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CVE-2026-55969 is an Integer Overflow or Wraparound vulnerability (CWE-190) in Apache Thrift affecting the C++, c_glib, Go, netstd, Delphi, and Haxe language bindings. All versions of Apache Thrift before 0.24.0 are affected. The vulnerability was publicly disclosed on July 24, 2026, via the Apache security mailing list, with NVD analysis completed on July 27, 2026. It carries a CVSS v3.1 base score of 7.5 (High) and a CVSS v4.0 base score of 8.7 (High) (Apache Advisory, GitHub Advisory).
The vulnerability is rooted in improper integer arithmetic within the TProtocol::checkReadBytesAvailable() function (or equivalent logic) across multiple Thrift language bindings, classified as CWE-190 (Integer Overflow or Wraparound) and mapped to CAPEC-92 (Forced Integer Overflow). An unauthenticated remote attacker can send specially crafted Thrift protocol messages containing field sizes or counts that, when processed, cause an integer to overflow or wrap around to a small or negative value, bypassing bounds checks and leading to unexpected program behavior or a crash. No authentication or user interaction is required, and the attack complexity is low, making exploitation straightforward over any network-accessible Thrift service (Apache Advisory, Red Hat Bugzilla).
Successful exploitation results in a Denial of Service (DoS) condition — an unauthenticated attacker can crash or destabilize any service built on the affected Apache Thrift bindings (C++, c_glib, Go, netstd, Delphi, Haxe) by sending malformed messages. There is no assessed impact to confidentiality or integrity; the primary risk is availability loss for services relying on Thrift-based RPC communication. Given that Apache Thrift is widely used in distributed microservice architectures, a successful attack could disrupt multiple dependent services simultaneously (GitHub Advisory, Red Hat Bugzilla).
As of the time of reporting, there is no known public proof-of-concept exploit and no evidence of active in-the-wild exploitation (Apache Advisory). The NVD SSVC assessment confirms exploitation status as "none" and notes the attack is automatable. The EPSS score is approximately 1.097% (62nd percentile), indicating a moderate but not elevated near-term exploitation probability. The vulnerability is not currently listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. No threat actor attribution has been reported (GitHub Advisory).
INT32_MAX or UINT32_MAX) designed to trigger overflow in checkReadBytesAvailable() or equivalent parsing logic.INT32_MAX/UINT32_MAX); repeated connection attempts from a single source IP to Thrift endpoints.TProtocol, checkReadBytesAvailable); sudden service restarts or watchdog-triggered process respawns logged by the process supervisor.The primary remediation is to upgrade Apache Thrift to version 0.24.0 or later, which contains the fix for this integer overflow (Apache Advisory). Organizations using the Go binding should update github.com/apache/thrift to v0.24.0; NuGet users should update the ApacheThrift package to 0.24.0. Red Hat has issued security advisories (RHSA-2026:46974 and RHSA-2026:46987) for affected Red Hat products, and openSUSE has also released updated packages. As a temporary workaround where immediate patching is not possible, restrict network access to Thrift service endpoints using firewall rules to limit exposure to trusted clients only (Red Hat Advisory).
Red Hat issued two security advisories (RHSA-2026:46974 and RHSA-2026:46987) addressing this vulnerability in their product lines, and the Canadian Centre for Cyber Security published advisory AV26-749 (Canadian CCCS). The Australian CERT (AusCERT) published bulletins ESB-2026.8639 and ESB-2026.9301. Community discussion was noted on Bluesky and Mastodon (RedPacketSecurity), and the vulnerability was covered by standard security aggregators including VulnDB and Vulners. Microsoft also acknowledged the vulnerability in their MSRC update guide. Overall community sentiment reflects routine patching urgency with no reports of active exploitation.
Source: This report was generated using AI
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