The Ultimate Solution for Password Recovery: EK Fluid Works W7000-RM

May 17, 2023 | 3-Min. Read

Andraž Lazič

Password recovery plays a crucial role in the cybersecurity industry, saving customers significant amounts of money and ensuring data security in the digital age. While using the right software is important, having the proper hardware is equally critical for efficient and speedy operations.

The EK Fluid Works W7000-RM liquid-cooled GPU workstation is the ultimate solution in the password recovery market, offering exceptional GPU density, reliable liquid cooling, and unmatched continuous performance. This article delves into the reasons why upgrading to this powerful workstation is a wise choice for your password-cracking endeavors.

Enhancing Cybersecurity and Data Protection

Data protection is a paramount concern in today's world, where a significant portion of our lives unfolds in the digital realm and the cloud. To safeguard our valuable data, whether it be cherished family photos or mission-critical information, passwords are commonly employed. Additionally, administrator access is often fortified with usernames and passwords.

These passwords, along with the data itself in some cases, are encrypted using various algorithms to render them unreadable in the event of a security breach. Further security measures, such as two-factor authentication and physical authentication keys, elevate data protection. Biometric scanners like fingerprint and iris scanners can also be utilized for securing critical data.

The Effectiveness of EK Fluid Works W7000-RM in Password Recovery

All these security measures can be rendered ineffective if users and administrators fail to adhere to protocols, which often leads to massive data breaches through phishing and social engineering tactics. Moreover, human error, such as forgetting passwords, can create situations where specialized knowledge, hardware, and software are required to crack passwords, saving substantial costs or providing evidence for legal proceedings.

Software and Hardware Requirements in Cybersecurity

While the cybersecurity industry encompasses numerous fields, this article focuses specifically on the requirements for offline password cracking. HashCat is one of the most widely used software for unscrambling data, particularly passwords. Since 2015, it has been available as open-source software, benefiting from optimizations and upgrades that harness the immense parallel computational power of modern GPUs.

This allows cybersecurity specialists to achieve significantly higher efficiency and speed compared to using just CPUs or clusters. Paradoxically, gaming GPUs like the NVIDIA GeForce RTX 3090 and 4090 offer the best price-to-performance ratios for this application. However, these GPUs demand substantial power and cooling to sustain high workloads that can span weeks or even months.

Traditional air cooling methods are inadequate for such GPUs. Equipped with large 2- or 3.5-slot air coolers by default to handle thermal dissipation ranging from 350W to 550W, these GPUs cannot be densely deployed in standardized rackmount and tower cases due to their wider-than-standard PCBs. Typically, only two GPUs can be accommodated in a single system, whereas maximizing the number of GPUs is desirable for cost-efficiency and space optimization.

The intensive and prolonged workload further compounds the challenge. When GPUs are loaded with HashCat, core and component temperatures often exceed 90℃, leading to thermal throttling, shutdowns, premature component failure, and substantial time and revenue losses.

Liquid Cooling: The Solution to Unique Requirements

Liquid cooling stands out as the popular solution to overcome the challenges posed by high-density deployment, power consumption, and thermal dissipation. Its superior thermal efficiency and compact water block design effectively address all the previously mentioned issues. By keeping vital components below 60℃, regardless of workload intensity, liquid cooling enables single-slot solutions, allowing up to 7 GPUs per system.