Описание
A flaw was found in ml-metadata. The statically-linked gRPC stack in ml-metadata is outdated, making it vulnerable to known HTTP/2 denial of service (DoS) issues. An in-cluster attacker, with network access to the MLMD pod, could exploit these vulnerabilities by sending specially crafted HTTP/2 requests. This could lead to a denial of service by crashing the MLMD pod, disrupting all pipeline runs in the affected namespace.
Отчет
This vulnerability has a Moderate impact. An in-cluster attacker, if able to reach the MLMD pod within the NetworkPolicy allowlist, could exploit HTTP/2 DoS vulnerabilities in the bundled gRPC to crash or resource-exhaust the MLMD pod. This could disrupt all pipeline runs in the namespace. The affected ml-metadata component is planned for removal from the product.
Меры по смягчению последствий
To mitigate this issue, ensure that network policies are strictly enforced to limit access to the MLMD pod's port 8080. Restrict inbound connections to only essential KFP v2 driver pods and other designated DSP components. This measure reduces the attack surface by limiting potential in-cluster attackers who could exploit the gRPC HTTP/2 denial-of-service vulnerabilities.
Дополнительная информация
Статус:
EPSS
7.5 High
CVSS3
Связанные уязвимости
A flaw was found in ml-metadata. The statically-linked gRPC stack in ml-metadata is outdated, making it vulnerable to known HTTP/2 denial of service (DoS) issues. An in-cluster attacker, with network access to the MLMD pod, could exploit these vulnerabilities by sending specially crafted HTTP/2 requests. This could lead to a denial of service by crashing the MLMD pod, disrupting all pipeline runs in the affected namespace.
A flaw was found in ml-metadata. The statically-linked gRPC stack in ml-metadata is outdated, making it vulnerable to known HTTP/2 denial of service (DoS) issues. An in-cluster attacker, with network access to the MLMD pod, could exploit these vulnerabilities by sending specially crafted HTTP/2 requests. This could lead to a denial of service by crashing the MLMD pod, disrupting all pipeline runs in the affected namespace.
EPSS
7.5 High
CVSS3