CVE-2025-61303 identifies a vulnerability in the behavioral analysis engine of the Hatching Triage Sandbox running on Windows 10 build 2004 and Windows 10 LTSC 2021. The sandbox is designed to analyze submitted malware samples by monitoring their behavior in a controlled environment. However, this vulnerability is triggered when a malicious sample recursively spawns a large number of child processes. This behavior generates an excessive volume of logs and exhausts the sandbox's system resources, leading to a denial-of-analysis condition. As a result, critical malicious activities such as PowerShell command execution and reverse shell connections may not be properly recorded or reported by the sandbox. This evasion technique undermines the integrity and availability of the sandbox analysis results, potentially misleading security analysts and automated detection systems. The vulnerability does not require user interaction or authentication to be exploited, as it is triggered by the malware's own behavior within the sandbox. No CVSS score has been assigned yet, and no known exploits have been observed in the wild. The root cause lies in insufficient resource management and lack of throttling or detection mechanisms for excessive process spawning within the sandbox environment. This vulnerability highlights a gap in sandbox robustness against resource exhaustion and evasion tactics employed by advanced malware.

For European organizations, this vulnerability poses a significant risk to malware detection and incident response capabilities. Organizations that utilize the Hatching Triage Sandbox or similar Windows 10-based sandbox environments for behavioral analysis may experience incomplete or inaccurate threat intelligence due to undetected malicious behaviors. This can lead to delayed or ineffective responses to advanced persistent threats (APTs) and sophisticated malware campaigns that leverage process spawning to evade detection. The denial-of-analysis condition compromises the availability and integrity of forensic data, potentially allowing attackers to maintain persistence or exfiltrate data unnoticed. Critical sectors such as finance, government, and critical infrastructure in Europe, which rely heavily on sandboxing for threat hunting and malware analysis, could be disproportionately impacted. Additionally, the inability to detect reverse shell activity increases the risk of remote control and lateral movement within networks. While no active exploitation is reported, the vulnerability lowers the barrier for attackers to bypass sandbox defenses, increasing the overall threat landscape for European cybersecurity operations.

To mitigate CVE-2025-61303, organizations should implement the following specific measures: 1) Apply any patches or updates released by Hatching or sandbox vendors addressing resource exhaustion and process spawning controls. 2) Configure sandbox environments to limit the maximum number of child processes spawned by any single sample, employing throttling or rate limiting. 3) Enhance monitoring of sandbox resource usage to detect and alert on abnormal process creation patterns indicative of evasion attempts. 4) Supplement sandbox analysis with additional detection layers such as static analysis, network traffic inspection, and endpoint monitoring to catch behaviors missed due to sandbox evasion. 5) Regularly review and update sandbox configurations to ensure they can handle high-volume logging without degradation. 6) Conduct internal testing with crafted samples that attempt recursive process spawning to validate sandbox resilience. 7) Maintain a multi-sandbox approach where possible, using diverse analysis platforms to reduce reliance on a single vulnerable system. 8) Train analysts to recognize signs of denial-of-analysis and corroborate findings with other threat intelligence sources. These targeted actions go beyond generic advice by focusing on resource management, detection of evasion techniques, and operational best practices tailored to this vulnerability.