How Generative AI Can Enhance Cybersecurity

Introduction

The digital landscape is rapidly evolving, with the increasing complexity and interconnectivity of systems posing significant cybersecurity challenges. To stay ahead of the game, organizations must adopt innovative solutions that leverage the latest technologies, including generative AI.

Static Application Security Testing (SAST)

SAST tools are widely used for identifying vulnerabilities in software code. However, they often produce a high number of false positives, which can be time-consuming and resource-intensive to resolve. This is due to several reasons, including:

• Lack of real data: Most SAST tools rely on patterns and signatures, which can be incomplete or outdated.
• Limited support for programming languages: SAST tools may not be able to analyze code written in emerging languages or those with unique syntax.
• Unkurated solutions: SAST tools often lack the ability to adapt to changing coding practices and security guidelines.

To address these challenges, many organizations are integrating generative AI into their SAST processes. This enables SAST tools to:

• Develop company-specific rules and secret detection
• Support additional programming languages with minimal effort
• Gain insights from all installed KI models, without analyzing proprietary code

Dynamic Application Security Testing (DAST)

DAST tools simulate real-world attacks on an application, identifying vulnerabilities and weaknesses. However, they often lack the ability to learn and adapt to changing attack patterns and techniques.

• DAST tools can learn from their mistakes and improve over time
• Develop the ability to bypass CAPTCHAs and firewalls
• Reduce noise by eliminating impossible test cases and adapting to the environment
• Generate diagrams and data points for management to analyze the financial impact of frequent vulnerabilities

Red Teaming

Red Teaming is a dynamic and comprehensive approach to assessing and optimizing an organization’s cybersecurity. It involves simulating sophisticated cyber attacks and mimicking the tactics, techniques, and procedures (TTPs) used by cybercriminals.

• Identify vulnerabilities and weaknesses
• Exploit these vulnerabilities to demonstrate the most severe scenarios

Red Team assessments also include activities that fall outside traditional security assessments, such as phishing, DDoS, session takeovers, and client-side attacks. In combination with generative AI, Red Team tools will be able to bypass anti-malware and antivirus solutions more easily.

Reverse Engineering

Reverse Engineering involves disassembling and decompiling executable code to extract information about the source code, data structures, and algorithms. This process is used for various purposes, including:

• Understanding legacy systems better
• Ensuring interoperability between different software components
• Identifying vulnerabilities
• Recognizing malicious behavior

Most Reverse Engineering tools are free, but they are often simple and lack advanced features. The main challenge is that each application has a unique architecture and codebase, making it difficult to create a universal rule.

Generative AI can accelerate the discovery process, reveal hidden insights, and improve the ability to reconstruct complex systems. KI-gestützte SAST and DAST tools can also support Reverse Engineers in automatically identifying functions, variables, and control flow within binary code.