Rust and Go Malware: Cross-Platform Threats Evading Traditional Defenses 🦀

The cybersecurity landscape is experiencing a fundamental shift as threat actors abandon traditional programming languages in favor of modern alternatives. Rust and Go have emerged as the languages of choice for sophisticated cybercriminals, fundamentally challenging how security teams detect and respond to malware. According to recent threat intelligence from Bitsight, cross-platform malware written in these languages is becoming standard practice among emerging threat actors, marking a new era in the evolution of cyber threats.

The Rise of Modern Programming Languages in Malware Development

The transition from C and C++ to Rust and Go represents more than a simple technological upgrade. These modern languages offer cybercriminals a powerful combination of performance, cross-platform compatibility, and inherent anti-analysis features that make traditional security defenses significantly less effective.

Research from 2025 reveals that malware authors are systematically migrating their toolkits to these newer languages. Ransomware groups including BlackCat, Hive, RansomExx, and the Agenda collective have all deployed Rust-based variants of their malware. The Hive ransomware operators even rewrote their entire payload from Go to Rust, demonstrating the strategic value they see in the language’s capabilities.

The numbers tell a compelling story. In 2019, researchers identified approximately 13,000 unique malware samples written in Go. By 2024, multiple security firms reported growth exceeding 2,000 percent in Go-based malware detections. Rust adoption, while starting later, is accelerating even faster as threat actors recognize its advantages.

Why Cybercriminals Are Choosing Rust and Go

Cross-Platform Dominance

Both Rust and Go excel at creating truly portable malware. Developers can write code once and compile it for Windows, Linux, and ESXi systems with minimal modifications. The Luna ransomware group leverages this capability to simultaneously target multiple operating systems with a single codebase. This efficiency is particularly valuable in ransomware operations where maximizing impact across diverse infrastructure is essential.

Recent incidents demonstrate this versatility in action. The ReaderUpdate malware loader platform has been observed deploying variants written in Crystal, Nim, Rust, and Go across macOS systems. Threat actors are also targeting ESXi virtual machines, which host critical enterprise workloads, using cross-platform ransomware that can pivot seamlessly between host and guest operating systems.

Evasion of Signature-Based Detection

Traditional antivirus and endpoint protection solutions rely heavily on signature databases built over decades of analyzing C and C++ malware. Rust and Go binaries present fundamentally different structures that evade these detection mechanisms. Static analysis tools struggle to parse the unique compilation artifacts these languages produce, particularly Rust’s aggressive compiler optimizations and Go’s statically linked libraries.

Security researchers have documented that automated malware analysis tools produce significantly more false positives and false negatives when examining Rust-compiled binaries compared to traditional languages. This detection gap provides threat actors with a critical operational advantage during the initial stages of an attack.

Reverse Engineering Complexity

The difficulty of analyzing Rust and Go malware represents perhaps their most significant advantage to cybercriminals. SentinelOne researchers have stated that with current tooling, Rust is “practically impossible to reverse engineer,” leading many security analysts to avoid investigating Rust-based threats entirely.

Rust binaries are substantially larger than their C counterparts—often double the size—because they statically link dependencies at compile time. A comparative analysis showed a simple C malware executable measuring 71.7 kilobytes while the functionally identical Rust version reached 151.5 kilobytes. This size difference, combined with aggressive function inlining and optimization, creates a perplexing code structure that surpasses even C++ in abstraction complexity.

Go presents similar challenges. The language embeds all necessary libraries directly into compiled binaries and obscures function name recovery, making debugging extraordinarily difficult for malware researchers. Popular reverse engineering tools like IDA Free and Ghidra historically struggled to disassemble these binaries effectively, though recent updates have begun addressing some limitations.

Memory Safety and Performance

Ironically, the same security features that make Rust attractive for legitimate software development also benefit malware authors. Rust’s memory safety guarantees eliminate entire classes of vulnerabilities that could be exploited to detect or disable malware. The Android development team reported that after transitioning to Rust, memory safety issues dropped from 76 percent of vulnerabilities in 2019 to just 24 percent in 2024.

This built-in security means malware written in Rust is less likely to crash or exhibit anomalous behavior that might trigger detection. Combined with Rust’s performance characteristics—offering speeds comparable to C while providing high-level abstractions—threat actors gain a reliable platform for sophisticated operations.

