Detonating Malware Across Architectures with pokiSEC

by

Author: Denis Avetisyan

A new containerized sandbox, pokiSEC, delivers consistent and reproducible dynamic malware analysis for both ARM64 and AMD64 systems.

The system architecture employs a reverse proxy to initially direct sessions to an image loader, then seamlessly transitions control to a virtual machine desktop environment established through QEMU/KVM once launched.
The system architecture employs a reverse proxy to initially direct sessions to an image loader, then seamlessly transitions control to a virtual machine desktop environment established through QEMU/KVM once launched.

pokiSEC leverages containerization and ephemeral execution to provide a universal entrypoint for cross-architecture malware detonation.

Dynamic malware analysis demands isolated, rapidly resettable execution environments, yet practical workflows often rely on heavyweight virtualization or dedicated hardware, hindering portability and automation. This paper introduces pokiSEC: A Multi-Architecture, Containerized Ephemeral Malware Detonation Sandbox, a lightweight solution packaging full virtualization within a Docker container to address this challenge. A key innovation is a universal entrypoint enabling consistent execution of Windows guests across both ARM64 and AMD64 hosts, leveraging QEMU with hardware acceleration. By delivering a portable, ephemeral sandbox, can pokiSEC facilitate more scalable and reproducible dynamic analysis workflows for security researchers?

The Evolving Challenge of Malware Evasion

Conventional static analysis, which dissects malware code without executing it, is increasingly challenged by the ingenuity of modern threats. Sophisticated malware authors employ techniques like code obfuscation, packing, and polymorphism to deliberately mask malicious intent and evade signature-based detection. These methods transform the malware’s appearance, making it difficult to identify malicious patterns through simple code review or hash comparisons. Furthermore, advanced malware frequently utilizes anti-disassembly tactics and relies on dynamically generated code, rendering static analysis incomplete or inaccurate. Consequently, relying solely on static techniques leaves systems vulnerable to evasive threats that can bypass initial security layers and establish a foothold within a network, highlighting the need for complementary, behavioral-based detection methods.

Effective malware analysis increasingly relies on dynamic analysis – the practice of executing suspicious code and meticulously observing its actions. However, unleashing potentially malicious software presents inherent risks; therefore, a secure and isolated environment, often termed a “sandbox,” is absolutely essential. These sandboxes function as controlled ecosystems, preventing malware from interacting with the host system or network, thereby containing any damage it might attempt. The sophistication of modern malware necessitates more than simple virtual machines; robust detonation infrastructure employs layered security, memory protection, and comprehensive monitoring to capture detailed behavioral data – from system calls and registry modifications to network traffic – without jeopardizing the security of the analyzing system. This careful observation allows security researchers to understand the malware’s true intent and develop effective defenses.

Modern malware increasingly employs techniques like polymorphism, obfuscation, and anti-virtualization to evade detection, rendering traditional signature-based approaches ineffective. Consequently, effective analysis now hinges on detonation – executing the malware in a controlled environment to observe its actions. However, the sheer volume and rapidly evolving sophistication of threats necessitate scalable detonation infrastructure capable of handling countless samples concurrently and adapting to novel evasion tactics. This isn’t simply about increasing processing power; it demands flexible architectures that can dynamically reconfigure analysis parameters, support diverse operating system and hardware configurations, and seamlessly integrate with automated analysis pipelines. Such adaptable systems are vital not only for identifying current threats but also for proactively uncovering emerging malware families and understanding the full scope of their malicious capabilities, enabling a more resilient cybersecurity posture.

Constructing a Flexible Virtualization Foundation

QEMU, a widely-used open-source machine emulator and virtualizer, forms the core of our virtualization infrastructure. It enables the creation of virtual machines capable of running a diverse range of guest operating systems, including Windows, Linux, and macOS, irrespective of the host system’s native architecture. This is achieved through dynamic binary translation, allowing QEMU to emulate different instruction set architectures (ISAs) – such as x86, ARM, and PowerPC – on the underlying hardware. Consequently, QEMU provides the necessary environment for executing software intended for architectures dissimilar to the physical host, facilitating cross-platform testing and analysis without requiring dedicated hardware for each target system.

Kernel-based Virtual Machine (KVM) is utilized to significantly enhance the performance of QEMU-based virtual machines. KVM operates by leveraging hardware virtualization extensions present in modern CPUs, specifically Intel VT-x and AMD-V. This allows QEMU to execute virtual machine instructions directly on the host CPU, bypassing emulation for many operations. Consequently, CPU and I/O performance within the virtual machine is dramatically improved, enabling faster and more efficient detonation and analysis of potentially malicious software. The performance gains are critical for scalable malware analysis, reducing the time required to process samples and increasing the overall throughput of the virtualization platform.

The system employs a ‘Universal Entrypoint’ to dynamically configure QEMU for execution on both x86_64 and ARM64 architectures. This configuration is achieved programmatically, eliminating the need for manual intervention or pre-configured images for each architecture. Testing within stable Windows desktop environments has demonstrated a 100% success rate for cross-architecture execution, indicating consistent and reliable operation regardless of the underlying host or guest architecture. This dynamic configuration is critical for analyzing samples compiled for various platforms without requiring dedicated hardware or complex build processes.

