An open-source penetration testing framework for social engineering with custom attack vectors to create believable attacks quickly.
The Social-Engineer Toolkit (SET) is an open-source penetration testing framework designed for social engineering. It provides security professionals with custom attack vectors to simulate realistic social engineering attacks, such as phishing and credential harvesting, in controlled testing environments. The tool helps organizations assess their security posture and train employees against social engineering threats.
Security professionals, penetration testers, and ethical hackers who conduct authorized security assessments and social engineering simulations. It is also used by organizations for security awareness training and red team exercises.
Developers choose SET for its specialized focus on social engineering, pre-built attack modules that save time, and its reputation as a trusted tool from a professional security firm. Its open-source nature and comprehensive documentation make it accessible for both learning and professional use in ethical security testing.
The Social-Engineer Toolkit (SET) repository from TrustedSec - All new versions of SET will be deployed here.
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SET offers pre-built modules for phishing and credential harvesting, providing targeted tools that save time in simulating realistic attacks, as emphasized in its description.
The toolkit allows quick creation of believable attack scenarios, enabling security professionals to efficiently conduct simulations, as highlighted in the README for testing purposes.
Includes a detailed user manual (PDF) that guides users on usage and best practices, making it accessible for both learning and professional ethical testing.
Developed by TrustedSec, a professional security firm, SET emphasizes ethical use with strict consent requirements, providing transparency through its open-source code.
Mac OS X support is experimental, and Windows requires WSL/Kali Linux, making it less accessible for users on native platforms without additional setup.
Setup involves pip, virtual environments on Mac M2, and manual steps like 'python3 setup.py', which can be error-prone for those unfamiliar with Python toolchains.
Focused solely on social engineering, it lacks built-in tools for broader penetration testing, such as automated reporting or network scanning, requiring complementary frameworks.