with JavaScript
AWS Certified Data Engineer Study Guide: Associate (DEA-C01) Exam
Safety Assurance under Uncertainties: From Software to Cyber-Physical/Machine Learning Systems