Anti.pro (Shadow) - BreakPro Team (New Thread will be posted)

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leontss1

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Anti.pro - BreakPro Development Team

Credit to this Project: iron768, Caicy, Bevelio

-------------------------------------------------------------------------------------------------------
iron768 - Some commands and some checks (Dev)
Bevelio - Helping with the Autoclicker Check (Dev)
Caicy - Sale Manager
leontss1 - Most Checks, Command Design, Configuration, Plugin-Support
-------------------------------------------------------------------------------------------------------

Changes from Normal Shadow:
- A ton new checks including the detection of 10 cps auto clickers, Triggerbots, and some surprises ;)

What Unique Features does Anti.pro offer:
- LQV and FF Neural Networks for some checks (Worked by Bevelio)
- Detection of Reach on low settings (About 3.2 depending on the ping)
- Instant KillAura Detection (1-2 hits for some clients) [If you have been a part of the BreakPro discord, you already know about this check]
- Detection to Vape Lite and Vape Autoclicker (We have a lot of auto clicker checks to check for whatever settings of vape or whatever low-cps auto clicker you might be using)
- Detection to Movement-Hacks on-toggle
- Detection to some AimAssist clients (Alpha but it's working)
- Timer Detection on 1.01 - 1.02 (Only if the TPS of the server is 20-19)
- Limited to no False-Flags
- Data-Collection (Every-Flag that is being sent to the server, it being logged and later used for the same or a different check) [This is not Machine Learning]
- Everything is Configurable

Full-List of Checks:
Jesus (2 checks)
Fly (2 checks)
Ascension (3 checks)
Speed (2 checks)
KillAura (15 checks)
Reach (4 checks)
PME (Spook and Vape)
AutoClicker (6 checks) [Some of them include click-patterns]
Heuristic Analyze (Used to detect some low reach)
AimAssist
AimPattern
Packet Analyzing + Packet Counting
VClip
Phase
NoFall
Glide
AntiKB
Timer
Change (Scaffold and some Fly)
Horizontal Flight
NoSlow
Step
Packet Checks (AuraS - ClickerA - AuraA) [Special Checks]
HitBox
Spook AimAssist / Clicker
Regen
MorePackets
FastBow
Crash (Animation Exploit, Packets, and some more I will not include)

Some Information about the "AC.RIP" fork:
- This is not using any code of AC.RIP in addition to checks or Utility, we are just using some base code of AC.RIP that will be removed in the upcoming updates.

The Completion Level of Checks:
Code:
AutoClicker: 90%
KillAura: 80%
Reach: 95%
Speed: 95%
Fly: 100%
NoFall: 100%
Jesus: 90%
PME: 100%
Machine Learning: 40%
Data-Use: 40%
Crash: 100%
FastBow: 90%
HitBox: 100%
AimAssist: 40%
AimPattern: 10% (Still working on it hard)
AntiKB: 50%
Phase: 90%
VClip: 100%
HClip: 100%
Glide: 40%
Step: 100%
Packet-Checks: 90%

Price: Currently about 30$ - 40$ or even more, haven't decided yet


 
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leontss1

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This isn't better than my hello world project :D na I'm joking gl with your anticheat 1 point tho can you explain more about machine learning

I would not call it Machine Learning, its a Neural Network of Vectors. Feed Forward is mostly use for AutoClickers as they have patterns that are complex. LQV is mostly used on some movement checks as its faster and easier to set-up.

How its working / Going to work:

- There is going to be a command called /anticheat train <player> <check> <legit, hacking>, then, it will take the scalled data of the check. For Example: Your highest reach and your minimum. Then, it will make a log file called reach - nameoftheplayer.txt in a folder called "logs". Then, you can either let it sit there (going to be used by the reach check or any other check you trained), if you are confident enough, you can transfere the values into your config, delete the reach.txt and make it always use that. (Thats happening in the legit option)

- In the hacking option some math is going on getting the value that seems the most un-legit depending on the config you set. Its going to make the txt file as I stated, and we dont recommend you getting it into the config.

How Data-Logging will work:

- When you set off a flag, its gets the scalled data simularly with the Machine Learning, and use this data for the next check thats going to be happening in a schedual. Also, the data is also going to be used on some heavy checks detecting you easier and faster.[DOUBLEPOST=1504124739][/DOUBLEPOST]
Code:
public class Hello {
    public static void main(String[] args){
        System.out.println("Hello, World!");
    }
}
Dude, sick hello world project.

Damn, this is better than whatever I ever coded, thanks for the skid matterial dude ;) XD
 
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a
I would not call it Machine Learning, its a Neural Network of Vectors. Feed Forward is mostly use for AutoClickers as they have patterns that are complex. LQV is mostly used on some movement checks as its faster and easier to set-up.

How its working / Going to work:

- There is going to be a command called /anticheat train <player> <check> <legit, hacking>, then, it will take the scalled data of the check. For Example: Your highest reach and your minimum. Then, it will make a log file called reach - nameoftheplayer.txt in a folder called "logs". Then, you can either let it sit there (going to be used by the reach check or any other check you trained), if you are confident enough, you can transfere the values into your config, delete the reach.txt and make it always use that. (Thats happening in the legit option)

- In the hacking option some math is going on getting the value that seems the most un-legit depending on the config you set. Its going to make the txt file as I stated, and we dont recommend you getting it into the config.

How Data-Logging will work:

- When you set off a flag, its gets the scalled data simularly with the Machine Learning, and use this data for the next check thats going to be happening in a schedual. Also, the data is also going to be used on some heavy checks detecting you easier and faster.[DOUBLEPOST=1504124739][/DOUBLEPOST]

Damn, this is better than whatever I ever coded, thanks for the skid matterial dude ;) XD
LOL thanks for clearing stuff up man I understand what do you mean by machine learning now
 

leontss1

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leontss1 Machine learning? This literally is anticheat.rip v2 isn't it?
 

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Code:
public class Hello {
    public static void main(String[] args){
        System.out.println("Hello, World!");
    }
}
Dude, sick hello world project.
na it has // Codded in 30second in it LOL
 

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leontss1 Machine learning? This literally is anticheat.rip v2 isn't it?

No. AC.RIP never had any based code for any Neural Networks. It was been worked on as Caicy told me.
 
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leontss1

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Well yeah no shit, ac.rip was complete ass.[DOUBLEPOST=1504125071][/DOUBLEPOST]
thx, its lit aye

Well, I only use some of the base of AC.RIP. All checks are mine.
 
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leontss1

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I wonder if it can detect my "vape lite", not vape v2 but vape lite on my super low closet cheater settings.

It can detect 9-20 cps from vape lite.[DOUBLEPOST=1504139276][/DOUBLEPOST]
please stop making fucking anti-cheats

Please stop making Practice Plugins
 
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