AI and Reverse Engineering: Redefining Cybersecurity in a Digital Age

Reverse engineering has long been a cornerstone of cybersecurity, enabling professionals to deconstruct software, firmware,
and hardware to uncover their internal mechanisms. Traditionally, this process has been labor-intensive, requiring deep expertise
in assembly code, system architecture, and network protocols. However, the advent of artificial intelligence (AI) is revolutionizing
reverse engineering, making it faster, more efficient, and more accessible to a broader range of professionals.

“AI is not merely a tool but a transformative force in reverse engineering, unlocking capabilities previously inaccessible to many.”

This article explores how AI is reshaping reverse engineering, from automating decompilation to enhancing malware analysis.
We will also consider the ethical implications of these powerful tools, linking our discussion to other critical areas of cybersecurity research, such as discovering Insecure Direct Object Reference (IDOR) vulnerabilities.

The Role of AI in Automating Reverse Engineering

Reverse engineering is traditionally viewed as a complex and specialized discipline, requiring a combination of technical skill
and intuition. At its core, reverse engineering involves dissecting a system’s components to understand their functionality, typically
to identify vulnerabilities, comprehend proprietary software, or analyze malware. Historically, this process required meticulous examination of binary code and manual reconstruction into human-readable form.

AI fundamentally alters this narrative by automating many facets of reverse engineering. One of the most significant advancements
is in AI-powered decompilation. Research by IDC indicates that AI-driven tools can reduce the time required for decompilation
and binary analysis by up to 40%. Decompilation involves converting binary code back into a higher-level language,
such as....