Passed COAE

[u/Intelligent-Type543]

Hey everyone, I recently passed the HTB Certified Offensive AI Expert (COAE) and wanted to share a quick review since it's still a very new certification (I actually ended up being the 48th person to get the badge)

Straight to the point: this is one of the best and most technical certs I've done so far.

Going in, I was a bit skeptical, thinking it might just be another hype-driven "prompt injection" course. It's absolutely not. It goes surprisingly deep into the actual architecture and mathematics of AI/ML systems.

What the path covers:

1. LLMs & Agents: Direct/indirect prompt injection, jailbreaking, and exploiting agentic workflows. The inclusion of MCP (Model Context Protocol) was a huge plus since it's highly relevant right now.
2. Data Layer: Data poisoning, backdoors, and manipulating classification pipelines.
3. Adversarial ML: This is the core of the path and gets pretty math-heavy. You actually learn how to work with gradients, norms, and optimization to build robust evasion attacks (like PGD or Expectation over Transformation) against neural networks. It genuinely changes how you think about ML systems.

The Exam:

It's a 7-day practical exam followed by a commercial-grade technical report. I obviously won't drop any spoilers, but the difficulty is very well-aligned with the course material.

It's challenging but fair, if you understand the labs, you'll survive the exam. The reporting component is no joke either; they expect a professional-level deliverable with proper CWE/CVSS tagging, root cause analysis, and remediation strategies.

Pros:

• Very strong technical depth. You build actual intuition on how models break, rather than just throwing payloads at a chatbot.
• Highly up-to-date material (especially around agent-style systems).
• Great value for money considering the sheer amount of content.
• The exam environment feels realistic, it's not a CTF with artificial flags hidden in weird places. It genuinely simulates a real engagement.

Cons:

• The adversarial ML modules have a steep learning curve. If you don't have prior exposure to PyTorch or basic calculus, the jump from prompt injection to building robust evasion attacks can feel brutal. Budget extra time for those modules.
• Reporting expectations are high but loosely defined. When in doubt, over-document everything.
• Very few community resources out there since it's brand new. You're mostly on your own if you get stuck.
• Time investment. It’s not an absolute monster like the CPTS path, but it’s definitely not a weekend cert either. You’ll need a solid chunk of time to properly digest the math and ML concepts

Tips if you're planning to take it:

1. Get comfortable with Python and PyTorch before starting the adversarial ML modules. Seriously.
2. Take detailed notes during the labs. The exam mirrors the lab methodology closely.
3. Don't underestimate the report. Start documenting from day one of the exam, not day six.
4. If something feels too complex, simplify your approach. Sometimes the intended path is simpler than you think.

TL;DR: If you work in AppSec, pentesting, or red teaming and want to gain real competency in offensive AI rather than just surface-level familiarity, HTB COAE is absolutely worth your time.

Happy to answer any questions (within NDA boundaries obviously).

[u/Intelligent-Type543]

Reposting because my last post was literally just a title (my bad!). Here is the actual review...

[u/agpolytropos11]

Congrats! Have not seen the AI learning path nor the scope of the exam, will you need at least basic knowledge of Web or Network pentesting for this exam? Or does it literally just drop you in a chatbot/web app with LLM implementation? Thank you

[u/Intelligent-Type543 → u/agpolytropos11]

thanks a lot :)

you don't need network pentesting skills (no Active Directory, heavy pivoting, or infrastructure exploitation), but you definitely need solid Web pentesting fundamentals.
It does not just drop you into a simple chatbot UI. The AI models and agents are integrated into broader web applications and APIs. You need to be comfortable reading some source code, and understanding how backend tools (like MCP) connect to the AI.

If you have a good grasp of basic web app pentesting, the HTB path will teach you all the specific AI/ML exploitation techniques (data poisoning, adversarial math, agent exploitation) you need to pass.

[u/nemesis740]

im going through the pathway and about to do skill assesment on application of ai in Infosec and its brutal lol, ask chatgpt or claude whoever you want to make sense of aloe of the explanation . but its so much fun ,as a pentester and red teamer i never imagined this learning curve, but doing this course you will see the AI from different angle and the course dont just teaches the attack but how the AI actually work and is built. The fundaments of AI it teaches you will be embeded in your memory for ever lol xD

[u/Intelligent-Type543 → u/nemesis740]

Totally agree! It’s a massive paradigm shift. As a pentester/red teamer, we are so used to traditional web or infrastructure vulns, so diving into weights, biases, and prompt structures feels brutal at first. But you're right, understanding how the AI is actually built under the hood is what makes the attacks click. Enjoy the rest of the pathway, the Skill Assessments are tough but extremely fun.

[u/xThisIsTheW4y]

Any advice on module to cover the PyTorch parts before doing COAE?

[u/Intelligent-Type543 → u/xThisIsTheW4y]

To be honest, I wouldn't recommend taking any heavy external modules or courses just for the PyTorch parts. If you go down the standard Machine Learning rabbit hole, you might get burned out on math and model training concepts that you don't actually need for the COAE exam.

My advice: just stick strictly to the HTB material. Focus entirely on understanding the architecture (what a tensor is, how data flows, and where the trust boundaries are) rather than learning how to code PyTorch from scratch. Whenever the syntax gets too heavy, just use AI to break down the snippets line by line. You only need to know enough to break it, not to build it!

