Can an AI Pentest Replace Human Pentesters?

Pentesting is the most accurate and trusted form of security assessment. It’s also one of the most time-consuming and expensive. As the threat landscape becomes more dynamic, that pace and cost become more problematic. AI-based pentesting has emerged to fill the gap. But in AI assisted vs. traditional pentesting, can AI truly match the quality of a human pentester?

Key takeaways

• Pentesting delivers the most high-quality security testing results. But it’s also time-consuming, making it less effective in fast-moving environments.
• AI pentesting acts like a force multiplier for this powerful offensive security tool, increasing its pace and scope.
• AI pentesting won’t replace human pentesters, but will allow them to focus on more complex attacks.

What is manual penetration testing?

In manual penetration testing, a skilled security professional attempts to think and act as a cyberattacker would to breach a system or application accordingly. With the data unearthed from this type of testing, organizations have a clear and accurate picture of where they have truly exploitable, not just theoretical, vulnerabilities.

Pros and cons of manual penetration testing

Manual penetration testing is considered the gold standard for security assessment. Nothing compares to an experienced and skilled human exploring and testing your system. Humans have a unique ability to apply creativity, context, and an understanding of business logic to their investigation and conclusions.This type of testing delivers highly accurate testing results that reveal real, proven attack paths, not just patterns of known vulnerabilities that may or may not pose a true business risk.

The downside of manual penetration testing is its time and expense burden. Manual penetration testing is so accurate and effective that most organizations would do it around the clock, across their entire attack surface, if they could. But these tests are expensive and take months to conduct. With AI boosting both software development and cyberattacks and creating a fast-moving and fluid attack surface, a test that is conducted once or twice a year will leave coverage gaps.

What is AI pentesting?

AI pentesting follows the same steps and stages as manual pentesting, but AI plays a role throughout. The extent of that role can vary. Different types of AI pentesting include:

AI-assisted pentesting

With AI-assisted pentesting, humans drive the testing. AI helps with:

• Vulnerability discovery
• Payload generation
• Log parsing
• Report drafting

AI tools are used to accelerate specific actions of the pentesting process, like scanning for and alerting on known vulnerabilities, but a human is heavily involved, orchestrating and planning the overall testing strategy and managing each individual step.

Hybrid / AI-augmented pentesting

In this type of AI pentesting, AI gets more autonomy, but the human is still leading and orchestrating. In hybrid/AI-augmented pentesting, AI handles discrete stages on its own, such as:

• Discovery automation
• Attack path analysis
• Vulnerability prioritization

Humans interject after each phase, validating findings and hypotheses before testing continues.

AI-led autonomous pentesting

With this method, AI takes the lead, and humans play more of an oversight role.

AI agents:

• Map attack surface
• Form hypotheses
• Execute multi-step exploit chains
• Validate findings
• Draft reports

Humans:

• Set scope
• Review results
• Handle edge-case logic abuse
• Investigate more challenging, creative exploits

Pros and cons of AI pentest

AI won’t replace human pentesters, even in AI-led autonomous pentesting. It will, however, take the menial tasks like finding known vulnerabilities and drafting reports, off their plates. It will ultimately leave the human pentesters to do what they do best: creatively explore complex, business logic-based attack paths.

Limitations of AI pentesting include:

• Certain types of business logic and context, including risk tolerance, regulatory nuances, business impact severity. Although AI is rapidly improving its ability to understand and apply business logic and context to testing results, there are always additional layers of advanced human logic that can be applied.
• Humans needed for scoping.
• Some regulations, like PCI, require human review.
• Novel architecture edge cases: highly custom environments may require human reasoning.

AI vs. manual pentesting example

How exactly does AI pentesting match up with human pentesting?

AI can match or exceed senior testers on common classes of issues at dramatically higher speed. But the most complicated, logic-heavy cases still benefit from humans. The ideal scenario is AI for continuous coverage, humans for deep logic and edge cases.

For example, XBOW recently conducted a human vs. AI pentest experiment. Five professional pentesters and XBOW were tasked with finding and exploiting the vulnerabilities in 104 realistic web security benchmarks. The most senior human pentester, with over 20 years of experience, solved 85% during 40 hours, while others scored 59% or less. XBOW also scored 85%, doing so in 28 minutes – a material time savings. However, when broken down by difficulty, XBOW came in second to the most experienced pentester on the most challenging tasks.

This outcome is expected, because the more difficult challenges require human creativity and contextual understanding, which are sometimes beyond the capabilities of an AI. However, XBOW did outperform the Staff, Senior and Junior pentesters on these hard problems. On the easy and medium challenges, XBOW excelled, surpassing all humans. Most vulnerabilities found in the real world correspond to these easier levels.

XBOW is the ideal assistant for human pentesting teams

XBOW is an AI-led autonomous offensive security platform that can handle the mundane pentesting tasks while your team does what it does best: craft complex, creative exploits.

To find out how XBOW will boost the productivity of your team by rapidly finding and reporting on exploitable vulnerabilities in your system, get a demo today.

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This post is part of the XBOW Offensive Security Academy, an educational blog series that discusses and explores offensive security tactics and techniques in the age of AI.