CVE-2023-40023
Published: 14 August 2023
Summary
CVE-2023-40023 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Yaklang Yaklang. Its CVSS base score is 6.5 (Medium).
Operationally, ranked at the 45.2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2383
Vulnerability details
yaklang is a programming language designed for cybersecurity. The Yak Engine has been found to contain a local file inclusion (LFI) vulnerability. This vulnerability allows attackers to include files from the server's local file system through the web application. When…
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exploited, this can lead to the unintended exposure of sensitive data, potential remote code execution, or other security breaches. Users utilizing versions of the Yak Engine prior to 1.2.4-sp1 are impacted. This vulnerability has been patched in version 1.2.4-sp1. Users are advised to upgrade. users unable to upgrade may avoid exposing vulnerable versions to untrusted input and to closely monitor any unexpected server behavior until they can upgrade.
- 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.