CVE-2026-18617: Improperly Controlled Modification of Dynamically-Determined Object Attributes in Red Hat Red Hat OpenShift AI 2.25
A flaw was found in the Data Science Pipelines Operator (DSPO). A namespace editor can exploit a vulnerability in the spec.database.customExtraParams field, which allows for the injection of dangerous parameters into the MySQL Data Source Name (DSN) string. By manipulating these parameters, an attacker can enable LOCAL INFILE functionality and exfiltrate sensitive files, such as the service account token, from the operator pod. This can lead to privilege escalation, allowing a namespace editor to gain cluster-admin privileges.
AI Analysis
Technical Summary
CVE-2026-18617 is a vulnerability in the Data Science Pipelines Operator (DSPO) where a namespace editor can manipulate the spec.database.customExtraParams field to inject dangerous parameters into the MySQL DSN string. This injection enables the LOCAL INFILE feature, allowing the attacker to read sensitive files from the operator pod, including the service account token. This file exfiltration can lead to privilege escalation, enabling the attacker to gain cluster-admin privileges within the Kubernetes cluster. The vulnerability is classified under CWE-915 (Improper Control of Dynamically-Managed Code Resources). The CVSS v3.1 score is 8.8 (high severity) with network attack vector, low attack complexity, privileges required as low, no user interaction, and high impact on confidentiality, integrity, and availability.
Potential Impact
An attacker with namespace editor privileges can exploit this vulnerability to exfiltrate sensitive files from the operator pod, including service account tokens. This can lead to privilege escalation, allowing the attacker to gain cluster-admin privileges, which significantly compromises the security of the Kubernetes cluster and its workloads.
Mitigation Recommendations
According to the Red Hat advisories RHSA-2026:53261 and RHSA-2026:53262, updated images for Red Hat OpenShift AI are available that address this vulnerability. Users should upgrade to Red Hat OpenShift AI versions 2.25.10 or 3.4.3 as applicable and follow the official upgrade documentation to fully apply the errata updates. No other temporary or workaround fixes are mentioned, so applying the vendor-provided updates is the recommended remediation.
CVE-2026-18617: Improperly Controlled Modification of Dynamically-Determined Object Attributes in Red Hat Red Hat OpenShift AI 2.25
Description
A flaw was found in the Data Science Pipelines Operator (DSPO). A namespace editor can exploit a vulnerability in the spec.database.customExtraParams field, which allows for the injection of dangerous parameters into the MySQL Data Source Name (DSN) string. By manipulating these parameters, an attacker can enable LOCAL INFILE functionality and exfiltrate sensitive files, such as the service account token, from the operator pod. This can lead to privilege escalation, allowing a namespace editor to gain cluster-admin privileges.
CVSS v3.1
Score 8.8high
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-18617 is a vulnerability in the Data Science Pipelines Operator (DSPO) where a namespace editor can manipulate the spec.database.customExtraParams field to inject dangerous parameters into the MySQL DSN string. This injection enables the LOCAL INFILE feature, allowing the attacker to read sensitive files from the operator pod, including the service account token. This file exfiltration can lead to privilege escalation, enabling the attacker to gain cluster-admin privileges within the Kubernetes cluster. The vulnerability is classified under CWE-915 (Improper Control of Dynamically-Managed Code Resources). The CVSS v3.1 score is 8.8 (high severity) with network attack vector, low attack complexity, privileges required as low, no user interaction, and high impact on confidentiality, integrity, and availability.
Potential Impact
An attacker with namespace editor privileges can exploit this vulnerability to exfiltrate sensitive files from the operator pod, including service account tokens. This can lead to privilege escalation, allowing the attacker to gain cluster-admin privileges, which significantly compromises the security of the Kubernetes cluster and its workloads.
Mitigation Recommendations
According to the Red Hat advisories RHSA-2026:53261 and RHSA-2026:53262, updated images for Red Hat OpenShift AI are available that address this vulnerability. Users should upgrade to Red Hat OpenShift AI versions 2.25.10 or 3.4.3 as applicable and follow the official upgrade documentation to fully apply the errata updates. No other temporary or workaround fixes are mentioned, so applying the vendor-provided updates is the recommended remediation.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- GHSA-g6qh-932v-chpq
- Osv Schema Version
- 1.4.0
- Aliases
- ["CVE-2026-18617"]
- Ecosystems
- []
- Database Specific Severity
- HIGH
- Cvss Version
- 3.1
Patch Information
Threat ID: 6a7c9b73bf8831d539ce0bc2
Added to database: 08/12/2026, 16:12:35 UTC
Last enriched: 08/12/2026, 17:32:46 UTC
Last updated: 08/13/2026, 03:40:59 UTC
Views: 3
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.