Disclaimer: All information described in this article is publicly available and can be independently verified through research. Nothing presented here violates any non-disclosure agreement or discloses proprietary detection methodologies that I have reported. This article is intended for educational and research purposes only.
My name is sebwebneb. I am an independent security researcher specializing in kernel-level vulnerability research and anti-cheat system analysis. I have submitted accepted vulnerability reports to Epic Games through their HackerOne bug bounty program, as well as reports to Riot Games, Malwarebytes, and other major companies. I am not employed by these companies and do not have access to their internal systems. I am writing this article because the gaming security community is saturated with misinformation and speculation regarding how kernel-level anti-cheat systems actually work.
Understanding Anti-Cheat Architecture
To effectively analyze anti-cheat systems, you need to understand their fundamental architecture. Most people conceptualize an anti-cheat as a single program that simply "scans for cheats." This oversimplification leads to completely flawed assumptions about detection methodologies.
Think of an anti-cheat system like a turtle: the anti-cheat is the shell, and the game is the body. If you can penetrate or circumvent the shell, you gain direct access to the body. This metaphor illustrates the protective layering that modern anti-cheat systems employ.
In Fortnite's case, the anti-cheat operates as a combined system. UAC (Epic's user-mode component) works in conjunction with EasyAntiCheat's kernel module. These components function cooperatively, sharing telemetry and cross-referencing behavioral data points. The user-mode component monitors process space, detects overlay applications, and identifies unsigned executables commonly used in commercial cheats. The kernel component serves an entirely different purpose.
The kernel-mode component of a modern anti-cheat system maintains near-total visibility of system activity. Apart from things running outside the system or above it, like System Management Mode or hypervisors, the kernel driver observes all standard CPU-mediated activity. This includes driver enumeration, process traversal, thread inspection, and kernel memory scanning. While there are edge cases involving specialized hardware or firmware manipulation that can evade this visibility, these represent advanced attack vectors beyond the scope of typical cheat development.
What many developers fail to understand is that anti-cheat systems are automated pattern-recognition engines, not human analysts making contextual judgments. If you have a kernel-level cheat loaded for an entirely different game, you can still receive a ban in Fortnite. The system cannot determine with absolute certainty that a specific kernel driver was exclusively used for Counter-Strike and would never interact with Fortnite. This is a critical distinction that separates theoretical bypass knowledge from practical operational security.
The Backend Intelligence System
The most pervasive misconception in the cheat development community is the belief that the kernel driver on the client side is the primary enforcement mechanism. This is fundamentally incorrect. The kernel driver's primary function is telemetry collection and automated filtering of low-hanging fruit. Publicly known drivers, unsigned executables, and previously catalogued bypass techniques get caught here.
The real enforcement happens server-side through machine learning models and behavioral correlation. If 100 players all have the same process running and all 100 players are suspected of cheating, the anti-cheat can establish a deterministic correlation. From there, the system makes automated decisions based on pattern matching across the entire dataset.
This is why claims of being "undetected" are misleading. If you are active in a cheat community and not actively attacking the anti-cheat infrastructure itself, your ban is already automated and queued. The data exists on their servers, and they can action it whenever strategic priorities align. Your telemetry is sitting there waiting to be processed.
Common Misconceptions About Driver-Based Bypasses
When I was new to game security and active in the Fortnite cheating community, there was persistent speculation that you could survive indefinitely using an IOCTL driver manually mapped with KDMapper that created a driver object as long as you were the only one using it. This is completely false, and I cannot stress this enough.
Having reverse-engineered EasyAntiCheat's detection logic for driver objects aside, there is no strategic reason for them to delay ban this method. The detection is fully automated as the kernel driver handles the majority of detections, the low-effort, publicly known methods. Backend data analysis handles the "undetected" minority that slip through initial client-side filtering.
As biased as this may sound, you will eventually be ban waved. Your telemetry data resides on their servers indefinitely, and they can process it at will. I am speaking from direct experience: I developed three separate pay-to-cheat (P2C) systems that all resulted in ban waves, and I understand anti-cheat theory at a level where this outcome is now obvious in retrospect. It comes down to common sense. You cannot hide from server-side correlation forever.
The Detection Profiling System
When developers create novel bypass methods, they often believe they are outsmarting the anti-cheat. From my experience on both sides of this process, what actually happens is quite different. You are providing free research to the security team. This is what I call the "feedback loop trap," and it is why "undetected" is a fundamentally misleading term in this domain.
Ban delays are not arbitrary. They are strategic decisions made by security teams based on specific objectives. If your method is a minor variation of a catalogued technique, bans occur within days. However, if you have discovered a genuinely novel bypass, the detection window extends for weeks or months.
