Text-based Captchas have been widely deployed across the Internet to defend against undesirable or malicious bot programs. Many attacks have been proposed; these fine prior art advanced the scientific understanding of Captcha robustness, but most of them have a limited applicability. In this paper, we report a simple, low-cost but powerful attack that effectively breaks a wide range of text Captchas, each with distinct design features, including those deployed by Google, Microsoft, Yahoo!, Amazon and other Internet giants. For most of the schemes, our attack achieved a success rate ranging from 16% to 77%, and achieved an average speed of solving a puzzle in less than 15 seconds on a standard desktop computer (with a 3.3GHz Intel Core i3 CPU and 2 GB RAM). To the best of our knowledge, this is to date the simplest generic attack on text Captchas. Our attack is based on Log-Gabor filters; a famed application of Gabor filters in computer security is John Daugman's iris recognition algorithm. Our work is the first to apply Gabor filters for breaking Captchas. Haichang Gao (Xidian University), Jeff Yan (Lancaster University), Fang Cao, Zhengya Zhang, Lei Lei, Mengyun Tang, Ping Zhang, Xin Zhou, Xuqin Wang and Jiawei Li (Xidian University) You are a Game Bot!: Uncovering Game Bots in MMORPGs via Self-similarity in the Wild Game bots are a critical threat to Massively Multiplayer Online Role-Playing Games (MMORPGs) because they can seriously damage the reputation and in-game economy equilibrium of MMORPGs. Existing game bot detection techniques are not only generally sensitive to changes in game contents but also limited in detecting emerging bot patterns that were hitherto unknown. To overcome the limitation of learning bot patterns over time, we propose a framework that detects game bots through machine learning technique. The proposed framework utilizes self-similarity to effectively measure the frequency of repeated activities per player over time, which is an important clue to identifying bots. Consequently, we use real world MMORPG (“Lineage”, “Aion” and “Blade & Soul”) datasets to evaluate the feasibility of the proposed framework. Our experimental results demonstrate that 1) self-similarity can be used as a general feature in various MMORPGs, 2) a detection model maintenance process with newly updated bot behaviors can be implemented, and 3) our bot detection framework is practicable.