CVE-2025-8519
Published: 04 August 2025
Summary
CVE-2025-8519 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Vvveb Vvveb. Its CVSS base score is 2.0 (Low).
Operationally, ranked in the top 46.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-23539
Vulnerability details
A vulnerability classified as problematic has been found in givanz Vvveb up to 1.0.5. This affects an unknown part of the file /vadmin123/index.php?module=editor/editor of the component Drag-and-Drop Editor. The manipulation of the argument url leads to information disclosure. It is…
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possible to initiate the attack remotely. The exploit has been disclosed to the public and may be used. Upgrading to version 1.0.6 is able to address this issue. The identifier of the patch is f684f3e374d04db715730fc4796e102f5ebcacb2. It is recommended to upgrade the affected component.
- 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.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Associating and retaining security attributes with data directly supports enforcement of access control decisions across storage, processing, and transmission.
Enforces rules governing access to the system and its data from external systems based on established trust relationships.
This control requires verifying that a sharing partner's access authorizations match the information's restrictions before sharing occurs.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.