Real-World Threat Landscape: 2025 Observations

Bitsight’s 2025 Threat Intelligence

Bitsight’s analysis of malware trends through 2025 reveals that emerging toolkits written in Rust, Go, and other cross-platform languages demonstrate the technical evolution of criminal development practices. The cybersecurity firm observed sustained growth in Malware-as-a-Service (MaaS) and Remote Access Trojan (RAT) activity, with cross-platform capabilities becoming a standard feature rather than an advanced option.

The professionalization of the cybercrime market is evident in the increased advertising of MaaS toolkits and stealer logs across dark web forums. Popular platforms like Fog, Acreed, and Lumma provide turnkey capabilities for data theft and credential harvesting, significantly lowering the technical barriers for aspiring cybercriminals. Many of these services now offer Rust and Go variants specifically marketed for their detection evasion capabilities.

Ransomware Evolution

Ransomware operators have been particularly aggressive in adopting modern languages. The Akira ransomware group, which has claimed approximately 244 million dollars in ransom payments, deployed a Rust-based encryptor called Megazord that encrypts files with enhanced speed and anti-analysis features. The group has also developed Akira_v2, a variant enabling faster encryption speeds that further inhibits system recovery.

Trend Micro researchers documented the Agenda ransomware group’s transition from Go to Rust, noting that the rewritten version targets manufacturing and IT companies with improved capabilities. The Rust implementation allows attackers to disable Windows User Account Control and other security features, preventing legitimate applications from running with administrative privileges.

Supply Chain Attacks

Modern programming languages have also infiltrated software supply chains. Socket security researchers recently identified malicious packages across the Go, npm, and Rust ecosystems designed to harvest sensitive developer data. A particularly concerning case involved the Rust crate “evm-units,” which accumulated over 7,000 downloads before its malicious nature was discovered.

The package embedded a cross-platform loader within seemingly legitimate Ethereum development utilities, targeting Web3 developers specifically. The malware checked for the presence of specific antivirus processes and adjusted its behavior accordingly, demonstrating sophisticated environmental awareness designed to evade detection.

Technical Challenges for Security Teams

Inadequate Tooling

The cybersecurity industry’s reverse engineering toolkit has not kept pace with the adoption of modern programming languages in malware. Standard analysis tools that work effectively on C and C++ binaries falter when confronted with Rust’s complex type system, borrowing mechanisms, and compiler optimizations.

SentinelOne and Intezer launched the OxA11C project in 2024 specifically to address this gap. The initiative aims to develop methodologies and tools for analyzing Rust malware, building on the success of their earlier AlphaGolang project for Go malware analysis. These efforts revealed that once proper context is restored, analyzing Go malware can actually be easier than traditional languages—a promising sign for future Rust analysis capabilities.

Behavioral Detection Limitations

Signature-based detection has always had limitations, but the unique characteristics of Rust and Go malware exacerbate these weaknesses. The languages’ different memory management approaches, runtime behaviors, and system API interactions don’t match patterns security tools have been trained to recognize over decades of C-based malware analysis.

Modern endpoint detection and response (EDR) solutions increasingly rely on behavioral analysis to complement signature detection. However, threat actors are developing countermeasures specifically designed to evade these systems. Recent ransomware campaigns have employed bring-your-own-installer (BYOI) techniques, just-in-time (JIT) hooking, and memory injection to bypass behavioral detection mechanisms.

Resource and Skill Gaps

Organizations face a critical shortage of security professionals with expertise in both malware analysis and modern programming languages. While the general developer community has embraced Rust and Go, cybersecurity teams often lack the specialized knowledge needed to effectively investigate threats written in these languages.

This skills gap creates a concerning asymmetry. Malware developers can leverage extensive documentation, helpful communities, and robust tooling to build sophisticated threats, while defenders struggle with inadequate analysis tools and limited expertise.

Defense Strategies for Modern Threats

Advanced Threat Intelligence

Proactive threat intelligence has become essential for combating Rust and Go malware. Security teams should participate in threat-sharing platforms like Information Sharing and Analysis Centers (ISACs) to receive real-time indicators of compromise related to these emerging threats. Intelligence gathered from global threat feeds can help organizations anticipate attacker strategies and adapt defenses accordingly.

Machine learning and artificial intelligence offer promising approaches for detecting malware regardless of programming language. By analyzing behavioral patterns rather than code signatures, AI-powered systems can identify malicious activity even when static analysis fails. These platforms should aggregate data from multiple sources to build comprehensive threat models that capture the unique characteristics of modern malware.

