Slow Pisces is a North Korean state-sponsored threat actor that has developed a sophisticated campaign targeting cryptocurrency developers, primarily via LinkedIn. The group impersonates recruiters and sends malicious coding challenges disguised as legitimate project tasks. These challenges contain malware payloads, specifically RN Loader and RN Stealer, which are designed to infect the victim's system stealthily. The malware is delivered through GitHub repositories that leverage adapted open-source projects written in Python and JavaScript. A notable technical aspect of the malware is its use of YAML deserialization and EJS (Embedded JavaScript) rendering techniques to execute arbitrary code fetched from command-and-control (C2) servers. This approach enables dynamic and flexible execution of malicious code, increasing the difficulty of detection and analysis. Slow Pisces has demonstrated operational security by ensuring that payloads exist only in memory and are deployed selectively, reducing forensic footprints and complicating incident response efforts. The group has reportedly stolen over $1 billion from the cryptocurrency sector in 2023 using multiple attack vectors, including fake trading applications and supply chain compromises. The campaign's focus on cryptocurrency developers suggests a targeted approach to compromise individuals with access to valuable digital assets or development environments that could be leveraged for further attacks.

For European organizations, especially those involved in cryptocurrency development, blockchain technology, and fintech sectors, Slow Pisces poses a significant threat. Successful compromise can lead to theft of sensitive credentials, intellectual property, and direct financial losses through stolen cryptocurrency assets. The use of memory-resident payloads and selective deployment complicates detection and mitigation, increasing the risk of prolonged undetected intrusions. Additionally, the exploitation of developer environments can lead to supply chain risks, where compromised code or tools propagate malware further into the ecosystem. The campaign's social engineering vector via LinkedIn also raises concerns about insider threats and the difficulty of preventing initial infection. Given the increasing adoption of cryptocurrency technologies across Europe, organizations may face reputational damage, regulatory scrutiny, and financial penalties if breaches occur. The threat also underscores the risk to European software supply chains, which could have cascading effects on broader IT infrastructure and services.

1. Implement strict verification procedures for recruitment and project-related communications on professional networks like LinkedIn, including validating the identity of recruiters and the legitimacy of coding challenges before engagement. 2. Enforce application whitelisting and runtime application self-protection (RASP) to detect and block unauthorized execution of code, especially focusing on scripts that perform YAML deserialization and EJS rendering. 3. Deploy advanced endpoint detection and response (EDR) solutions capable of identifying memory-resident malware and anomalous behaviors associated with RN Loader and RN Stealer. 4. Conduct regular security training for developers emphasizing the risks of social engineering, especially via professional networking platforms, and the dangers of executing unvetted code from external sources. 5. Monitor GitHub repositories and other code-sharing platforms for suspicious or unauthorized forks and projects that may be used as malware delivery vectors. 6. Implement network segmentation and strict egress filtering to limit communication with known or suspected command-and-control servers. 7. Use multi-factor authentication (MFA) and robust credential management to reduce the impact of stolen credentials. 8. Regularly audit and harden software supply chains, including dependency management and code review processes, to detect and prevent the introduction of malicious code.