CVE-2025-1741
Published: 27 February 2025
Summary
CVE-2025-1741 is a medium-severity Improper Input Validation (CWE-20) vulnerability in B1Gmail (inferred from references). Its CVSS base score is 5.1 (Medium).
Operationally, ranked at the 44.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-5453
Vulnerability details
A vulnerability classified as problematic was found in b1gMail up to 7.4.1-pl1. Affected by this vulnerability is an unknown functionality of the file src/admin/users.php of the component Admin Page. The manipulation of the argument query/q leads to deserialization. The attack…
more
can be launched remotely. Upgrading to version 7.4.1-pl2 is able to address this issue. The identifier of the patch is 4816c8b748f6a5b965c8994e2cf10861bf6e68aa. It is recommended to upgrade the affected component. The vendor acted highly professional and even fixed this issue in the discontinued commercial edition as b1gMail 7.4.0-pl3.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.