CVE-2025-34123
Published: 16 July 2025
Summary
CVE-2025-34123 is a high-severity Improper Input Validation (CWE-20) vulnerability in Githubusercontent (inferred from references). Its CVSS base score is 8.4 (High).
Operationally, ranked in the top 4.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
A stack-based buffer overflow vulnerability exists in VideoCharge Studio 2.12.3.685 when processing a specially crafted .VSC configuration file. The issue occurs due to improper handling of user-supplied data in the XML 'Name' attribute, leading to an SEH overwrite condition. The vulnerability is tracked as CVE-2025-34123 with a CVSS 4.0 score of 8.4 and is associated with CWE-20, CWE-94, and CWE-121.
An unauthenticated attacker can exploit the flaw by convincing a user to open a malicious .VSC file on a local system, resulting in arbitrary code execution under the context of the current user. The attack requires user interaction but no privileges or additional authentication.
Public references including a Metasploit module, an Exploit-DB entry, and a VulnCheck advisory document the issue and provide exploit artifacts, though no vendor patch or explicit mitigation guidance is described in the available sources. The EPSS score stands at 0.1987 with no material change from its peak value.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-21748
Vulnerability details
A stack-based buffer overflow vulnerability exists in VideoCharge Studio 2.12.3.685 when processing a specially crafted .VSC configuration file. The issue occurs due to improper handling of user-supplied data in the XML 'Name' attribute, leading to an SEH overwrite condition. An…
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attacker can exploit this vulnerability by convincing a user to open a malicious .VSC file, resulting in arbitrary code execution under the context of the user.
- 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.
Directly implements checks on information inputs to reject invalid data before processing.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Dynamically generated code can be produced and executed inside the isolated chamber, preventing host compromise from code-injection payloads.
Directly prevents execution of attacker-supplied code written into data memory regions.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.