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Evading and crashing anti-malware solutions via data collection overloading during analysis serialization
(2026-02-02) Gkritsis, Evgenios; Γκρίτσης, Ευγένιος; Gritzalis, Dimitrios; Stergiopoulos, George; Patsakis, Constantinos
Anti-malware systems rely on sandboxes, hooks, and telemetry pipelines like collection agents, serializers, and database backends, to monitor program and system behavior. We show that these data-handling components constitute an exploitable attack surface that can lead to denial-of-analysis (DoA) states without disabling sensors or requiring elevated privileges. We present Telemetry Complexity Attacks (TCAs), a new class of vulnerabilities that exploit mismatches between unbounded collection mechanisms and bounded processing capabilities. Our method recursively spawns child processes to generate deeply nested and oversized objects that stress serialization and storage boundaries, as well as visualization layers, e.g., JSON/BSON depth and size limits. Depending on the product, this leads to truncated or missing behavioral reports, rejected database inserts, serializer recursion and size errors, and unresponsive dashboards, with some cases also exhibiting normal malicious execution that was not recorded or presented to analysts. We evaluate our technique against 13 commercial and open-source malware analysis platforms and endpoint detection and response (EDR) solutions. Seven products fail at different stages of the telemetry pipeline; three CVE identifiers have been assigned (CVE-2025-61301, CVE-2025-61303, and CVE-2025-67221); one more is pending; and others have issued patches or configuration changes. We discuss root causes and propose mitigation strategies to prevent DoA attacks triggered by adversarial telemetry.