Github Aimbot Top !!exclusive!! May 2026

Based on trending repositories and recent updates as of early 2026, here are some of the most notable "top" aimbot and AI-assisted aim projects on GitHub.

These projects predominantly leverage machine learning (computer vision) for target detection, minimizing memory reading to avoid anti-cheat detection. Top AI-Based Aimbot Projects (2026)

RootKit-Org/AI-Aimbot: Marketed as a "World's Best AI Aimbot," this repository is tailored for major FPS titles like CS2, Valorant, Fortnite, and Apex Legends, focusing on AI-driven screen analysis.

McDaived/AIMi: An AI aimbot that utilizes real-time object detection and neural networks, designed to mimic human aiming patterns.

ReksarGames/RN_AI: A comprehensive aimbot project geared toward FPS/TPS games, utilizing CUDA and TensorRT for GPU-accelerated targeting.

BinAlexme/NeuralBot: A specialized "pixel bot" utilizing a convolutional neural network (YOLOv4-tiny) for pixel-based targeting.

ttwizz/Open-Aimbot: A popular universal aim assist framework. Top Roblox Specific Aimbots github aimbot top

Exunys/Aimbot-V3: The latest version of the popular,, and highly active Roblox script-based aimbot, offering improved speed and reduced detection risk. Key Trends & Technologies

AI/Machine Learning: The shift away from reading memory to "pixel bot" techniques (using neural networks to read the screen) is standard in modern aimbot development to evade detection.

GPU Acceleration: Many of the top repositories rely on CUDA/TensorRT to achieve fast inference times.

Anti-Cheat Risks: While these are popular, they are often detected by modern engines, and their usage violates the terms of service of most competitive games, with severe penalties for usage.

Disclaimer: This information is for educational purposes regarding software development and AI training on GitHub. Using cheating software violates game terms of service and can lead to permanent bans. Exunys/Aimbot-V3: Universal ROBLOX Aimbot Module - GitHub

GitHub hosts a variety of "aimbot" projects, primarily categorized into AI-powered computer vision tools and traditional memory-based cheats. While many are shared for educational purposes, using them in live matches typically violates game Terms of Service and can lead to permanent account bans. Popular GitHub Aimbot Categories Based on trending repositories and recent updates as

Type B: The Computer Vision Aimbot (Python / OpenCV / YOLO)

How it works: This script does not touch game memory. It takes a screenshot of your monitor, uses a neural network (often pre-trained) to detect enemy outlines, and then physically moves your mouse cursor to the enemy’s bounding box.

Found on GitHub as: "Python AutoAim," "Color Aimbot No Memory."

Why this is often the "top" search result:

• Undetectable by game anti-cheats (since it reads the screen like a human does).
• Written in Python (Easy to read and modify).
• Runs on external hardware (Arduino or Raspberry Pi).

The catch: It is slower than memory-based cheats because it relies on screen capture FPS (usually 30-60 FPS vs. the game’s 240 FPS).

2. Methodology

To define the "top" repositories, this study utilizes key metrics available on the GitHub platform:

• Stars: A metric of community approval and popularity.
• Forks: An indicator of active development and modification by other users.
• Activity: Frequency of commits and issue discussions.

Repositories were categorized by their underlying detection and actuation methods. The analysis excludes malware-infected impostor repositories and focuses on legitimate open-source projects that are frequently referenced within the game security community. Type B: The Computer Vision Aimbot (Python /

4.2. Heuristics and Behavioral Analysis

Since memory-based cheats are easily detected via signature scanning, the shift toward AI and Color aimbots forces anti-cheat developers to rely on behavioral analysis (statistical anomalies in mouse movement) and visual capture detection. Open-source projects combat this by introducing "humanization" algorithms—randomizing mouse path curvature and reaction times to mimic organic human input.

Part 3: The Most Popular Repositories (A Historical Analysis)

While specific URLs change daily due to takedowns, the "top" GitHub aimbot repositories consistently fall into a few legendary categories. Let's review the archetypes you will encounter.

1. The "External ESP + Aimbot" (C#, ImGui)

• Stars: 500–2,000 (before deletion)
• Visuals: Overlay boxes, health bars, distance text.
• Aim: Silent aim (visual only) or standard auto-lock.
• Risk: High – Easy to signaturize by Easy Anti-Cheat (EAC).

2. The "Python OpenCV Triggerbot"

• Stars: 1,500–4,000 (These survive longer because they are gray-area).
• Logic: Detects a specific RGB color (e.g., enemy red name tag). When the crosshair turns red, it clicks.
• Best for: Valorant, Overwatch 2, CS2.
• Limitation: Cannot aim around corners or predict movement.

3. The "Linux Internal" (LD_PRELOAD hooks)

• Stars: Moderate (300–800)
• Why it is top: Many anti-cheats (like Vanguard) are weaker on Linux/Steam Deck.
• Mechanism: Hooks OpenGL or Vulkan draw calls to render cheats.

3. The Driver Exploit (Ring0)

The truly "top" aimbots (the ones that work on Valorant or Warzone) use a Kernel driver. When you look at the source code for these, you aren't just seeing an aimbot; you are seeing a rootkit. The code exploits vulnerable drivers (often old motherboard drivers) to read and write kernel memory.