CVE-2025-47821 identifies a security vulnerability in Flock Safety Gunshot Detection devices, specifically versions prior to 1.3. The vulnerability is classified under CWE-259, which pertains to the use of hard-coded passwords within a system. In this case, the devices contain a hardcoded password that is embedded in the system firmware or software, which cannot be changed or customized by the user. This type of vulnerability is problematic because it provides a predictable and static credential that attackers can exploit to gain unauthorized access to the device or its management interface. The CVSS v3.1 base score for this vulnerability is 2.2, indicating a low severity level. The vector string (CVSS:3.1/AV:P/AC:H/PR:N/UI:N/S:C/C:L/I:N/A:N) shows that the attack requires physical access (AV:P), has high attack complexity (AC:H), requires no privileges (PR:N), no user interaction (UI:N), and affects confidentiality slightly (C:L) but does not impact integrity or availability. The scope is changed (S:C), meaning the vulnerability affects components beyond the initially vulnerable component. The absence of known exploits in the wild suggests that this vulnerability has not yet been actively targeted by attackers. However, the presence of a hardcoded password can allow an attacker with physical access to the device to potentially extract sensitive information or manipulate device settings, undermining the confidentiality of the system. Given that these devices are used for gunshot detection, unauthorized access could lead to tampering with detection data or disabling alerts, which could have operational and safety implications.

For European organizations deploying Flock Safety Gunshot Detection devices, this vulnerability poses a risk primarily in environments where physical security controls are insufficient. Attackers with physical access could exploit the hardcoded password to access device settings or data, potentially compromising the confidentiality of incident detection logs. While the vulnerability does not directly affect data integrity or availability, unauthorized access could enable attackers to disable or alter detection capabilities, reducing the effectiveness of gunshot detection systems. This could have serious consequences for public safety, law enforcement, and private security operations relying on these devices. Additionally, compromised devices could be used as entry points into broader network infrastructures if connected, increasing the risk of lateral movement. The low CVSS score reflects the requirement for physical access and high attack complexity, limiting remote exploitation risks. However, in sensitive or high-risk locations such as government facilities, critical infrastructure, or urban areas with high crime rates, the impact could be more pronounced due to the strategic importance of accurate gunshot detection.

To mitigate this vulnerability, European organizations should prioritize upgrading all affected Flock Safety Gunshot Detection devices to version 1.3 or later, where the hardcoded password issue is presumably resolved. In the absence of an official patch or update, organizations should implement strict physical security controls around the devices to prevent unauthorized physical access. This includes securing device enclosures, restricting access to authorized personnel only, and monitoring device locations with surveillance. Network segmentation should be employed to isolate these devices from critical network assets, minimizing potential lateral movement if a device is compromised. Additionally, organizations should conduct regular audits and inspections of device configurations and logs to detect any unauthorized access attempts. If possible, coordinate with the vendor for guidance on temporary workarounds or password management improvements. Finally, integrating these devices into a broader security monitoring framework can help detect anomalies indicative of tampering or unauthorized access.