Defending Against Generative AI-Based Social Engineering

DON'T GET ENGINEEREDSocial engineering, such as phishing, is one of the biggest problems for corporations - and users - in terms of security. And the advent of generative AI. has just made it worse.

In the world of today, companies and individuals must be able to not only resist social engineering and phishing, but resist it when it leverages generative AI - which means faster, larger-scale, more sophisticated attacks. This course will teach you how to protect against social engineering, when social engineering is accelerated by generative AI. LET ME TELL YOU.

EVERYTHING. Some people - including me - love to know what they're getting in a package. And by this, I mean, EVERYTHING that is in the package.

So, here is a list of everything that this course covers:You'll learn the basics of generative AI and what it can do, including common models and families of models, the characteristics of generative content, and how it can be misused due to negligence or active malevolence (including biases, misinformation, impersonation and more);You'll learn the basics of social engineering and what it consists of (manipulating someone to access information you otherwise would not), including common approaches and the facts that enable it (social norms, weak OPSEC, etc);You'll learn the basics of social engineering with generative AI, including how it accelerates approaches (more sophisticated attacks, faster attacks, on larger scales, with micro-targeting), the major approaches that are affected (such as impersonation or more convincing pretexts), and the major defenses that are also affected (sophisticated detection mechanisms, MFA, behavioral analytics, faster IR, etc);You'll learn about an overview of the major generative content types used in social engineering attacks (text, image, audio and video), including the specific approaches that each leverage, the model training requirements and data required for attackers to train such models, and how each type can be detected;You'll learn about generative text, including the models that enable it (e. g. , LLMs), the usual distribution channels (messages, emails, social media profiles), the required data to train such models (text samples, including specific ones), and how it can be detected (inconsistencies in facts, spotting specific text styles and patterns, detecting emotional manipulation patterns);You'll learn about generative image, including the models that enable it (e.