CVE-2020-7387
Published: 22 July 2021
Summary
CVE-2020-7387 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Sage X3. Its CVSS base score is 5.3 (Medium).
Operationally, ranked in the top 1.9% 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-2020-28513
Vulnerability details
Sage X3 Installation Pathname Disclosure. A specially crafted packet can elicit a response from the AdxDSrv.exe component that reveals the installation directory of the product. Note that this vulnerability can be combined with CVE-2020-7388 to achieve full RCE. This issue…
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was fixed in AdxAdmin 93.2.53, which ships with updates for on-premises versions of Sage X3 Version 9 (components shipped with Syracuse 9.22.7.2 and later), Sage X3 HR & Payroll Version 9 (those components that ship with Syracuse 9.24.1.3), Version 11 (components shipped with Syracuse 11.25.2.6 and later), and Version 12 (components shipped with Syracuse 12.10.2.8 and later) of Sage X3. Other on-premises versions of Sage X3 are unsupported by the vendor.
- 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.