The Penetration Testing Industry Has an Automation Problem

The cybersecurity industry has a new buzzword problem, and this one could leave your organization dangerously exposed.

Over the past few years, I've watched a wave of vendors flood the market promising "automated penetration testing" powered by AI. The pitch is slick: continuous, affordable, scalable security testing without the hassle of scheduling a human team. It sounds like a dream. But as someone who has spent years doing this work for real organizations, finding the vulnerabilities that actually keep security leaders up at night, I can tell you that calling these tools "penetration testing" is a stretch that borders on misleading.

Let me explain what's actually happening inside a real penetration test, why human intuition is irreplaceable, and where AI and automation legitimately fit into the picture.

What Is Penetration Testing, Really?

Before we can have an honest conversation about automation, we need to agree on what penetration testing actually is.

A penetration test, a real one, is a simulated cyberattack conducted by a skilled professional who is actively trying to compromise your environment. Not just scanning it. Not just cataloging weaknesses. Actually exploiting them, the same way a determined adversary would. The goal is to answer a question no vulnerability scanner can answer: If a motivated attacker came after us right now, how far would they get?

That question requires a thinker on the other end. It requires someone who can read a situation, pivot when an obvious path is blocked, chain together vulnerabilities that individually look minor, and find the creative angle that no ruleset anticipated. Penetration testing is, at its core, an exercise in adversarial human reasoning.

The Rise of "Automated Pen Testing" and Why It's Mostly Repackaged Vulnerability Scanning

Here's where things get complicated. A number of vendors have gone to market with platforms that run automated scans, apply machine learning to prioritize findings, and deliver reports that look, on the surface, like the output of a penetration test. Some go further, claiming their AI can actively "test" vulnerabilities rather than just detect them.

What these tools are actually doing, in most cases, is sophisticated vulnerability scanning. Vulnerability scanning is valuable. I use scanning tools every single day as part of my workflow. But there is a fundamental, categorical difference between identifying a vulnerability and exploiting it, and that difference is exactly what separates a vulnerability assessment from a penetration test.

A scanner can tell you that a service is running an outdated version of software with a known CVE. A penetration tester takes that finding and asks: Can I actually exploit this in this specific environment? What does it give me access to? Can I combine this with that misconfigured permission I found over there to move laterally and reach something that matters?

That chain of reasoning, driven by curiosity, creativity, and contextual judgment, is not something current AI systems replicate. And frankly, the vendors who claim otherwise are selling you comfort, not security.

What Makes Human Creativity So Critical in a Pen Test?

I've worked on engagements where the "obvious" attack path led nowhere, and the actual compromise came from a completely unexpected angle. A legacy system that wasn't even on the client's radar. A business logic flaw that no automated tool would think to probe. A social engineering angle that emerged from a conversation with an employee during a physical assessment.

Real attackers are creative. They are patient. They adapt. They chain together findings that individually seem insignificant. They read your environment not just technically, but contextually, understanding your business, your workflows, and where the gaps between them might live.

Human pen testers do the same thing. When I'm on an engagement, I'm not just running scripts. I'm thinking about the organization I'm trying to compromise. I'm asking myself what a ransomware group would prioritize. I'm looking at the relationships between systems, not just the systems themselves. I'm trying things that don't appear in a CVE database because they're specific to how this organization built their environment.

That intuition, built on years of experience, research, and genuine adversarial thinking, is the entire value proposition of a penetration test. It's what separates it from a checklist exercise.

Can AI and Automation Help in Pen Testing?

Absolutely. Here's How. I want to be fair here, because this isn't an anti-technology argument. Automation and AI genuinely do make penetration testers more effective. The key word is "more effective," not "replaceable."

Here's where these tools add real value in our engagements:

Reconnaissance and data gathering. Automated tools can rapidly collect open-source intelligence, map attack surfaces, enumerate subdomains, and identify exposed assets far faster than any human working manually. This frees up time for what matters most: analysis and exploitation.

Vulnerability identification. Running authenticated and unauthenticated scans, identifying known CVEs, flagging misconfigurations. Automated scanning tools do this reliably and at scale. Used as an input to a human-led engagement, they're invaluable.

Credential testing and brute force. Automating password spray attempts, testing default credentials across discovered services, or running dictionary attacks against authentication portals. These are tasks where automation shines and where a human's time is better spent elsewhere.

