HTB Academy certificate holders now have access to dedicated, public-facing pages for every certification earned. These pages offer a professional, verifiable way to showcase your technical expertise to employers and the community.

Users can access these pages directly through their HTB Profile. Clicking on any earned certificate credential takes you to that certificate's dedicated public page.

Key features include:

The HTB Academy platform has officially migrated to Academy 2.0. This update establishes the new interface as the primary environment for all learners. It’s faster, smoother, and built to power the next wave of content, features, and skill progression.

The previous interface has been retired to ensure a unified experience across the platform.

HTB Profile introduces a centralized view of your achievements and skills across Hack The Box platforms.

With the HTB Profile, you can:

Learn more about it here.

The Privilege Escalation Tradecraft Analysis module covers the analytical study of privilege escalation tradecraft on Windows, from its role in the attack lifecycle to how it can be detected and investigated. While completing this module, you will analyze real-world techniques and exploits to understand how they work internally and learn how to translate this knowledge into effective and reliable detection strategies.

Key learning outcomes:

HTB CWPE is a hands-on, cloud-based certification that brings wireless security training into the modern age. Paired with the WiFi Penetration Tester Job-Role Path, it's one of the few programs to offer a holistic curriculum, real-world practice with WPA3 attacks, and doesn’t require specific hardware or complex setups.

Included in the job-role path and certification are learning material and hands-on labs that focus on how attackers actually approach wireless environments: reconnaissance, exploiting weak configurations, credential attacks, evil twins, captive portals, and full corporate Wi-Fi attack chains for anyone who wants to properly understand and test wireless security, not just check a box.

Get started with HTB CWPE here or learn more on our blog here.

The module provides a structured, hands-on introduction to the most common and impactful security risks affecting modern mobile applications. By completing the module, you will learn how mobile vulnerabilities arise, how to categorize them based on known mobile security frameworks, how they are exploited in real applications, and how to identify and remediate them using techniques learned in the previous modules.

Key learning outcomes:

The module provides a deep technical analysis of WMI tradecraft from both attacker and defender perspectives. While completing the module, you will learn how WMI is abused for execution, lateral movement, persistence, and stealthy backdoor deployment, as well as how to detect, hunt, and investigate malicious WMI activity using logs, ETW, and low-level artifacts.

Key learning outcomes:

HTB Account has now been fully integrated into the LetsDefend platform.

What this means for Community Platform users:

For a short transition period, there will be two sign-in options:

The AI Red Teamer Job Role Path, built in collaboration with Google, is now fully complete!

This path equips cybersecurity professionals with the cutting-edge skills needed to assess, exploit, and secure today’s AI-powered systems. With 12 hands-on modules aligned to Google’s Secure AI Framework (SAIF), you’ll explore everything from prompt injection and model privacy attacks to adversarial AI techniques, supply chain risks, and deployment-level threats.

As you move through the path, you’ll work through real-world AI security scenarios, learning how to influence model behavior, craft AI-specific red teaming strategies, and execute offensive security testing against AI-driven applications.

Modules included in this path are:

The module introduces you to one of the most critical privacy threats in machine learning: the ability to determine whether a specific individual’s data was included in a model’s training set. You’ll explore how overfitting creates detectable behavioral signals, implement real membership inference attacks using the shadow model methodology, and apply industry‑recommended defenses such as differential privacy.

Key learning outcomes:

The module introduces you to the strategies and techniques for protecting AI applications from attacks explored in the AI Red Teamer path. You’ll explore how to proactively harden models through adversarial training and tuning, as well as implement LLM guardrails to enforce safety and reliability at the application layer.

Key learning outcomes: