CVE-2022-34776
Published: 22 August 2022
Summary
CVE-2022-34776 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Tabit Tabit. Its CVSS base score is 5.5 (Medium).
Operationally, ranked in the top 49.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-37724
Vulnerability details
Tabit - giftcard stealth. Several APIs on the web system display, without authorization, sensitive information such as health statements, previous bills in a specific restaurant, alcohol consumption and smoking habits. Each of the described APIs, has in its URL one…
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or more MongoDB ID which is not so simple to enumerate. However, they each receive a 'tiny URL' in tabits domain, in the form of https://tbit.be/{suffix} with suffix being a 5 character long string containing numbers, lower and upper case letters. It is not so simple to enumerate them all, but really easy to find some that work and lead to a personal endpoint. Furthermore, the redirect URL disclosed the MongoDB IDs discussed above, and we could use them to query other endpoints disclosing more personal 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.