Reporting assistance. AI can help structure and draft findings, cross-reference remediation guidance, and format reports more efficiently. This is a genuine productivity gain for testers.

Coverage consistency. Automated tools ensure that known vulnerability classes don't get missed. A great pen tester can have a bad day. An automated scanner doesn't.

All of these are force multipliers for a skilled human tester. They compress the time spent on mechanical tasks so the human can focus on what they do best: thinking like an attacker.

What Automation Cannot Do and Why It Matters for Your Security Posture

Now let's be clear about the limitations, because this is where the marketing diverges from reality.

Automation cannot chain vulnerabilities with contextual judgment. Finding that a web application has an SSRF vulnerability is one thing. Recognizing that the internal metadata service it can reach exposes cloud credentials that can then be used to pivot into a storage bucket containing sensitive customer data, that's a chain of reasoning that requires a human to construct and test.

Automation cannot adapt to unexpected environments. Pen testers constantly encounter systems, configurations, and architectures that don't match what's in the scope documentation. Real attackers don't stop when they hit something unexpected. Neither do good pen testers. Automated tools, by definition, work within predefined logic.

Automation cannot test business logic. Some of the most impactful vulnerabilities aren't technical at all. They're flaws in how a system is designed to work. An e-commerce platform that allows negative quantity purchases. A healthcare portal that lets you access another patient's records by incrementing an ID number. These require a human who understands business context to even think to look for them.

Automation cannot perform meaningful social engineering or physical testing. Phishing simulations have their place, but a real social engineering assessment requires a human who can think on their feet, adjust their approach mid-conversation, and understand human psychology in real time.

And critically, automation cannot be held professionally accountable. When we conduct a penetration test, there are licensed professionals with their names and reputations attached to the findings. We scope engagements carefully, communicate with clients throughout, and make judgment calls that require professional responsibility. An automated platform does not carry that accountability.

The "Human-in-the-Loop" Myth: QA'ing Scan Results Is Not Pen Testing

One argument I hear from vendors defending automated platforms is that they keep a human in the loop. Testers review and validate the output of the automated tools. This is framed as the best of both worlds.

It isn't.

If the human's role in an engagement is primarily to review what a scanner found, clean up the report, and mark findings as confirmed or false positives, that is a vulnerability assessment with a human reviewer. That is not a penetration test. The human contribution in a real penetration test is the active, creative exploitation. It's the offensive thinking. Reviewing a machine's output after the fact is not a substitute for that.

This distinction matters enormously for the organizations purchasing these services. If you believe you've had a penetration test but what you actually received was a glorified vulnerability scan with a human rubber stamp, you have a false sense of your security posture. And in the current threat landscape, that false sense of security may be more dangerous than knowing your gaps honestly.

Questions to Ask Before You Schedule a "Penetration Test"

If you're evaluating penetration testing providers, whether established firms or newer automated platforms, here are questions that will cut through the marketing quickly:

What percentage of the engagement time is spent on active, manual exploitation attempts versus automated scanning? What is the methodology for chaining vulnerabilities across your environment? Can the tester walk me through how they would attempt lateral movement after an initial compromise? What happens when they encounter a system or configuration that's outside the standard scope of automated tools? Who, specifically, is responsible for the findings, and what are their credentials?

If the answers are vague, or if active human exploitation isn't central to the methodology, you're looking at a vulnerability assessment. You should price and scope it accordingly.

The Bottom Line: Real Penetration Testing Requires a Real Adversary Mindset

The cybersecurity market is moving fast, and vendors are moving even faster to capitalize on interest in AI. That's not inherently bad. AI genuinely is transforming a lot of security functions for the better. But penetration testing is a specific discipline with a specific purpose, and that purpose is to answer the hardest possible version of the question: Can we actually be compromised?

Answering that question requires someone who thinks like an attacker. Someone who is creative, persistent, and experienced enough to find the path that wasn't supposed to exist. Someone who understands not just your technical environment, but how a real adversary would think about targeting you.

Automation can make that person faster, more thorough, and more consistent. It cannot make that person unnecessary.

When you're evaluating your penetration testing program, make sure you know what you're actually getting, and make sure a real human is doing the most important work.

Have questions about what a legitimate penetration testing engagement looks like? Compass conducts manual, methodology-driven penetration tests across a range of industries. Reach out to our team to learn more about our approach.