CVE-2026-94449: Red Hat build of Quarkus 3.27.6.redhat · Uncontrolled Resource Consumption
Affects Red Hat build of Quarkus 3.27.6.redhatSource CVE Database V5
Not known to be exploited · CVSS 7.5 High.
Data as of 5 Nov 2026, 00:01 UTC
- EPSS
- 0.6% chance of exploitation in 30 days – higher than 50% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HExploitation evidence
Disclosed: evidence found.
CVE published 21 Sep 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 5 Nov 2026.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| Red HatRed Hat build of Quarkus 3.27.6.redhat | Affected– | Fixed in– |
| Red HatRed Hat build of Quarkus 3.33.4.redhat | Affected– | Fixed in– |
| Red HatExploit Intelligence | Affected– | Fixed in– |
| Red HatRed Hat build of Apache Camel 4 for Quarkus 3 | Affected– | Fixed in– |
| Red HatRed Hat build of Apicurio Registry 3 | Affected– | Fixed in– |
| Red HatRed Hat Fuse 7 | Affected– | Fixed in– |
AI-suggested
Red Hat has released an official security update for Red Hat build of Quarkus 3.27.6 that addresses this memory leak vulnerability. Users should apply the update as described in the Red Hat advisory RHSA-2026:83082. Before applying this update, ensure all previously released relevant errata have been applied. No additional mitigation steps are indicated by the vendor.
Description
A flaw was found in the SmallRye Fault Tolerance library, which is used by Quarkus to provide strategies like retries and circuit breakers for microservices. The issue occurs when using the ApplyGuard or ApplyFaultTolerance annotations, where the library fails to release internal tracking objects after each request. This causes a steady increase in memory usage that eventually leads to the application slowing down and crashing due to lack of memory.