Python tools for penetration testers

简介: NetworkScapy: send, sniff and dissect and forge network packets.

Network

  • Scapy: send, sniff and dissect and forge network packets. Usable interactively or as a library
  • pypcap, Pcapy and pylibpcap: several different Python bindings for libpcap
  • libdnet: low-level networking routines, including interface lookup and Ethernet frame transmission
  • dpkt: fast, simple packet creation/parsing, with definitions for the basic TCP/IP protocols
  • Impacket: craft and decode network packets. Includes support for higher-level protocols such as NMB and SMB
  • pynids: libnids wrapper offering sniffing, IP defragmentation, TCP stream reassembly and port scan detection
  • Dirtbags py-pcap: read pcap files without libpcap
  • flowgrep: grep through packet payloads using regular expressions
  • httplib2: comprehensive HTTP client library that supports many features left out of other HTTP libraries

Debugging and reverse engineering

  • Paimei: reverse engineering framework, includes PyDBG, PIDA, pGRAPH
  • Immunity Debugger: scriptable GUI and command line debugger
  • IDAPython: IDA Pro plugin that integrates the Python programming language, allowing scripts to run in IDA Pro
  • PyEMU: fully scriptable IA-32 emulator, useful for malware analysis
  • pefile: read and work with Portable Executable (aka PE) files
  • pydasm: Python interface to the libdasm x86 disassembling library
  • PyDbgEng: Python wrapper for the Microsoft Windows Debugging Engine
  • uhooker: intercept calls to API calls inside DLLs, and also arbitrary addresses within the executable file in memory
  • diStorm64: disassembler library for AMD64, licensed under the BSD license
  • python-ptrace: debugger using ptrace (Linux, BSD and Darwin system call to trace processes) written in Python

Fuzzing

  • Sulley: fuzzer development and fuzz testing framework consisting of multiple extensible components
  • Peach Fuzzing Platform: extensible fuzzing framework for generation and mutation based fuzzing
  • antiparser: fuzz testing and fault injection API
  • TAOF, including ProxyFuzz, a man-in-the-middle non-deterministic network fuzzer
  • untidy: general purpose XML fuzzer
  • Powerfuzzer: highly automated and fully customizable web fuzzer (HTTP protocol based application fuzzer)
  • FileP: file fuzzer. Generates mutated files from a list of source files and feeds them to an external program in batches
  • SMUDGE
  • Mistress: probe file formats on the fly and protocols with malformed data, based on pre-defined patterns
  • Fuzzbox: multi-codec media fuzzer
  • Forensic Fuzzing Tools: generate fuzzed files, fuzzed file systems, and file systems containing fuzzed files in order to test the robustness of forensics tools and examination systems
  • Windows IPC Fuzzing Tools: tools used to fuzz applications that use Windows Interprocess Communication mechanisms
  • WSBang: perform automated security testing of SOAP based web services
  • Construct: library for parsing and building of data structures (binary or textual). Define your data structures in a declarative manner
  • fuzzer.py (feliam): simple fuzzer by Felipe Andres anzano

Web

  • ProxMon: processes proxy logs and reports discovered issues
  • WSMap: find web service endpoints and discovery files
  • Twill: browse the Web from a command-line interface. Supports automated Web testing
  • Windmill: web testing tool designed to let you painlessly automate and debug your web application
  • FunkLoad: functional and load web tester

Forensics

  • Volatility: extract digital artifacts from volatile memory (RAM) samples
  • SandMan: read the hibernation file, regardless of Windows version
  • LibForensics: library for developing digital forensics applications
  • TrIDLib, identify file types from their binary signatures. Now includes Python binding

Malware analysis

  • pyew: command line hexadecimal editor and disassembler, mainly to analyze malware
  • Didier Stevens' PDF tools: analyse, identify and create PDF files (includes PDFiD, pdf-parser and make-pdf and mPDF)
  • Origapy: Python wrapper for the Origami Ruby module which sanitizes PDF files
  • Exefilter: filter file formats in e-mails, web pages or files. Detects many common file formats and can remove active content
  • pyClamAV: add virus detection capabilities to your Python software

