How AI Is Transforming Offensive Security: Benefits, Limitations & Trends

Offensive Security Academy is an educational blog series on offensive security tactics and techniques in the age of AI.

AI is dramatically altering how offensive security testing is conducted, as well as what it tests. AI has become another attack surface for almost all organizations and needs to be tested as such. At the same time, AI automation in security offense is allowing teams to test more systems, faster, and at significantly less cost.

Key takeaways

• Offensive security simulates attacks to discover vulnerabilities, while defensive security shores up assets and systems.

• AI is impacting both what offensive security tests and how it operates.

• Speed, scale, and cost are the primary impacts of AI-based offensive security testing.

• AI is limited in offensive security tactics by its inability to apply business context and logic, understand human behavior, and to identify complex, chained attacks.

• XBOW offers human-level offensive security at machine speed.

What is offensive security?

Offensive security is a security tactic designed to emulate and anticipate attacker tactics. For instance, in a controlled environment, a team could attempt to find and exploit vulnerabilities in an application. Through this exercise, they will understand if the app is vulnerable and address any vulnerabilities before an attacker finds them.

Offensive vs. defensive security

Offensive security is about thinking like attackers and trying to mimic their strategies in order to identify and thwart them proactively. Defensive security is about shoring up assets and systems with measures like firewalls or vulnerability scanning. While offensive security is like trying to break into your house to see where it might be vulnerable, defensive security is like installing an alarm system. 

Types of offensive security

A few popular offensive security tactics in cybersecurity include penetration testing, red teaming, and social engineering testing.

Penetration testing

In traditional penetration testing, or pentesting, ethical hackers attempt to breach parts of a computer system, such as the network, applications, or APIs. They perform reconnaissance, attempt to exploit any vulnerabilities they find, then document their findings to help an organization shore up its defenses.

Although highly effective and trusted, this type of penetration testing is also time-consuming and expensive. AI-driven pen testing is emerging to address these shortcomings.

Red teaming

Red teaming is similar to penetration testing, but its scope is more broad. In a red-teaming exercise, the team attempts to breach an organization in multiple ways, from trying to physically break in to exploiting software vulnerabilities to looking for flaws in an incident response plan.

Social engineering testing

Social engineering testing is a specific type of offensive security designed to test whether the employees at an organization are aware of and prepared to respond to threats. For example, a social engineering test could involve sending out a mock phishing email, analyzing how employees respond, and then conducting training sessions to better prepare employees to respond to real phishing emails.

How AI impacts offensive security

As with all areas of cybersecurity, AI is increasingly playing a role in offensive security. Although many offensive security tactics have traditionally been human-led, AI is becoming a force multiplier for offensive security, making it more efficient and effective.

In addition, AI systems are now another attack surface organizations need to test offensively.

Testing generative AI in offensive security

Offensive security tactics like pen testing and red teaming now often include AI systems and simulate attacks like prompt injection and data poisoning. AI threat modeling is also an emerging best practice to help teams understand where, how, and how securely AI is in use in their organizations.

Benefits of leveraging AI in offensive security

Speed, scale, and cost savings are the key benefits of AI in most areas of life, and cybersecurity is no exception. In AI offensive security, AI greatly expands what can be tested and how fast, while giving humans the time and space to focus on what they do best.

Cost savings from AI in offensive security

Less manual, less human-led work always yields less cost. For instance, traditional, human-led penetration testing takes months and costs in the range of $10K to $30K per test. With AI-based vulnerability discovery, a pen test can be conducted and documented in days for less than $10K.

Scale and speed improvements from AI in offensive security

Human-led testing could never match the scale and speed of AI. For example, an AI-led pen test can quickly and easily scale to cover large, complex environments and be be run continually. Manual pen tests are one-off projects that capture a point-in-time that is soon obsolete in fast-moving organizations.

Similarly, AI-powered red teaming generates AI cyberattack simulations and automated attack strategies and leverages AI to map attack surfaces, while social engineering tests feature AI-generated phishing emails, results analysis, and documentation.

In all cases, AI does more tasks faster than humans could, while freeing the humans from manual tasks and giving them more time to do strategic, creative tasks. It also saves organizations significant time and money when they can do the same or more testing without adding staff.

Limitations of AI in offensive security

Human creativity, expertise, knowledge, and judgement play, and will continue to play, critical roles in offensive security.

AI needs human guidance to apply business context and logic or interpret some human reactions in offensive security activities. For instance, some social engineering tests require a nuanced understanding of human emotions and behavior, which AI struggles with. In pen testing, there are some complex attack patterns, such as those that chain together a series of vulnerabilities, that AI can’t identify independently.

AI won’t replace humans in offensive security, but it will allow them to do more with less.

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