CVE-2023-47643
Published: 21 November 2023
Summary
CVE-2023-47643 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Salesagility Suitecrm. Its CVSS base score is 3.1 (Low).
Operationally, ranked in the top 2.1% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
SuiteCRM versions prior to 8.4.2 are affected by a vulnerability in which GraphQL introspection remains enabled without authentication, thereby exposing the complete schema that defines all object types, arguments, and functions. This exposure includes sensitive fields such as UserHash and reveals the full structure of the API.
An attacker with network access can query the introspection endpoint to obtain the schema and map the API attack surface, although the associated CVSS 3.1 score of 3.1 indicates limited confidentiality impact under the listed conditions.
The GitHub security advisory and accompanying commit show that the issue is fixed in SuiteCRM 8.4.2; the advisory states there are no known workarounds. The EPSS score has remained flat at a peak of 0.4965 with no material increase after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-51742
Vulnerability details
SuiteCRM is a Customer Relationship Management (CRM) software application. Prior to version 8.4.2, Graphql Introspection is enabled without authentication, exposing the scheme defining all object types, arguments, and functions. An attacker can obtain the GraphQL schema and understand the entire…
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attack surface of the API, including sensitive fields such as UserHash. This issue is patched in version 8.4.2. There are no known workarounds.
- 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.