It appears that the market for illegal game programs in China is nearing a staggering 2 trillion won.

This revelation comes courtesy of the 2025 Game Security White Paper, recently published by Tencent ACE (Anti-Cheat Expert). According to the report, the Chinese gaming market generated 350.789 billion yuan (approximately 80 trillion won) in 2025, with the player base ballooning past 683 million users. Revenue from Chinese-developed titles abroad also hit a record high of 20.4 billion dollars (roughly 31 trillion won).

However, this market expansion has come with a rather dark shadow: the illegal program industry is growing in lockstep. The white paper estimates the value of this illicit trade in China at around 2 trillion won. This includes everything from the sale of cheat software and compromised accounts to boosting services and automated botting for in-game currency.

In the old days, illicit activities were mostly about buying hacks, but the market has evolved into a 'service' model. Users no longer need to install dodgy software; instead, they simply pay a provider who logs in via a dedicated environment to do the dirty work for them. The white paper calls this 'CaaS (Cheating as a Service)' and highlights it as a critical hurdle for maintaining fair play.

The report also points out that the proliferation of Large Language Models (LLMs) and generative AI has made crafting cheats a breeze. Indeed, the number of illegal programs has skyrocketed; in 2025, the count for PC-based cheats rose by roughly 124% year-on-year to 138,395. The number of individual cheat functions saw an even more dramatic 277% surge, hitting 592,222.

When breaking it down by genre, shooter cheats account for a whopping 81.9% of the total, followed by action games at 11.8%. Mobile gaming hasn't been spared either, with illegal programs jumping 117.3% to 230,677. These bad actors are now deploying AI bots that mimic actual human input rhythms and conversation, making them devilishly difficult to detect.

As for countermeasures, the white paper suggests using AI to analyse replay data, flagging inputs or decisions that defy normal player behaviour. Furthermore, they are pushing for deep learning systems to map out the habits and transaction flows of illegal service providers, aiming to build a more robust environment to catch these bad actors in the act.