Misc

  • InlineEgg: toolbox of classes for writing small assembly programs in Python
  • Exomind: framework for building decorated graphs and developing open-source intelligence modules and ideas, centered on social network services, search engines and instant messaging
  • RevHosts: enumerate virtual hosts for a given IP address
  • simplejson: JSON encoder/decoder, e.g. to use Google's AJAX API

Other useful libraries and tools

  • IPython: enhanced interactive Python shell with many features for object introspection, system shell access, and its own special command system
  • Beautiful Soup: HTML parser optimized for screen-scraping
  • matplotlib: make 2D plots of arrays
  • Mayavi: 3D scientific data visualization and plotting
  • RTGraph3D: create dynamic graphs in 3D
  • Twisted: event-driven networking engine
  • Suds: lightweight SOAP client for consuming Web Services
  • M2Crypto: most complete OpenSSL wrapper
  • NetworkX: graph library (edges, nodes)
  • pyparsing: general parsing module
  • lxml: most feature-rich and easy-to-use library for working with XML and HTML in the Python language
  • Pexpect: control and automate other programs, similar to Don Libes `Expect` system
  • Sikuli, visual technology to search and automate GUIs using screenshots. Scriptable in Jython
目录
相关文章
|
3月前
|
分布式计算 MaxCompute 对象存储
关于 Mac OSX下运行Python程序调用tools库的问题,ModuleNotFoundError: No module named ‘Tools‘
关于 Mac OSX下运行Python程序调用tools库的问题,ModuleNotFoundError: No module named ‘Tools‘
|
人工智能 测试技术 程序员
书籍:Pro Python 3 3rd -2019: Features and Tools for Professional Development .pdf
简介 优化您的编程技巧和方法,以成为更高效和创造性的Python程序员。本书探讨了概念和功能,这些概念和功能不仅可以改进您的代码,还可以通过Python理念的见解和细节来理解Python社区。 Pro Python 3,第三版为您提供编写干净,创新代码的工具。
|
Web App开发 XML 数据格式
|
Python 传感器 并行计算
|
21天前
|
机器学习/深度学习 存储 设计模式
Python 高级编程与实战:深入理解性能优化与调试技巧
本文深入探讨了Python的性能优化与调试技巧,涵盖profiling、caching、Cython等优化工具,以及pdb、logging、assert等调试方法。通过实战项目,如优化斐波那契数列计算和调试Web应用,帮助读者掌握这些技术,提升编程效率。附有进一步学习资源,助力读者深入学习。
|
21天前
|
机器学习/深度学习 数据可视化 TensorFlow
Python 高级编程与实战:深入理解数据科学与机器学习
本文深入探讨了Python在数据科学与机器学习中的应用,介绍了pandas、numpy、matplotlib等数据科学工具,以及scikit-learn、tensorflow、keras等机器学习库。通过实战项目,如数据可视化和鸢尾花数据集分类,帮助读者掌握这些技术。最后提供了进一步学习资源,助力提升Python编程技能。
|
9天前
|
Python
[oeasy]python074_ai辅助编程_水果程序_fruits_apple_banana_加法_python之禅
本文回顾了从模块导入变量和函数的方法,并通过一个求和程序实例,讲解了Python中输入处理、类型转换及异常处理的应用。重点分析了“明了胜于晦涩”(Explicit is better than implicit)的Python之禅理念,强调代码应清晰明确。最后总结了加法运算程序的实现过程,并预告后续内容将深入探讨变量类型的隐式与显式问题。附有相关资源链接供进一步学习。
23 4
|
21天前
|
设计模式 机器学习/深度学习 前端开发
Python 高级编程与实战:深入理解设计模式与软件架构
本文深入探讨了Python中的设计模式与软件架构,涵盖单例、工厂、观察者模式及MVC、微服务架构,并通过实战项目如插件系统和Web应用帮助读者掌握这些技术。文章提供了代码示例,便于理解和实践。最后推荐了进一步学习的资源,助力提升Python编程技能。