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VulnerabilityPublished Updated

CVE-2026-18620: Data Science Pipelines · Insecure Direct Object Reference

Source GCVE Database

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Authoritative record:CVE-2026-18620· High 7.1

Not known to be exploited · CVSS 7.1 High : patch Red Hat OpenShift AI 2.25 soon.

Data as of 11 Nov 2026, 23:24 UTC

CVSS 3.1 base score
7.1High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 41% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 10 Aug 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq 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 11 Nov 2026.

What to do

Affected software

ProductAffectedFixed in
Red HatRed Hat OpenShift AI 2.25Affected–Fixed in–
Red HatRed Hat OpenShift AI 2.25Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.3Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.4Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.4Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.5Affected–Fixed in–

AI-suggested

Red Hat has published security advisories (RHSA-2026:53261 and RHSA-2026:53262) for Red Hat OpenShift AI that include updated images and instructions for upgrading clusters to remediate this vulnerability. Users should follow the official Red Hat documentation to upgrade to the fixed versions of Red Hat OpenShift AI as soon as possible. No other specific mitigations are indicated. Patch status is confirmed by vendor advisories indicating updated images are available.

Description

A flaw was found in Data Science Pipelines. A restricted user, or tenant, can exploit an improper authorization vulnerability in the setDefaultServiceAccount function. By specifying a more privileged ServiceAccount (SA) during a CreateRun request, an attacker can bypass authorization checks. This allows the tenant to run their containers with elevated privileges, potentially leading to the disclosure of sensitive information (secrets) and the ability to execute commands within other users' pods.

References

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