CVE-2023-26049
Published: 18 April 2023
Summary
CVE-2023-26049 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Eclipse Jetty. Its CVSS base score is 2.4 (Low).
Operationally, ranked in the top 38.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-1360
Vulnerability details
Jetty is a java based web server and servlet engine. Nonstandard cookie parsing in Jetty may allow an attacker to smuggle cookies within other cookies, or otherwise perform unintended behavior by tampering with the cookie parsing mechanism. If Jetty sees…
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a cookie VALUE that starts with `"` (double quote), it will continue to read the cookie string until it sees a closing quote -- even if a semicolon is encountered. So, a cookie header such as: `DISPLAY_LANGUAGE="b; JSESSIONID=1337; c=d"` will be parsed as one cookie, with the name DISPLAY_LANGUAGE and a value of b; JSESSIONID=1337; c=d instead of 3 separate cookies. This has security implications because if, say, JSESSIONID is an HttpOnly cookie, and the DISPLAY_LANGUAGE cookie value is rendered on the page, an attacker can smuggle the JSESSIONID cookie into the DISPLAY_LANGUAGE cookie and thereby exfiltrate it. This is significant when an intermediary is enacting some policy based on cookies, so a smuggled cookie can bypass that policy yet still be seen by the Jetty server or its logging system. This issue has been addressed in versions 9.4.51, 10.0.14, 11.0.14, and 12.0.0.beta0 and users are advised to upgrade. There are no known workarounds for this issue.
- 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.