Establishing Isolation, Scalability, and Reproducibility

Docker containerization streamlines the deployment of malware analysis sandboxes by packaging the entire execution environment – including the operating system, necessary tools, and the malware itself – into a standardized unit. This approach eliminates inconsistencies arising from differing host system configurations and dependencies, ensuring repeatable analysis results across various infrastructures. The container encapsulates all runtime requirements, facilitating portability and enabling rapid scaling of the sandbox environment through orchestration tools. This standardized packaging also simplifies the process of sharing analysis environments and results with collaborators, improving efficiency and reducing potential errors due to environmental discrepancies.

Ephemeral execution in malware analysis environments utilizes a reset mechanism following each detonation. This process reverts the virtual machine or container to a pristine, pre-configured state, effectively eliminating any files, registry changes, or other modifications introduced by the analyzed malware. By discarding the post-execution environment, ephemeral execution prevents data persistence and ensures that subsequent analyses are not influenced by residual artifacts from previous runs, mitigating the risk of false positives or skewed results and maintaining a consistent, clean baseline for each test.

Sysmon and Procmon are system monitoring tools utilized within the virtualized malware detonation environment to generate comprehensive forensic data. Sysmon, a Windows system service, logs detailed events including process creations, network connections, file creations, and registry modifications. Procmon, a more interactive tool, captures real-time file system, registry, and process/thread activity. The data collected by these tools includes timestamps, event descriptions, process IDs, and associated paths/filenames, allowing for granular analysis of malware behavior. This detailed event logging is crucial for identifying malicious activity, understanding infection vectors, and reconstructing the timeline of events during malware execution. Both tools output data in formats suitable for parsing and analysis by security information and event management (SIEM) systems and dedicated forensic analysis platforms.

Delivering Accessibility and Enhancing the User Experience

The architecture utilizes NoVNC to deliver a fully functional virtual desktop directly within a standard web browser, circumventing the complexities and security concerns associated with traditional, dedicated client software installations. This browser-based approach significantly simplifies deployment and enhances accessibility, allowing users to interact with the virtual environment from virtually any device capable of running a modern web browser-without requiring platform-specific applications or extensive configuration. By eliminating the need for client-side software, the system minimizes administrative overhead and broadens the potential user base, fostering a more streamlined and user-friendly experience for accessing and interacting with the contained analysis environment.

The implementation of a reverse proxy represents a critical architectural decision, significantly bolstering both the security posture and operational robustness of the platform. By positioning the proxy as an intermediary between users and the virtual desktop infrastructure, it effectively shields the backend systems from direct exposure to external threats, mitigating risks such as denial-of-service attacks and unauthorized access. Furthermore, a reverse proxy facilitates intelligent load balancing, distributing incoming requests across multiple servers to prevent overload and ensure consistently responsive performance, even during peak demand. This distributed architecture not only enhances reliability by eliminating single points of failure but also improves accessibility, allowing users to seamlessly connect to the platform from diverse locations without experiencing performance degradation or service interruptions.

The pokiSEC malware detonation sandbox demonstrates remarkable performance on Apple M3 Pro hardware, achieving Windows boot times of roughly 25 seconds – comparable to those on traditional AMD64 systems. This consistency is enabled by a containerized design, allowing pokiSEC to operate effectively across both ARM64 and AMD64 architectures without significant performance degradation. Such architectural parity is crucial for comprehensive malware analysis, ensuring that observed behavior isn’t influenced by underlying hardware differences and providing a reliable environment for identifying malicious code regardless of the target platform. This capability streamlines security investigations and enhances the sandbox’s utility in a diverse computing landscape.

The development of pokiSEC embodies a dedication to essential functionality, stripping away unnecessary layers to reveal the core of dynamic malware analysis. This pursuit aligns with Donald Davies’ observation that, “Complexity is vanity. Clarity is mercy.” The system’s cross-architecture compatibility, achieved through containerization and a universal entrypoint, isn’t about adding features; it’s about removing barriers to consistent, reproducible execution. PokiSEC prioritizes what remains – a streamlined, efficient, and reliable environment for detonation – echoing the philosophy that true design lies in subtraction, not accumulation. The ephemeral execution further reinforces this, focusing solely on the critical moments of malware behavior.

Future Trajectories

The presentation of pokiSEC, while addressing the practical demand for cross-architecture dynamic analysis, merely clarifies the contours of a larger, more persistent problem. Consistent ephemeral execution is not an end, but a necessary precondition. The true difficulty lies not in how to detonate malware, but in the fundamentally stateful nature of modern malicious code. A sandbox, however meticulously constructed, remains an approximation of a living system; it is, by definition, incomplete. Future iterations must grapple with the issue of observable state-the subtle traces left by analysis that alert sophisticated malware to its confinement.

The current focus on virtualization and containerization, while yielding improvements in reproducibility, risks becoming a local maximum. The computational cost of full system emulation, even in ephemeral form, remains significant. A worthwhile investigation lies in the exploration of selective instrumentation and minimal viable system models. The goal is not to replicate a host environment, but to provide sufficient stimulus for observable behavior. Unnecessary fidelity is violence against attention.

Ultimately, the field requires a shift in perspective. Analysis should not be a reactive process of detonation and observation, but a proactive synthesis of predictive modeling. The ambition is not merely to detect malware, but to anticipate its behavior. Density of meaning is the new minimalism; a concise model, accurately predicting malicious intent, surpasses any amount of detailed, post-hoc analysis.

Original article: https://arxiv.org/pdf/2512.20860.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2025-12-26 06:32