A guide to identifying cheating in online video games in 2026

Serafim Pinto is the CTO and co-founder of the anti-cheat solutions provider Anybrain.

The cheating landscape in video games is drastically different in 2026 than in previous years. Advancements in generative AI (GenAI) coding have opened the floodgates in the cheating marketplace. Meanwhile, traditional cheating tools are still in wide circulation, and are only getting more complex and difficult to prevent as bad actors work to make them compatible with the latest anti-cheat software.

It’s a complex and messy world to navigate for game developers, and in the current gaming landscape, where competitive online gaming is more popular than ever, it is vital for those in the games industry to understand it.

As we enter 2026, the battle between game developers and cheaters is still at an all-time high. I have seen and heard this first hand, and using the data and insights from the Anybrain platform, I want to break down in this article how the cheating landscape has shifted and give game creators a guide to identifying the various different forms of cheating in gaming, so they have an advantage in the coming year.

A brief history of cheating in video games

In the early days of video games, cheating was a less serious affair. State manipulation still existed in the few competitive online PC games, but the vast majority of cheats came from code-manipulating tools like Game Genie, and were primarily used for functions like unlocking extra lives or skipping levels. It was locally contained, and it was the choice of the player to engage.

Then came the 2000s and the rise of online games. This new wave of competitive online titles birthed the first generation of wallhacks and aimbots in competitive PC titles, and more importantly, saw the rise of esports. There were more players who were desperate to win by any means necessary, and that turned cheating from a fan activity with friends to a sophisticated, multi-million dollar industry existing within the black market; an industry that threatens the very core of a game’s economy, damaging player retention and brand integrity in the process.

Within the past decade, however, we’ve seen the most significant shift in the cheating landscape. Previously, the bad actors making cheats were programmers with years of experience behind them, but the introduction of GenAI and vibe coding has given just about anyone the ability to make their own cheating tools, learning and adapting from existing open-source tools and the kernel-level anti-cheat solutions themselves. It has resulted in the 2026 cheating landscape being full of different forms of cheating, which I want to go over in this article.

The seven pillars of modern cheating

Cheating comes in several formats, from physical hardware manipulation to software hacking. While the differences between cheating solutions are minute, they can broadly fall into seven primary categories. Understanding these seven is an essential starting place for any developer looking to identify cheating in their games.

1. Pixel-based AI bots

The most common cheating tool for competitive online shooters. These bots use local machine learning to identify player outlines and automatically trigger inputs. In recent years, the cheat has exploited cloud-streamed games, allowing it to operate outside traditional detection systems. In order to catch these cheaters, developers need to look out for consistent, inhuman reaction times that fall within a suspiciously narrow millisecond window across thousands of encounters. Current AI bots are programmed to act autonomously with exact precision. It leads to very inhuman consistency, and presents the feeling of an AI.

2. Computer vision

Similar to pixel bots, but more advanced, these systems read the game screen as one image, bypassing the need to access the game’s internal memory. Discrepancies between player input and the game’s UI state, often detectable by analysing the smoothness of a mouse or controller path, will indicate to developers that this is the cheat in use.

3. Direct memory access

Direct memory access (DMA) cards allow a second computer to read the memory of the gaming PC. This makes the cheat invisible to software-based anti-cheat systems. The solution is to use AI and anti-cheat detection tools to pick out which inputs are synthetic and which are not. By monitoring for player behaviour and comparing it against profiles of real players and confirmed AI bots, developers can figure out who is cheating through their actions, rather than any device or software on their device.

4. State manipulation

Common in peer-to-peer or poorly validated server-side games, this includes speed hacks or lag switching. Regular teleportation or packet bursts that coincide exactly with engagement windows (e.g., a player lags only when they are about to be shot) give these cheaters away. This is a pretty standard form of cheating that is easy to spot, but still quite common.

5. Overlays/ESP (extra sensory perception)

The classic wallhack, where players see skeletons or boxes through geometry. By having your anti-cheat system analyse gaze data, it is possible to identify players who are consistently tracking enemies through walls (even if they don’t fire). They reveal themselves through predictive movement patterns.

6. Automation and macros

This is common in MMOs and RPGs to automate resource gathering or complex combat rotations. Like with many automated cheating services, the frame-perfect execution of complex button combos over extended periods (three or more hours) without error gives the game away.

7. Exploits

This form of cheating involves utilizing unintended game logic (e.g., clipping through a map), and usually appears as frequent out-of-bounds triggers or impossible coordinates recorded in the game log. Exploits like this tend to go viral, so use your community as a form of Q&A to catch things that are missed in development and patch them out.

Emerging threats: the future of 2026 and beyond

One of the most significant hurdles in 2026 is the democratization of cheating. “Cheating as a service” (CaaS) has lowered the barrier to entry to near-zero, with Discord or TikTok serving as an entry point for casual cheaters. However, the real threat lies in “private cheats.” For a monthly fee, players receive bespoke software that updates automatically whenever a game developer issues a patch. Cheaters evolve faster than anti-cheat updates, requiring constant adaptation.

The primary emerging threat that I’ve seen is the rise of “humanized AI models”

Between these two avenues for cheating technology, 2026 will almost certainly see a host of emerging threats, including evolutions of the pillars this article has already touched upon, as well as all new methods of cheating. Developers are encouraged to always stay on their toes and invest into their anti-cheat stacks in order to avoid being on the backfoot against the cheating community.

The primary emerging threat that I’ve seen is the rise of “humanized AI models.” This can be done via physical devices that mimic human inputs to avoid detection, along with deep learning tools that create more sophisticated cheats which adapt to patterns. Rather than creating something with inhuman precision, cheaters are programming their AI bots to make mistakes on purpose in an attempt to replicate human errors. These include intentional jitters, “lazy” aiming, and varied reaction times that enable the AI bot to blend in with legitimate player pools. It doesn’t matter if the cheating player appeared to be playing averagely over the course of the match, as long as they win.

The path forward

Cheating is not solved overnight: it requires constant innovation and adaptation. There is no one anti-cheat solution that blocks all cheats (if there was, the cheating community would have bypassed it years ago). With no perfect solution available, the next best step for developers is to work with tech partners and build out a multi-layered anti-cheat stack. The security industry commonly implements tech stacks into networks in order to deal with cyber criminals, and the same principles apply to gaming: multiple layers of security and prevention are essential.

What this means in practice is several layers of anti-cheat to make sure nothing slips through the cracks. Start with your own bespoke anti-cheat solution or a third-party kernel-based anti-cheat as the first line of defence, and then bolster it by stacking other forms of anti-cheat on top. This should include solutions that:

• use code obfuscation and packing techniques to make the game code difficult to crack;
• encrypt and protect game files and memory from being tampered with;
• use player profiling AI and behavioural scanning to separate legitimate players from cheaters;
• and implement multi-factor authentication and account security.

In addition, make sure any human on the managing side of your online game is aware that suspicious players could be lurking about.

Collaboration is key, with success coming from working together with the gaming community, developers, and studios to ensure fair play. The only players who like cheats in their games are the cheaters themselves, and ultimately they make up a minority of any game’s player base. Most players just want to have fun using their own skills and what the game itself provides, and the industry needs to take whatever steps are required to make that happen.