When a POST request comes through AJP and the request exceeds the max-post-size limit (maxEntitySize), Undertows AjpServerRequestConduit implementation closes a connection without sending any response to the client/proxy. This behavior results in that a front-end proxy marking the backend worker (application server) as an error state and not forward requests to the worker for a while. In mod_cluster, this continues until the next STATUS request (10 seconds intervals) from the application server updates the server state. So, in the worst case, it can result in All workers are in error state and mod_cluster responds 503 Service Unavailable for a while (up to 10 seconds). In mod_proxy_balancer, it does not forward requests to the worker until the retry timeout passes. However, luckily, mod_proxy_balancer has forcerecovery setting (On by default; this parameter can force the immediate recovery of all workers without considering the retry parameter of the workers if all workers of a balancer are in error state.). So, unlike mod_cluster, mod_proxy_balancer does not result in responding 503 Service Unavailable. An attacker could use this behavior to send a malicious request and trigger server errors, resulting in DoS (denial of service). This flaw was fixed in Undertow 2.2.19.Final, Undertow 2.3.0.Alpha2.
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Integration_camel_k | Redhat | - (including) | - (including) |
| Jboss_fuse | Redhat | 7.0.0 (including) | 7.0.0 (including) |
| Undertow | Redhat | * | 2.2.19 (excluding) |
| Undertow | Redhat | 2.3.0-alpha1 (including) | 2.3.0-alpha1 (including) |
| Undertow | Ubuntu | bionic | * |
| Undertow | Ubuntu | impish | * |
| Undertow | Ubuntu | kinetic | * |
| Red Hat Fuse 7.11.1 | RedHat | undertow | * |
| Red Hat JBoss Enterprise Application Platform 7 | RedHat | undertow | * |
| Red Hat JBoss Enterprise Application Platform 7.4 for RHEL 8 | RedHat | eap7-undertow-0:2.2.19-1.SP2_redhat_00001.1.el8eap | * |
| Red Hat JBoss Enterprise Application Platform 7.4 for RHEL 9 | RedHat | eap7-undertow-0:2.2.19-1.SP2_redhat_00001.1.el9eap | * |
| Red Hat JBoss Enterprise Application Platform 7.4 on RHEL 7 | RedHat | eap7-undertow-0:2.2.19-1.SP2_redhat_00001.1.el7eap | * |
Limited resources include memory, file system storage, database connection pool entries, and CPU. If an attacker can trigger the allocation of these limited resources, but the number or size of the resources is not controlled, then the attacker could cause a denial of service that consumes all available resources. This would prevent valid users from accessing the product, and it could potentially have an impact on the surrounding environment. For example, a memory exhaustion attack against an application could slow down the application as well as its host operating system. There are at least three distinct scenarios which can commonly lead to resource exhaustion:
Resource exhaustion problems are often result due to an incorrect implementation of the following situations:
Mitigation of resource exhaustion attacks requires that the target system either:
The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.