CVE-2025-53193 is a Cross-Site Request Forgery (CSRF) vulnerability identified in Burst Statistics B.V.'s product, Burst Statistics, affecting versions up to 2.0.6. CSRF vulnerabilities arise when an attacker tricks an authenticated user into submitting a malicious request to a web application in which they are currently authenticated, thereby performing unwanted actions on behalf of the user without their consent. In this case, the vulnerability allows an attacker to craft a malicious web request that, when executed by an authenticated user, can alter data or perform actions within the Burst Statistics application without proper authorization checks. The CVSS 3.1 base score of 4.3 indicates a medium severity level, with the vector showing that the attack can be performed remotely over the network (AV:N), requires low attack complexity (AC:L), no privileges (PR:N), but does require user interaction (UI:R). The impact is limited to integrity (I:L) with no impact on confidentiality or availability. No known exploits are currently reported in the wild, and no patches have been linked yet. The vulnerability is classified under CWE-352, which is a common web application security weakness related to CSRF attacks. The absence of a patch and the medium severity suggest that while the vulnerability is not trivial, it does not allow full compromise or data leakage but can lead to unauthorized changes within the application context.

For European organizations using Burst Statistics, this vulnerability could lead to unauthorized modification of statistical data or configuration settings within the application if an attacker successfully tricks an authenticated user into executing a malicious request. This could undermine the integrity of business intelligence and analytics data, potentially leading to incorrect decision-making or reporting. While the vulnerability does not directly expose sensitive data or cause service disruption, the integrity impact can have downstream effects on compliance, audit accuracy, and operational trustworthiness. Organizations in sectors relying heavily on data analytics, such as finance, healthcare, and public administration, may face reputational damage or regulatory scrutiny if manipulated data leads to erroneous conclusions or reporting. Since the attack requires user interaction, phishing or social engineering campaigns could be used as vectors, increasing the risk if users are not adequately trained or if the application is integrated into critical workflows.

To mitigate this CSRF vulnerability, organizations should implement anti-CSRF tokens in all state-changing requests within the Burst Statistics application. This involves embedding unique, unpredictable tokens in forms and verifying them server-side upon request submission. Additionally, enforcing the SameSite cookie attribute (preferably 'Strict' or 'Lax') can help prevent cookies from being sent with cross-origin requests, reducing CSRF risk. Organizations should also ensure that users are educated about phishing and social engineering tactics to minimize the likelihood of malicious link clicks. Network-level mitigations such as Web Application Firewalls (WAFs) can be configured to detect and block suspicious cross-origin requests. Monitoring and logging unusual activity patterns related to user actions in the application can help detect exploitation attempts. Finally, organizations should track Burst Statistics vendor communications for patches or updates addressing this vulnerability and apply them promptly once available.