CVE-2024-5010
Published: 25 June 2024
Summary
CVE-2024-5010 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Progress Whatsup Gold. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 3.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
CVE-2024-5010 is an information disclosure vulnerability affecting the TestController functionality in Progress WhatsUp Gold versions prior to 2023.1.3. The flaw permits a specially crafted unauthenticated HTTP request to expose sensitive information, rated at CVSS 7.5 with network attack vector, low complexity, and high confidentiality impact.
An unauthenticated remote attacker can exploit the issue by sending a crafted HTTP request to the affected TestController endpoint, resulting in unauthorized disclosure of sensitive data without requiring credentials or user interaction.
The referenced Progress security bulletin and Talos report advise upgrading to WhatsUp Gold 2023.1.3 or later to address the vulnerability. The EPSS score has remained flat at 0.2849 with no material increase observed after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-47139
Vulnerability details
In WhatsUp Gold versions released before 2023.1.3, a vulnerability exists in the TestController functionality. A specially crafted unauthenticated HTTP request can lead to a disclosure of sensitive information.
- 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.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
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.