Security readout for executives and security teams
Plain-English summary
An authenticated Kubernetes user could submit specially crafted YAML that makes the API server spend excessive CPU parsing it. The business impact is service disruption: the control plane may slow or become unavailable, affecting cluster management and dependent operations.
Executive priority
Prioritize remediation for production clusters, shared platforms, and environments with many users or service accounts. This is not described as unauthenticated or exploited in the provided sources, but control-plane denial of service can disrupt critical operations.
Technical view
CVE-2019-11254 affects Kubernetes API Server in versions 1.1 through 1.14, and versions before 1.15.10, 1.16.7, and 1.17.3. The issue is a denial of service caused by CPU exhaustion during YAML parsing, reachable over the network by a low-privileged authorized user.
Likely exposure
Exposure is mainly Kubernetes clusters running the listed vulnerable versions where authenticated users or service accounts can submit YAML-backed API requests. Internet exposure increases operational risk, but the sources require prior authorization.
Exploitation context
The source bundle does not show CISA KEV listing or active exploitation evidence. The attack precondition is authenticated API access, so insider, compromised credential, or over-permissive service account scenarios matter most.
Researcher notes
This is an availability-only Kubernetes API Server issue with CVSS 3.1 score 6.5 and vector AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H. Evidence in the bundle identifies vulnerable version ranges and fixed release thresholds, but does not provide exploit-in-the-wild confirmation.
Mitigation direction
- Upgrade affected Kubernetes clusters to 1.15.10, 1.16.7, 1.17.3, or later supported releases.
- Review Kubernetes and downstream vendor advisories for supported upgrade guidance.
- Restrict Kubernetes API access to users and service accounts with operational need.
- Review RBAC permissions that allow broad object creation or updates.
- Monitor kube-apiserver CPU saturation until remediation is complete.
Validation and detection
- Inventory Kubernetes control-plane versions across all clusters.
- Compare versions against 1.1-1.14 and releases before 1.15.10, 1.16.7, and 1.17.3.
- Confirm managed Kubernetes providers or vendors have applied the fixed control-plane version.
- Review kube-apiserver metrics for unexplained CPU spikes or parsing-related instability.
- Check RBAC assignments for unnecessary API write access.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.
ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-1050: Exact CWE lookup
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Open ATT&CK lookupContainer behavior lookup
The affected technology mentions containers, so container-specific ATT&CK technique review may help. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.
Open ATT&CK lookupCVE-2019-11254 mapping review
Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.
Open ATT&CK lookup- Severity
- Medium
- CVSS
- 6.5 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H2.83.6Primary CVE scoreVulnerability scoring details
Base CVSS 3.1 score
6.5MediumVector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/kubernetes/kubernetes/issues/89535CVE reference · x_refsource_MISC
- https://groups.google.com/d/msg/kubernetes-announce/ALL9s73E5ck/4yHe8J-PBAAJCVE reference · x_refsource_MISC
- https://security.netapp.com/advisory/ntap-20200413-0003/CVE reference · x_refsource_CONFIRM
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Excessive Platform Resource Consumption within a Loop
Excessive Platform Resource Consumption within a Loop represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.