The delay is not due to detection uncertainty. Security teams actively gather telemetry across thousands of flagged accounts to construct behavioral profiles. These profiles encompass all observable characteristics: memory execution regions, call stack patterns during memory access, loaded driver signatures, and executable file hashes. They are watching you the entire time, cataloguing every detail.
Consider a scenario where the anti-cheat system observes forty accounts over two weeks, all exhibiting memory execution within discardable driver sections. For context, discardable sections are regions of driver memory intended only for initialization and should not contain actively executing code during normal runtime. Rather than issuing immediate bans, which would alert developers to the specific detection vector, security teams allow the method to propagate while refining detection heuristics to eliminate false positives. This approach maximizes the impact of the eventual ban wave while minimizing developer feedback about which specific implementation triggered detection.
This is the reality of modern anti-cheat systems. They are patient, methodical, and they always win in the end.
Vanguard vs. EasyAntiCheat
A long-standing debate in game security is which anti-cheat system is superior: Vanguard or EasyAntiCheat. I have not reverse-engineered Vanguard to the same depth as EasyAntiCheat, primarily analyzing their imports and external behavior, but I maintain close connections with researchers who have extensively deobfuscated Vanguard's internal logic. This provides sufficient context for an objective technical comparison.
The two systems rival each other extremely closely. For the amount of client-side work EasyAntiCheat performs compared to Vanguard, it is genuinely surprising. Vanguard takes a deeper approach focused on data collection and statistical analysis rather than active prevention. They prioritize stackwalking and identifying behavioral outliers over implementing hard blocks.
One of Vanguard's most significant enforcement mechanisms is mandatory HVCI, which forces the majority of cheats to operate as internal modifications rather than external kernel drivers. This is simultaneously Vanguard's greatest strength and its primary weakness. Stopping internal cheats is extraordinarily difficult because a game's memory is constantly changing and highly susceptible to manipulation.
In contrast, EasyAntiCheat maintains a balanced approach but primarily reserves extensive data collection for large-scale cheat providers. This strategic focus is why EasyAntiCheat leads in DMA detection capabilities, while Vanguard emphasizes prevention. DMA detection is inherently challenging, but mitigation techniques like Vanguard's guarded memory regions can slow exploitation significantly.
However, guarded regions have fundamental limitations. The protected memory still exists and remains technically accessible. The guard is a layer of abstraction, not true isolation, which leads to extremely simple bypasses like posted by Xyrem a while ago. If these do or do not work at the moment, I couldn't tell you since I am not up-to-date. This isn't to say Vanguard is bad at all though, I think very highly of their innovative ideas such as their SwapContext hook.
Personally, I believe EasyAntiCheat is more strategically positioned for long-term dominance. Vanguard expends substantial system resources detecting relatively simple low-level cheats. If EasyAntiCheat were to enforce mandatory HVCI like Vanguard does, they would establish a decisive advantage. However, this decision depends heavily on existing HVCI adoption rates among their player base. If the majority of users do not already have it enabled, the operational disruption may outweigh the security benefits.
From Cheat Development to Security Research
My background in this space follows an unconventional path. I started around age 8 with game exploitation on Roblox, learning how software worked by breaking it. By my early teens, I was deep in the kernel development scene, eventually becoming Head Kernel Engineer with multiple providers where I built and maintained commercial anti-cheat bypasses.
I developed kernel drivers that evaded EasyAntiCheat and BattlEye, no matter it was through things like blending in or hiding. Near the end of 2024, I sold pay-to-cheat software for approximately four months. The funds were into savings for future learning resources, but the experience provided invaluable insight into both the technical and operational realities of the cheat ecosystem.
Across three separate P2C projects I developed, all three resulted in ban waves. That pattern made one thing abundantly clear: the security teams always win eventually. The only variables are how long detection takes and how much data they collect during that window. There is no such thing as permanent undetected status.
In early 2025, I shifted focus entirely. I started reporting vulnerabilities through HackerOne instead of exploiting them. The work I do now centers on identifying vulnerabilities before they become widespread problems and developing prevention mechanisms that eliminate entire attack classes. This transition was not driven by morality or some sudden revelation. It was driven by the simple realization that defense is the only side that wins permanently.
The technical significance of these findings is not the bypass methods themselves, but what they reveal about architectural assumptions in current protection models. When documented attack surfaces remain unmonitored despite being well-understood threat vectors, it indicates gaps in the defense-in-depth strategy that could affect multiple components of the system.
Conclusion
The gaming security landscape continues to evolve at an accelerating pace. Developers who rely on AI for driver development or outdated forum discussions from 2021 for bypass techniques will find themselves increasingly outmatched.
The era of reactive detection is ending, what comes next will separate those who adapt from those who get left behind.
If you're a game security researcher or just interested in talking, feel free to contact me!