CVE-2024-7557 (GCVE-0-2024-7557)
Vulnerability from cvelistv5 – Published: 2024-08-08 21:33 – Updated: 2026-10-30 16:50
VLAI
EPSS
VEX
Title
Odh-dashboard: odh-model-controller: cross-model authentication bypass in openshift ai
Summary
A vulnerability was found in OpenShift AI that allows for authentication bypass and privilege escalation across models within the same namespace. When deploying AI models, the UI provides the option to protect models with authentication. However, credentials from one model can be used to access other models and APIs within the same namespace. The exposed ServiceAccount tokens, visible in the UI, can be utilized with oc --token={token} to exploit the elevated view privileges associated with the ServiceAccount, leading to unauthorized access to additional resources.
Severity
8.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-08-09 13:52 UTC
CWE
- CWE-305 - Authentication Bypass by Primary Weakness
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://access.redhat.com/errata/RHBA-2024:8240 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/security/cve/CVE-2024-7557 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2303094 | issue-trackingx_refsource_REDHAT |
| https://github.com/opendatahub-io/odh-dashboard/p… |
Impacted products
12 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
|
Affected:
2.8.*
(semver)
Affected: 2.11 (semver) Unaffected: a122ad06a297f4e8b2a065eece910aa882cc3fa6 (git) |
||||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-11 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-5 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-6 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-7 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-8 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-10 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-40 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-9 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-46 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | RHOAI-2.14-RHEL-8 |
Unaffected:
v2.14.0-24 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.14::el8 |
||
| Red Hat | Red Hat OpenShift Data Science (RHODS) |
cpe:/a:redhat:openshift_data_science
|
Date Public
2024-08-07 00:00
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"attackVector": "NETWORK",
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"baseScore": 8.8,
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
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{
"url": "https://github.com/opendatahub-io/odh-dashboard/pull/3198"
}
],
"timeline": [
{
"lang": "en",
"time": "2024-08-06T10:31:41.202Z",
"value": "Reported to Red Hat."
},
{
"lang": "en",
"time": "2024-08-07T00:00:00.000Z",
"value": "Made public."
}
],
"title": "Odh-dashboard: odh-model-controller: cross-model authentication bypass in openshift ai",
"workarounds": [
{
"lang": "en",
"value": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability."
}
],
"x_generator": {
"engine": "cvelib 1.8.0"
},
"x_redhatCweChain": "CWE-305: Authentication Bypass by Primary Weakness"
}
},
"cveMetadata": {
"assignerOrgId": "53f830b8-0a3f-465b-8143-3b8a9948e749",
"assignerShortName": "redhat",
"cveId": "CVE-2024-7557",
"datePublished": "2024-08-08T21:33:14.505Z",
"dateReserved": "2024-08-06T11:08:34.986Z",
"dateUpdated": "2026-10-30T16:50:57.000Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.