A Diablo IV speedrunner's world record was debunked by hackers who modified the game to replicate the supposedly impossible circumstances of the run. They discovered the runner, who claimed to have benefited from extremely rare item drops and enemy spawns, actually used a cheat to manipulate the game's random number generator, making the fortunate events occur on demand. This manipulation, confirmed by analyzing network traffic, allowed the runner to artificially inflate their luck and achieve an otherwise statistically improbable clear time. The discovery highlighted the difficulty of verifying speedruns in online games and the lengths some players will go to fabricate records.
The author details their complex and manual process of scraping League of Legends match data, driven by a desire to analyze their own gameplay. Lacking a readily available API for detailed match timelines, they resorted to intercepting and decoding network traffic between the game client and Riot's servers. This involved using a proxy server to capture the WebSocket data, meticulously identifying the relevant JSON messages containing game events, and writing custom parsing scripts in Python. The process was complicated by Riot's obfuscation techniques and frequent changes to the game, requiring ongoing adaptation and reverse-engineering. Ultimately, the author succeeded in extracting the data, but acknowledges the fragility and unsustainability of this method.
HN commenters generally praised the author's dedication and ingenuity in scraping League of Legends data despite the challenges. Several pointed out the inherent difficulty of scraping data from games, especially live service ones like LoL, due to frequent updates and anti-scraping measures. Some suggested alternative approaches like using the official Riot Games API, though the author explained their limitations for his specific needs. Others shared their own experiences and struggles with similar projects, highlighting the common pain points of maintaining scrapers. A few commenters expressed interest in the data itself and potential applications for analysis and research. The overall sentiment was one of appreciation for the author's persistence and the technical details shared.
The blog post explores using linear programming to optimize League of Legends character builds. It frames the problem of selecting items to maximize specific stats (like attack damage or ability power) as a linear program, where item choices are variables and stat targets are constraints. The author details the process of gathering item data, formulating the linear program, and solving it using Python libraries. They showcase examples demonstrating how this approach can find optimal builds based on desired stats, including handling gold constraints and complex item interactions like Ornn upgrades. While acknowledging limitations like the exclusion of active item effects and dynamic gameplay factors, the author suggests the technique offers a powerful starting point for theorycrafting and understanding item efficiency in League of Legends.
HN users generally praised the approach of using linear programming for League of Legends item optimization, finding it clever and interesting. Some expressed skepticism about its practical application, citing the dynamic nature of the game and the difficulty of accurately modeling all variables, like player skill and enemy team composition. A few pointed out existing tools that already offer similar functionality, like Championify and Probuilds, though the author clarified their focus on exploring the optimization technique itself rather than creating a fully realized tool. The most compelling comments revolved around the limitations of translating theoretical optimization into in-game success, highlighting the gap between mathematical models and the complex reality of gameplay. Discussion also touched upon the potential for incorporating more dynamic factors into the model, like build paths and counter-building, and the ethical considerations of using such tools.
Summary of Comments ( 27 )
https://news.ycombinator.com/item?id=43058522
Hacker News commenters largely praised the technical deep-dive in uncovering the fraudulent Diablo speedrun. Several expressed admiration for the hackers' dedication and the sophisticated tools they built to analyze the game's network traffic and memory. Some questioned the runner's explanation of "lag" and found the evidence presented compelling. A few commenters debated the ethics of reverse-engineering games for this purpose, while others discussed the broader implications for speedrunning verification and the pressure to achieve seemingly impossible records. The general sentiment was one of fascination with the detective work involved and disappointment in the runner's actions.
The Hacker News post titled "Diablo hackers uncovered a speedrun scandal" has generated a robust discussion with several compelling comments. Many commenters focus on the technical details of the exploit and the detective work involved in uncovering it.
One commenter delves into the specifics of the "rubberbanding" exploit, explaining how manipulating the game's netcode could create the illusion of faster movement. They highlight the complexity of identifying and proving this manipulation, praising the hackers for their meticulous analysis. This comment receives several replies further discussing the technicalities and implications for online gaming security.
Another commenter emphasizes the broader significance of the incident, drawing parallels to financial fraud and highlighting how seemingly minor exploits can have substantial consequences. They argue that the dedication shown by the community in uncovering this cheat demonstrates the importance of integrity in competitive environments, even in gaming.
Several comments discuss the ethical implications of reverse engineering and hacking games, even for seemingly positive purposes like uncovering cheating. Some argue that while the outcome was positive in this case, such actions could be misused in other contexts. This sparks a debate about the boundaries of acceptable game modification and the responsibility of players in maintaining fair play.
Some users express skepticism about the speedrunner's claims of ignorance, suggesting that the complexity of the exploit makes it unlikely to have been unintentional. Others defend the speedrunner, pointing out that even experienced players might not fully understand the intricacies of game netcode.
A few comments also touch upon the broader culture of speedrunning, with some arguing that the pressure to achieve record times can incentivize cheating. They suggest that the community needs to implement stricter verification processes to prevent similar incidents in the future.
Finally, some commenters express admiration for the collaborative effort and technical expertise demonstrated by the individuals who uncovered the cheat. They view this incident as a testament to the power of community-driven investigation and the importance of transparency in competitive gaming.