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Let's Talk Online Poker: Cheating and Counter-Measures Unveiled
Online poker has become a battleground, with cheaters trying to exploit the system and security personnel fighting back. They're constantly innovating, advancing their tactics to stay one step ahead. So, how do we battle this emerging threat?
John A. Dive in, buddy! Back in the day, PokerStars was the epitome of security, and combating bots was relatively straightforward. Contextual detection, monitoring mouse clicks and running programs during the game, was sufficient then. But recent events, like the Russian bot army exposed in Bloomberg, have taken things to a whole new level. Whole corporations are now manufacturing bots, constantly refining their product. It's a never-ending chase between them and the room's security teams.
Bloomberg: Russian Bot Army Invades Online Poker Read MoreA Bloomberg article about Siberian bots in online poker features many familiar faces in the scene.
Read MoreBot creators are pouring resources not just into bypassing security protocols but also into improving their gameplay. Many still believe GTO bots pose the most significant threat. However, this couldn't be further from the truth.
Thanh T. The deal is, it's impossible to create an AI that always plays perfect poker. Current bots still have a strong human influence, emanating from manual programming and human expertise. They've made significant strides in the past decade, thanks to technological advancements and immense investments. We've analyzed the play of different bots, and it's far from GTO.
John A. The goal of a solver is to solve the Nash equation, but a bot's goal is quite different. They aim to make as much money as possible under the given conditions. This focus on field exploitation, rather than pursuit of perfect play, makes them a menacing opponent.
Fully-automated bots pose the most significant threat because they drain the most money from the system. They can easily exploit the field and, due to their numbers, win big. RTA (Remote Till Assistance) is less common, typically used by individual players. Although it's still a big problem—for instance, a high-stakes player employing such software can significantly boost their winrate—it can't rival the financial impact of bot farms that run entire armies of low-limit bots.
Thanh T. Sadly, the reality is glaringly clear. Many rooms are indeed infested with bot armies. All the chatter on forums lately seems to be true.
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Joe I. So, how do we combat all this?
Thanh T. Fighting bots is complex, as many operators lack the incentive. Small rooms spring up, only interested in quick profits, not long-term successful operations. Large networks are keen on battling bots but prioritize other aspects, such as attracting players, client convenience, etc. As a result, they often neglect essential data collection, machine learning infrastructure—all crucial components for effective bot-fighting. Our role is to persuade operators that it's in their best interest.
Technically, it's all about data collection. Apart from contextual bot detection, there's a method based on analyzing their gameplay. We advocate combining these methods to efficiently differentiate bots from humans. The more data we acquire about their strategies, the easier it becomes.
John A. Contextual detection is employed by game developers to combat cheaters, but poker has come up with ways to bypass it. No external software can operate on the computer where the client is installed. Gameplay cannot be concealed, so it's our top priority. As Thanh pointed out, we analyze mammoth databases to grasp human play. People are predictable in their habits. We collect data on regular and occasional players and implement algorithms to instantly identify any software or cheat tool use.
Joe I. If you notice suspicious behavior in a player's actions, what happens next?
John A. Investigation ensues, just like any other. Sometimes, cheaters are so brazen, there's little to question. However, some rooms even ignore such cases.
Thanh T. Some players don't care about bots at all. Others employ contextual detection to identify RTA or VPN but rarely engage in gameplay analysis due to its complexity. We've engineered our own solvers, use AI support, and designed algorithms to spot bot, GTO, or exploit playing patterns. It's an enormously arduous technological task.
Joe I. Can you explain what exploitative bots are?
Thanh T. As mentioned, exploitative bots have been the most detrimental to the poker world. They're designed by poker players, with GTO as the foundation, but such designs must deviate from ideal play to maximize winnings. Both players and bots adapt differently, but there are consistent patterns that remain prevalent.
Currently, there's quite a conundrum—distinguishing human-made content from AI-generated content. This topic is undergoing intensive research. Experts concede it's a difficult but solvable dilemma. In essence, AI actions have less randomness compared to human decisions. To discern human exploits from bots, we analyze several technical indicators, including stability and impulsivity.
Joe I. If bots occasionally make losing moves deliberately, will that complicate your task?
Thanh T. If you want to be identified, simply play poorly. But if you're not making profits, no one will look for you. The more random a bot's actions, the worse its results. To generate income, one must play according to certain patterns. These patterns exhibit distinctive technical attributes that differ greatly from human patterns.
John A. If a bot intentionally makes mistakes but still wins significantly more than regular players, it's not an intelligent strategy to avoid detection.
Joe I. Google recently introduced an AI bot that reads information from your screen and provides real-time advice. What effect will this have on poker?
Thanh T. All recent technological advancements in AI have little to do with poker. Poker bot and solver creators employ entirely different methods, unrelated to mainstream bots like ChatGPT.
John A. I concur. While it's unlikely that AI advancements will enhance cheaters' software, they may still bring additional headaches. For example, AI could aid cheaters in bypassing contextual detection or manufacturing documents during verification. I anticipate issues in this area in the future.
Joe I. Chamath Palihapitiya recently predicted the imminent death of online poker due to AI development. Are you concerned about this?
Billionaire Predicts Imminent Demise of Online Poker. Visionary or Alarmist? ReadFormer Facebook executive and avid poker player, as well as Phil Hellmuth's close friend, Chamath Palihapitiya assumes that due to AI development, we're may be witnessing the final days of online poker. Regulars react negatively.
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Thanh T. What he says is a natural evolution. If you want to adapt to the next world faster, you'll need to prepare for AI becoming an integral part of life soon, no matter what your profession—doctor or poker player. But this mainly pertains to learning with AI, not its practical implementation. AI facilitates work, so you'll simply lag behind those who master new technologies first.
Who knows, perhaps it may also contribute to online poker security or diversify formats to attract new players in the future.
Joe I. Another significant issue is false cheating accusations. How can we protect players from this?
John A. There should always be a right to appeal. PokerStars, along with other rooms, asks players to submit session recordings along with explanations of their actions. Sometimes, asking a player a few simple questions, such as their open-raise range, is sufficient.
John A. On our end, we can only pledge full transparency in our collaboration with the rooms. Typically, only bits and pieces of information reach the public. This is also the norm in the computer gaming industry, where combating cheaters is rarely discussed. I believe poker operators, too, could benefit from transparency. I personally know high-stakes players who have abandoned online play due to a lack of trust in the rooms.
I now believe that rooms cannot assure 100% safety. But when cheaters are caught, it should be shared—who, for what, how much money was confiscated, who received compensation, etc. This would boost trust levels.
- Online poker has turned into a battlefield with cheaters trying to manipulate the system and security personnel constantly innovating to keep up.
- John A. discusses the evolution of cheating in online poker, describing how simple detection methods used by PokerStars in the past are no longer effective in the face of sophisticated bot manufacturers.
- Thanh T. explains that while AI bots have made significant strides, they still contain a human element and do not play perfect poker.
- The discussion then focuses on the goals of bots, which are to make as much money as possible under the given conditions, rather than achieving perfect play.
- It is noted that fully-automated bots pose the most significant threat as they drain the most money from the system, while RTA is less common and used by individual players.
- The reality of bot infestation in many online poker rooms is acknowledged, with players outraged, rooms rolling out challenges to combat the issue, and continuous bot presence.
- The importance of data collection and analysis in the fight against bots is emphasized, with the suggestion that a combination of contextual bot detection and gameplay analysis would be effective in differentiating bots from humans.
