CVE-2026-45300
Published: 05 June 2026
Summary
CVE-2026-45300 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Asynchttpclient Project Async-Http-Client. Its CVSS base score is 7.4 (High).
Operationally, ranked at the 17.7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
No EU or UK CSIRT advisories indexed for this CVE.
Vulnerability details
The AsyncHttpClient (AHC) library allows Java applications to easily execute HTTP requests and asynchronously process HTTP responses. Versions on the 2.x branch prior to 2.15.0 and the 3.x branch prior to 3.0.10 leak `Cookie` headers to cross-origin redirect targets. When…
more
following a redirect to a different origin, the `propagatedHeaders()` method in `Redirect30xInterceptor.java` strips `Authorization` and `Proxy-Authorization` headers but does not strip the `Cookie` header, causing session cookies and other sensitive cookie values to be sent to attacker-controlled servers. Versions 2.15.0 and 3.0.10 patch the 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.