Researchers have demonstrated a method for cracking the Akira ransomware's encryption using sixteen RTX 4090 GPUs. By exploiting a vulnerability in Akira's implementation of the ChaCha20 encryption algorithm, they were able to brute-force the 256-bit encryption key in approximately ten hours. This breakthrough signifies a potential weakness in the ransomware and offers a possible recovery route for victims, though the required hardware is expensive and not readily accessible to most. The attack relies on Akira's flawed use of a 16-byte (128-bit) nonce, effectively reducing the key space and making it susceptible to this brute-force approach.
The blog post details a successful effort to decrypt files encrypted by the Akira ransomware, specifically the Linux/ESXi variant from 2024. The author achieved this by leveraging the power of multiple GPUs to significantly accelerate the brute-force cracking of the encryption key. The post outlines the process, which involved analyzing the ransomware's encryption scheme, identifying a weakness in its key generation (a 15-character password), and then using Hashcat with a custom mask attack on the GPUs to recover the decryption key. This allowed for the successful decryption of the encrypted files, offering a potential solution for victims of this particular Akira variant without paying the ransom.
Several Hacker News commenters expressed skepticism about the practicality of the decryption method described in the linked article. Some doubted the claimed 30-minute decryption time with eight GPUs, suggesting it would likely take significantly longer, especially given the variance in GPU performance. Others questioned the cost-effectiveness of renting such GPU power, pointing out that it might exceed the ransom demand, particularly for individuals. The overall sentiment leaned towards prevention being a better strategy than relying on this computationally intensive decryption method. A few users also highlighted the importance of regular backups and offline storage as a primary defense against ransomware.
ArkFlow is a high-performance stream processing engine written in Rust, designed for building and deploying real-time data pipelines. It emphasizes low latency and high throughput, utilizing asynchronous processing and a custom memory management system to minimize overhead. ArkFlow offers a flexible programming model with support for both stateless and stateful operations, allowing users to define complex processing logic using familiar Rust syntax. The framework also integrates seamlessly with popular data sources and sinks, simplifying integration with existing data infrastructure.
Hacker News users discussed ArkFlow's performance claims, questioning the benchmarks and the lack of comparison to existing Rust streaming engines like tokio-stream. Some expressed interest in the project but desired more context on its specific use cases and advantages. Concerns were raised about the crate's maturity and potential maintenance burden due to its complexity. Several commenters noted the apparent inspiration from Apache Flink, suggesting a comparison would be beneficial. Finally, the choice of using async for stream processing within ArkFlow generated some debate, with users pointing out potential performance implications.
Polars, known for its fast DataFrame library, is developing Polars Cloud, a platform designed to seamlessly run Polars code anywhere. It aims to abstract away infrastructure complexities, enabling users to execute Polars workloads on various backends like their local machine, a cluster, or serverless environments without code changes. Polars Cloud will feature a unified API, intelligent query planning and optimization, and efficient data transfer. This will allow users to scale their data processing effortlessly, from laptops to massive datasets, all while leveraging Polars' performance advantages. The platform will also incorporate advanced features like data versioning and collaboration tools, fostering better teamwork and reproducibility.
Hacker News users generally expressed excitement about Polars Cloud, praising the project's ambition and the potential of combining Polars' performance with distributed computing. Several commenters highlighted the cleverness of leveraging existing cloud infrastructure like DuckDB and Apache Arrow. Some questioned the business model's viability, particularly regarding competition with established cloud providers and the potential for vendor lock-in. Others raised technical concerns about query planning across distributed systems and the challenges of handling large datasets efficiently. A few users discussed alternative approaches, such as using Dask or Spark with Polars. Overall, the sentiment was positive, with many eager to see how Polars Cloud evolves.
DeepSeek's smallpond extends DuckDB, the popular in-process analytical database, with distributed computing capabilities. It leverages a shared-nothing architecture where each node holds a portion of the data, allowing for parallel processing of queries across a cluster. Smallpond introduces a distributed query planner that optimizes query execution by distributing tasks and aggregating results efficiently. This empowers DuckDB to handle larger-than-memory datasets and significantly improves performance for complex analytical workloads. The project aims to make distributed computing accessible within the familiar DuckDB environment, retaining its ease of use and performance characteristics for larger-scale data analysis.
Hacker News commenters generally expressed excitement about the potential of combining DeepSeek's distributed computing capabilities with DuckDB's analytical power. Some questioned the performance implications and overhead of such a distributed setup, particularly concerning query planning and data transfer. Others raised concerns about the choice of Raft consensus, suggesting alternative distributed consensus algorithms might be more performant. Several users highlighted the value proposition for data lakes, allowing direct querying without complex ETL pipelines. The discussion also touched on the competitive landscape, comparing the approach to existing solutions like Presto and Spark, with some speculating on potential acquisition scenarios. A few commenters shared their positive experiences with DuckDB's speed and ease of use, further reinforcing the appeal of this integration. Finally, there was curiosity around the specifics of DeepSeek's technology and its impact on DuckDB's licensing.
