A CS:GO player has built an AI tool and it’s caught 14,000 cheaters | The Loadout

A CS:GO player has built an AI tool and it’s caught 14,000 cheaters

CSGO FBI on Nuke

November 26, 2019 Following calls for more information about the statistics, 2Eggs has released new information. The case pool now reflects the total number of cases reviewed, reported, and banned.

If you’ve never heard of a thing called HestiaNet in Counter-Strike: Global Offensive, then we don’t blame you. Run by a single pen tester from his main Steam account, the artificial intelligence system, which is named after the Greek Goddess for hearth and fire, has successfully reported over 14,000 players for cheating in the last few months.

And while it’ll take the likes of you and me several minutes to sit through an Overwatch case and work out if ‘The Suspect’ is using CS:GO cheats or not, it only takes HestiaNet a couple of seconds, if that. And that’s because its owner, 2Eggs, who just last month was awarded $11,450 for helping Valve identify bugs and security risks on its platform, has spent hours plying HestiaNet with game demos dating back to 2015, helping her pull apart normal from suspicious behaviour.

Like other deep-learning platforms, HestiaNet gets more intelligent everyday. But while the likes of VACNet and FACEIT’s Minerva have been built by big teams, HestiaNet was built by one teenager in his bedroom in a far corner of the United Kingdom.

“What got me interested in this was the demo John McDonald [Senior Software Engineer at Valve] did back at GDC in 2018,” 2Eggs tells The Loadout. “After that I wanted to see if I could do something but I’d be the one marking harder decisions on whether someone was cheating or not. I only really finished it to a satisfactory point this year.

“I called it HestiaNet because, as you know, CS:GO is infested with cheaters and the Goddess Hestia has a power of healing as well as power of hearth and fire. I want HestiaNet to heal over the games infestation and to get rid of as many cheaters as possible. To many of us in the community, CS:GO is a home, and Hestia is also the protector of the house.”

Although HestiaNet uses 2Eggs’s main account to review Overwatch cases, 2Eggs himself has never had to step in. The system reviews the footage, analyses the data, gives a verdict, and stores the user’s SteamID in a database, which is reviewed occasionally to check for game or VAC bans. If a ban is handed out, HestiaNet makes a note of it, adding information from that specific verdict to her network pool to increase her overall accuracy.

And, well, it’s been pretty effective so far. Out of the 17,659 cases HestiaNet has reviewed, 15,356 of those were reported, and 15,104 have resulted in a ban. The large proportion of these bans are for some sort of cheats, with only 0.5% of the bans being handed out for griefing. Of course, you have to take into account that the majority of accounts flagged for Overwatch review are deemed as suspicious by multiple players, but those are impressive statistics regardless.

“I have to present verdicts that may get someone banned, and having that massive firepower requires you to be really strong about what options you pick,” 2Eggs adds. “I can’t have any favouritism – I have to stay neutral at all times, even if I’m parsing a demo from my own game.”

With more and more gaming-related companies investing in artificial intelligence to weed out cheaters from their games, it won’t be long before technology begins to outrun those invested in the cheat market. And although Valve’s VACNet is catching hundreds of thousands more hackers than 2Eggs and HestiaNet can ever dream of, it really goes to show what one person in their bedroom can do.