VulnerabilityPublished 20 Jun 2025Updated 9 Oct 2026

CVE-2025-6193: Red Hat OpenShift AI 2.16 trustyai-service-operator · OS Command Injection

Affects Red Hat OpenShift AI 2.16 trustyai-service-operatorSource CVE Database V5

Not known to be exploited · CVSS 5.9 Medium.

Data as of 26 Oct 2026, 10:12 UTC

CVSS 3.1 base score

5.9Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.7% chance of exploitation in 30 days – higher than 54% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L

Attack Vector: Network
Attack Complexity: Low
Privileges Required: High
User Interaction: Required
Scope: Changed
Confidentiality: Low
Integrity: Low
Availability: Low

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: High: The attacker is authorized with (i.e., requires) privileges that provide significant (e.g., administrative) control over the vulnerable component that could affect component-wide settings and files.
User Interaction: Required: Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited.
Scope: Changed: An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 20 Jun 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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 26 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

cwe-78

What to do

Affected software

Product	Affected	Fixed in
GitHubtrustyai-explainability/trustyai-service-operator`pkg:github/trustyai-explainability/trustyai-service-operator`Other threats	Affected =0	Fixed in–
GitHubtrustyAI`pkg:github/trustyAI`Other threats	Affected <=1.38	Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Apply vendor patches or updates as soon as they become available to fix the input validation flaw in the TrustyAI Explainability toolkit.
Restrict permissions to deploy or modify LMEValJob custom resources using Kubernetes Role-Based Access Control (RBAC) to only trusted administrators.
Implement admission controllers or policy enforcement tools (e.g., OPA Gatekeeper) to validate and sanitize inputs in custom resources before deployment.
Monitor audit logs for unusual creation or modification of LMEValJob CRs and unexpected pod behaviors.
Isolate AI workloads in dedicated namespaces with strict network policies to limit lateral movement.
Conduct regular security reviews of custom resource definitions and their handling code to detect injection risks.
Educate developers and operators on secure coding and deployment practices for Kubernetes CRDs and AI toolkits.

Description

A command injection vulnerability was discovered in the TrustyAI Explainability toolkit. Arbitrary commands placed in certain fields of a LMEValJob custom resource (CR) may be executed in the LMEvalJob pod's terminal. This issue can be exploited via a maliciously crafted LMEvalJob by a user with permissions to deploy a CR.

Impact

The vulnerability allows an authenticated user with permissions to deploy custom resources to execute arbitrary OS commands within the LMEValJob pod. This can lead to unauthorized access to sensitive data processed by the pod, modification or deletion of critical files, and disruption of AI explainability services. If the attacker escalates privileges or moves laterally within the cluster, the impact could extend to broader system compromise, affecting the integrity and availability of AI workloads and potentially other OpenShift components. Organizations relying on RHOAI for AI model explainability and deployment may face operational disruptions, data breaches, and loss of trust in AI outputs. The medium severity rating reflects the requirement for authenticated access and user interaction, limiting exposure to internal or trusted users rather than external unauthenticated attackers. However, in environments with weak RBAC or insider threats, the risk is significant.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 26 Mar 2026, 00:30 UTC

Technical details

References

Community reviews

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