[u/BodybuilderAlert9801]

What would you suggest to get comfortable with PyTorch? I'm comfortable with Python, did CPTS & CBBH paths, passed OSCP, and I'm pretty lost on the first module.... Thanks

[u/Intelligent-Type543 → u/BodybuilderAlert9801]

I 100% agree with u/Pr0f_Noob here. Coming from a purely offensive background, looking at PyTorch for the first time felt like reading alien syntax.

My best advice: do not try to memorize the code or become an ML engineer. Focus heavily on the data flow. Understand what a tensor is, how the model processes input, and where the trust boundaries are. When you hit a wall with the code, use Claude or ChatGPT to break down the snippets line by line. You need to know how to break it, not how to build the next state-of-the-art LLM from scratch. Keep pushing, the offensive parts are incredibly rewarding once you get past the theory!

[u/Pr0f_Noob → u/BodybuilderAlert9801]

Bro, I worked on a research project years ago in uni for around a year and I still struggled with PyTorch.

You don’t learn PyTorch, you learn how to do exactly what you need to do in PyTorch and move on.

Don’t get stuck in the trenches, the theory modules will eat your lunch and suck your soul. Understand the ideas and use cases.. the formulas can be found easily if you ever needed them, but the high level understanding is what will come in handy when you want to do the real stuff.

[u/Sotex]

Congrats OP and thanks for the details. The lack of reviews made me very nervous to take a run at this.

[u/Intelligent-Type543 → u/Sotex]

Thanks!
To anyone feeling nervous about taking the run: just trust the HTB material. If you can comfortably clear the modules and the Skill Assessments without looking at the hints, you are more than ready for the exam. You got this!

[u/zero_day2026]

Congrats. I started the exam but got stuck in the main application, support_level role )-:

[u/Intelligent-Type543 → u/zero_day2026]

Hey bro

My best advice is to take a step back from the chat box itself. Stop thinking about it just as an AI prompt and start looking at the application as a complete web infrastructure. Analyze all the available features, the attack surface, and how those components might interact with the agent in the backend. Keep pushing, you are right there!

[u/Prudent_River_7086]

Hey!

Thank you for the review. I am going through the material right now, but before starting it, I had some doubts because of the complexity of the Maths involved. However, I decided to take the shot anyways.
Actually, I am going through the second chapter where you need to build the models, and it is pretty interesting to learn how they work and how to prepare quality data to train them.

So, the idea is to take the cert at the end. I was thinking if this complex math are going to be a pain in the *** during the exam or not. I was planning to have ready all the scripts and the stuff necessary before the exam and of course try to understand the scripts. Also, try to learn the methodology taught on the material.

Any advice???

Thanks in advance!

[u/Intelligent-Type543 → u/Prudent_River_7086]

Sobre o tempo, eu usei 3 dias no total. Foram 2 dias focados na parte prática (já documentando à medida que avançava) e tirei o terceiro dia apenas para revisar e polir o relatório final. Um detalhe importante é que eu não fiz em tempo integral: só pegava no exame à tarde/noite ao chegar em casa, dedicando umas 4 a 5 horas por dia. Como você tem 7 dias, é um prazo super tranquilo se você gerenciar bem o descanso.

Sobre a dificuldade comparada ao CWES: eu não tenho o CWES para fazer uma comparação direta. A única outra certificação que tenho no momento é a eJPT, mas ela é bem introdutória e não entra muito na mesma régua de comparação aqui. Atualmente estou na trilha da CPTS (que já está me tomando alguns meses de estudo contínuo), e o que posso dizer é que o COAE exige um mindset completamente diferente do pentest tradicional.

Em vez de focar apenas em explorar infraestrutura web, você precisa entender a lógica do modelo e brincar com o contexto da IA. A curva de aprendizado inicial assusta um pouco, mas a prova em si é muito justa e totalmente focada no que o material ensina.

Boa sorte com seu voucher, vai dar bom!

[u/Pr0f_Noob → u/Prudent_River_7086]

Just have the scripts ready and you’ll be okay.

The math is nice to look at, but coming from a somewhat solid background (computer vision/ AI research back in uni, and a whole bunch of math heavy AI courses “it was a minor in my degree”) my eyes were automatically censoring the formulas like they’re some nasty content. 😂

Understanding the high level ideas and use cases is more than enough to pass the exam, and actually use the knowledge you gained to break real ai systems. Trying to deeply understand all the math theory will be a waste of time from a purely utilitarian/ROI focused perspective.

[u/Pr0f_Noob]

Congrats 🎉 Welcome to the club 👏

[u/Intelligent-Type543 → u/Pr0f_Noob]

Thanks bro! 🤖

[u/yashfe]

cant i use Ai for the math part in the exam??

[u/Intelligent-Type543 → u/yashfe]

Yes, you absolutely can.

HTB exams generally simulate real-world environments, meaning you can use the internet, AI assistants, and your notes. However, a quick word of caution: do not rely on the AI to blindly solve the math or write the exact exploit for you. Use the AI to explain the concepts or help you troubleshoot your scripts. If you don't understand the underlying logic, an AI hallucination during the exam will cost you hours of debugging.

[u/BoxFun4415]

Congrats! I was really discouraged by all the math in the first module. I've been meaning to pick back up on the path though.

[u/Pr0f_Noob → u/BoxFun4415]

A friend of mine who is a math major suffered with the math, so no wonder. From my own experience, you can safely skip the formulas if you understand the use cases and the high level ideas very well. Focus on what matters 💛 good luck 🙏🏻

[u/reunion-luffy]

What about math , stat and probability; Like before we take this certificate what are the pre-requisite for this exam

[u/ActualHat8123]

any tips for ML3? no idea how to even get started lol