CVE-2025-34188 is a vulnerability classified under CWE-532 (Insertion of Sensitive Information into Log File) affecting Vasion Print Virtual Appliance Host versions prior to 1.0.735 and macOS/Linux client applications prior to 20.0.1330. The flaw lies in the local logging mechanism where sensitive authentication session tokens—specifically PHPSESSID, XSRF-TOKEN, and laravel_session—are written in cleartext into log files that are world-readable on the host system. These tokens are used to maintain authenticated sessions with the SaaS environment of Vasion Print. Because the tokens are exposed in logs accessible by any local user, an attacker with local access can extract these tokens and impersonate legitimate users remotely without needing to know their credentials or perform additional authentication steps. The vulnerability does not require user interaction or elevated privileges beyond local user access, but it does require local access to the affected machine. The impact is significant as it allows unauthorized remote authentication, potentially leading to unauthorized system access and exposure of sensitive print management data. The CVSS 4.0 vector indicates low attack complexity but requires local access and privileges, with high impact on confidentiality and integrity. No public exploits have been reported yet, but the vulnerability is classified as high severity by the vendor and CVSS scoring. The vendor has identified this issue as V-2022-008 and it is recommended to apply patches or mitigations once available.

For European organizations, this vulnerability poses a serious risk especially in environments where multiple users share access to print appliance hosts or client machines. Unauthorized access to session tokens can lead to attackers bypassing authentication controls and gaining remote access to the SaaS print management environment. This could result in unauthorized print job manipulation, exposure of sensitive documents, or further lateral movement within the network. Confidentiality and integrity of print-related data and user sessions are at risk. Organizations with hybrid or cloud-integrated print infrastructures are particularly vulnerable. The risk is heightened in sectors with strict data protection regulations such as finance, healthcare, and government, where print data may contain sensitive personal or classified information. Additionally, the vulnerability could be exploited to disrupt print services or exfiltrate sensitive operational data. Since exploitation requires local access, environments with weak endpoint security or shared user accounts are more exposed. The absence of known exploits currently provides a window for proactive mitigation.

1. Immediately restrict permissions on log files generated by Vasion Print Virtual Appliance Host and client applications to prevent world-readable access, ensuring only authorized system administrators can read them. 2. Implement log sanitization or configuration changes to prevent sensitive session tokens from being logged in cleartext. 3. Apply vendor patches or updates as soon as they become available to address the root cause of the vulnerability. 4. Enforce strict endpoint security controls to limit local user access, including use of least privilege principles and strong user account management. 5. Monitor logs and system access for unusual activity that could indicate token theft or unauthorized authentication attempts. 6. Consider network segmentation to isolate print infrastructure from general user environments to reduce the risk of local access exploitation. 7. Educate IT staff and users about the risks of local token exposure and the importance of securing local machines. 8. If possible, rotate session tokens or invalidate existing sessions after patching to prevent reuse of stolen tokens. 9. Review and enhance SaaS environment authentication policies, such as implementing multi-factor authentication, to mitigate risk from stolen tokens. 10. Conduct regular security audits and vulnerability assessments on print infrastructure components to detect similar issues.