Par is a new programming language designed for exploring and understanding concurrency. It features a built-in interactive playground that visualizes program execution, making it easier to grasp complex concurrent behavior. Par's syntax is inspired by Go, emphasizing simplicity and readability. The language utilizes goroutines and channels for concurrency, offering a practical way to learn and experiment with these concepts. While currently focused on concurrency education and experimentation, the project aims to eventually expand into a general-purpose language.
Hacker News users discussed Par's simplicity and suitability for teaching concurrency concepts. Several praised the interactive playground as a valuable tool for visualization and experimentation. Some questioned its practical applications beyond educational purposes, citing limitations compared to established languages like Go. The creator responded to some comments, clarifying design choices and acknowledging potential areas for improvement, such as error handling. There was also a brief discussion about the language's syntax and comparisons to other visual programming tools.
Isaac Jordan's blog post introduces "data branching," a technique for optimizing batch job systems, particularly those involving large datasets and complex dependencies. Data branching creates a directed acyclic graph (DAG) where nodes represent data transformations and edges represent data dependencies. Instead of processing the entire dataset through each transformation sequentially, data branching allows for parallel processing of independent branches. When a branch's output needs to be merged back into the main pipeline, a merge node combines the branched data with the main data stream. This approach minimizes unnecessary processing by only applying transformations to relevant subsets of the data, resulting in significant performance improvements for specific workloads while retaining the simplicity and familiarity of traditional batch job systems.
Hacker News users discussed the practicality and complexity of the proposed data branching system. Some questioned the performance implications, particularly the cost of copying potentially large datasets, suggesting alternatives like symbolic links or copy-on-write mechanisms. Others pointed out the existing solutions like DVC (Data Version Control) that offer similar functionality. The need for careful garbage collection to manage the branched data was also highlighted, with concerns about the potential for runaway storage costs. Several commenters found the core idea intriguing but expressed reservations about its implementation complexity and the potential for debugging challenges in complex workflows. There was also a discussion around alternative approaches, such as using a database designed for versioned data, and the potential for applying these concepts to configuration management.
Summary of Comments ( 11 )
https://news.ycombinator.com/item?id=43387188
Hacker News commenters discuss the practicality and implications of using RTX 4090 GPUs to crack Akira ransomware. Some express skepticism about the real-world applicability, pointing out that the specific vulnerability exploited in the article is likely already patched and that criminals will adapt. Others highlight the increasing importance of strong, long passwords given the demonstrated power of brute-force attacks with readily available hardware. The cost-benefit analysis of such attacks is debated, with some suggesting the expense of the hardware may be prohibitive for many victims, while others counter that high-value targets could justify the cost. A few commenters also note the ethical considerations of making such cracking tools publicly available. Finally, some discuss the broader implications for password security and the need for stronger encryption methods in the future.
The Hacker News post titled "Akira ransomware can be cracked with sixteen RTX 4090 GPUs in around ten hours" has generated several comments discussing the implications of using powerful GPUs like the RTX 4090 for cracking encryption.
Some users express skepticism about the practicality of this approach. One commenter questions the feasibility for average users, pointing out the significant cost of acquiring sixteen RTX 4090 GPUs. They suggest that while technically possible, the financial barrier makes it unlikely for most victims of ransomware. Another user echoes this sentiment, highlighting that the cost would likely exceed the ransom demand in many cases. They also raise the point that this method might only work for a specific vulnerability in Akira and wouldn't be a universal solution for all ransomware.
Others discuss the broader implications of readily available GPU power. One comment points out the increasing accessibility of powerful hardware and its potential to empower both security researchers and malicious actors. They argue that this development underscores the ongoing "arms race" in cybersecurity, where advancements in technology benefit both sides. Another user suggests that this highlights the importance of robust encryption practices, as the increasing power of GPUs could eventually render weaker encryption methods vulnerable.
A few comments delve into the technical aspects. One user questions the specific algorithm used by Akira and speculates on its susceptibility to brute-force attacks. Another user mentions the importance of key length and how it affects the time required for cracking, emphasizing that longer keys would significantly increase the difficulty even with powerful GPUs.
One commenter points out the article's potentially misleading title. They clarify that the GPUs weren't cracking the encryption itself, but rather brute-forcing a password which was then used to decrypt the files. This distinction is important, as it implies a weakness in the implementation rather than the underlying encryption algorithm.
Finally, a few users offer practical advice. One suggests using strong, unique passwords to protect against this type of attack, emphasizing the importance of basic security hygiene. Another user proposes that the best defense against ransomware remains regular backups, allowing victims to restore their data without paying the ransom.
Overall, the comments reflect a mix of concerns about the practical implications of using GPUs for cracking ransomware, discussions about the broader cybersecurity landscape, and technical insights into the vulnerabilities highlighted by this specific case.