CVE-2024-28849
Published: 14 March 2024
Summary
CVE-2024-28849 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Follow-Redirects Project Follow-Redirects. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Credential Access (T1212); ranked in the top 21.8% 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-2024-0907
Vulnerability details
follow-redirects is an open source, drop-in replacement for Node's `http` and `https` modules that automatically follows redirects. In affected versions follow-redirects only clears authorization header during cross-domain redirect, but keep the proxy-authentication header which contains credentials too. This vulnerability may…
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lead to credentials leak, but has been addressed in version 1.15.6. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The vulnerability in follow-redirects enables exploitation of a flaw in HTTP redirect handling to leak proxy authentication credentials to unintended cross-domain servers.
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.