CVE-2022-29248
Published: 25 May 2022
Summary
CVE-2022-29248 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Guzzlephp Guzzle. Its CVSS base score is 8.0 (High).
Operationally, ranked in the top 29.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-3650
Vulnerability details
Guzzle is a PHP HTTP client. Guzzle prior to versions 6.5.6 and 7.4.3 contains a vulnerability with the cookie middleware. The vulnerability is that it is not checked if the cookie domain equals the domain of the server which sets…
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the cookie via the Set-Cookie header, allowing a malicious server to set cookies for unrelated domains. The cookie middleware is disabled by default, so most library consumers will not be affected by this issue. Only those who manually add the cookie middleware to the handler stack or construct the client with ['cookies' => true] are affected. Moreover, those who do not use the same Guzzle client to call multiple domains and have disabled redirect forwarding are not affected by this vulnerability. Guzzle versions 6.5.6 and 7.4.3 contain a patch for this issue. As a workaround, turn off the cookie middleware.
- 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.