Behavioral and Heuristic Analysis

Organizations must shift focus from signature-based detection to behavioral monitoring that identifies malicious actions rather than specific code patterns. Memory-based detection tools that monitor RAM for suspicious activities—such as unauthorized process injections, DLL sideloading, or irregular API calls—can catch Rust and Go malware executing in memory.

Runtime Application Self-Protection (RASP) technologies integrate directly into application runtime environments, preventing malicious code from executing regardless of how it was compiled. For instance, RASP can detect and block attempts to exploit memory buffers in real time, neutralizing threats before they escalate.

Specialized Training and Tool Development

Investing in cybersecurity team training on modern programming languages represents a strategic imperative. Security professionals need hands-on experience with Rust and Go development to understand how these languages compile, how their runtime environments behave, and what artifacts they leave in systems.

Organizations should also support the development and adoption of specialized reverse engineering tools. Projects like OxA11C and AlphaGolang demonstrate that with proper research and tool development, analyzing modern language malware can become tractable—and potentially even easier than analyzing traditional compiled languages.

Network Segmentation and Zero Trust

Given the cross-platform capabilities of Rust and Go malware, traditional perimeter-based security models prove insufficient. Zero Trust Network Access (ZTNA) architectures that assume no implicit trust and continuously verify every access request offer better protection against lateral movement after initial compromise.

Network segmentation limits the blast radius of successful intrusions. By isolating critical systems and requiring explicit authorization for cross-segment communication, organizations can prevent Rust and Go malware from leveraging their cross-platform capabilities to spread throughout heterogeneous environments.

Immutable Backup Strategies

The speed and efficiency of modern ransomware—particularly Rust-based variants—demands robust backup and recovery capabilities. Organizations should implement the 3-2-1-1-0 backup rule: three copies of data, on two different media types, with one copy offsite, one immutable or offline, and zero restore errors verified through regular testing.

Immutable backups protected by object-lock technology or maintained on air-gapped systems provide the last line of defense when ransomware evades all other controls. With average ransom payments reaching 2.73 million dollars in 2024—nearly double the previous year—the business case for resilient backup infrastructure is compelling.

The Future of Rust and Go in Cybercrime

The integration of artificial intelligence into malware development represents the next frontier. Threat actors are beginning to experiment with AI-driven evasion techniques, using machine learning to optimize code obfuscation and identify security blind spots. The GLOBAL GROUP ransomware operation has already launched an AI-driven Ransomware-as-a-Service model that automates target selection and attack customization.

As legitimate software development continues migrating to memory-safe languages—encouraged by agencies like CISA and DARPA—the ecosystem of tools, libraries, and developer knowledge around Rust and Go will expand. This maturation benefits everyone, including malware authors who gain access to more sophisticated capabilities and better community support.

The trend toward cross-platform, difficult-to-analyze malware written in modern languages appears irreversible. Organizations that fail to adapt their security strategies face increasing risk as the gap between attacker capabilities and defender preparedness widens.

Conclusion

The emergence of Rust and Go as preferred languages for malware development represents a fundamental challenge to traditional cybersecurity approaches. These modern languages offer cybercriminals cross-platform capabilities, detection evasion, reverse engineering resistance, and performance advantages that make legacy defense mechanisms significantly less effective.

Bitsight’s observation that cross-platform malware written in Rust and Go is becoming standard among emerging actors signals a permanent shift in the threat landscape. Security teams must respond with investments in advanced threat intelligence, behavioral detection systems, specialized training, and resilient backup infrastructure.

The cybersecurity community is beginning to develop the tools and methodologies needed to combat these threats. Projects like OxA11C and AlphaGolang demonstrate that with dedicated research and collaboration, the advantages modern languages provide to malware authors can be neutralized. However, success requires sustained commitment to evolving defensive capabilities at the same pace attackers are advancing their offensive toolkits.

Organizations that embrace this challenge—developing expertise in modern languages, deploying advanced detection technologies, and implementing defense-in-depth strategies—will be better positioned to withstand the next generation of cyber threats. Those that cling to outdated approaches risk facing increasingly sophisticated attacks from adversaries whose technical capabilities continue to accelerate.

The cat-and-mouse game between attackers and defenders continues, but the playing field has fundamentally changed. Understanding and adapting to the reality of Rust and Go malware is no longer optional—it’s an essential component of any mature cybersecurity program.