Custom Malware Frameworks Exploiting Windows Copilot+ NPUs for Stealthy Lateral Movement in 2026 Endpoints

Executive Summary: By mid-2026, a new generation of custom malware frameworks will emerge, uniquely leveraging the Neural Processing Units (NPUs) integrated into Windows Copilot+ PCs to execute stealthy lateral movement across enterprise networks. These frameworks exploit the NPU’s dedicated AI acceleration hardware—typically isolated from traditional CPU/memory inspection—to perform covert command-and-control (C2), privilege escalation, and lateral traversal without detection by conventional endpoint protection platforms (EPPs) or network monitoring tools. This report analyzes the threat landscape, outlines attack vectors, and provides strategic recommendations for defenders.

Key Findings

• NPU Abuse as a Stealth Vector: Malware leverages the Windows Copilot+ NPU—designed for AI workloads like Windows AI features—to perform unauthorized computations, bypassing CPU-based monitoring and obfuscating malicious activity.
• Lateral Movement via NPU-Enhanced Payloads: Custom frameworks use NPU-optimized models to generate polymorphic attack sequences, enabling adaptive evasion and real-time C2 reconfiguration.
• Evasion of Traditional Defenses: Because NPUs operate in a separate architectural domain, legacy EPPs, EDRs, and SIEMs fail to inspect NPU memory or registers, creating blind spots.
• Privilege Escalation via NPU Firmware Access: Some frameworks target NPU firmware—often stored in SPI flash—to inject persistent rootkits that survive OS reinstalls.
• Supply Chain Risk: OEM-integrated NPU drivers and firmware, supplied by vendors like Qualcomm, Intel, or AMD, may contain vulnerabilities that malware exploits to gain NPU-level access.

Technical Architecture of NPU-Aware Malware

Windows Copilot+ PCs introduced NPUs as part of the Copilot+ PC Initiative, with devices like the Surface Pro 11 and Dell XPS 13 featuring NPUs capable of 45+ TOPS. These units are managed via the Windows AI Platform (WAIP), which includes:

• The Neural Processing Engine (NPE) driver (part of the NPU SDK).
• The Windows AI Runtime (WAIR), exposing APIs to user-mode apps and services.
• A protected NPU Memory Management Unit (NPUMMU) that isolates NPU DRAM from the CPU.

Malware authors are developing frameworks that:

• Abuse the NpuQueryResource() and NpuSubmitWork() APIs to hijack NPU workloads.
• Inject malicious AI models (e.g., quantized neural networks) via compromised apps that call WAIP services.
• Use NPU-accelerated cryptography (e.g., lattice-based encryption) to encrypt C2 traffic in real time, evading TLS inspection.
• Leverage NPU-based steganography to hide exfiltrated data within AI-generated images or audio (e.g., diffusion model outputs).

Lateral Movement Tactics Using NPU Resources

Once a foothold is established on one Copilot+ endpoint, attackers repurpose the NPU to:

• Generate Living-off-the-Land Binaries (LOLBins): NPU-accelerated inference is used to dynamically compile PowerShell or Python scripts from encoded payloads, reducing entropy and avoiding signature detection.
• Bypass Application Control:**
• Malicious models are signed using stolen OEM AI certificates (e.g., from Qualcomm’s AI Hub), appearing as legitimate AI workloads.
• NPU tasks are not subject to AppLocker or WDAC policies, which typically target CPU-executed binaries.
• Establish NPU-to-NPU Communication:**
• Custom protocols over USB4 or PCIe (via NPU DMA) allow inter-NPU C2, forming an NPU mesh network invisible to network firewalls.
• DMA from NPU to host memory is used to dump credentials or inject shellcode into CPU context.
• Persistence via NPU Firmware Flash:
• Malware reflashes NPU firmware with a backdoored NPU OS (e.g., Qualcomm’s Hexagon SDK runtime), surviving OS wipes and secure boot.
• Firmware implants can survive even if the OS is reinstalled, as NPU firmware is stored in SPI NOR flash outside the main storage.