RHSA-2026:24541

Vulnerability from csaf_redhat - Published: 2026-06-08 17:51 - Updated: 2026-06-12 09:48
Summary
Red Hat Security Advisory: Red Hat AI Inference 3.4.1 (spyre)
Severity
Important
Notes
Topic: Red Hat AI Inference 3.4.1 (spyre) is now available.
Details: Red Hat AI Inference
Terms of Use: This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original.
CVE-2026-44431

A flaw was found in urllib3, an HTTP client library for Python. When using the low-level API via `ProxyManager.connection_from_url().urlopen()` with `assert_same_host=False`, cross-origin redirects can still forward sensitive headers. This could allow a remote attacker to gain unauthorized access to sensitive information.

5.9 (Medium)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N
CWE-201 - Insertion of Sensitive Information Into Sent Data
Affected products
Product Identifier Version Remediation
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:a89b09f6ec94078c599339b7feee9a0ddfc8048b748169310ed03f4c652d11f8_s390x —
Vendor Fix fix
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:e12e1c6d65d4b41e530057a37765f36afcfa4e1cf85996bb4ebe13cef713b7d3_amd64 —
Vendor Fix fix
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:f4aa279db2108029bfd1aa1329bccb7144a166fccbbc1d670494f2106d847691_ppc64le —
Vendor Fix fix
Threats
Impact Moderate
CVE-2026-44432

A flaw was found in urllib3, an HTTP client library for Python. This vulnerability allows a remote attacker to cause excessive resource consumption, such as high CPU usage and massive memory allocation, on the client side. This occurs when urllib3 attempts to decompress an entire HTTP response, even if only a partial read was requested, or when draining the connection after a partial decompression. This can lead to a Denial of Service (DoS) condition.

7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CWE-409 - Improper Handling of Highly Compressed Data (Data Amplification)
Affected products
Product Identifier Version Remediation
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:a89b09f6ec94078c599339b7feee9a0ddfc8048b748169310ed03f4c652d11f8_s390x —
Vendor Fix fix
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:e12e1c6d65d4b41e530057a37765f36afcfa4e1cf85996bb4ebe13cef713b7d3_amd64 —
Vendor Fix fix
Unresolved product id: Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:f4aa279db2108029bfd1aa1329bccb7144a166fccbbc1d670494f2106d847691_ppc64le —
Vendor Fix fix
Threats
Impact Important
References
To clipboard 

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          "details": "For more information visit https://access.redhat.com/errata/RHSA-2026:24541",
          "product_ids": [
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:a89b09f6ec94078c599339b7feee9a0ddfc8048b748169310ed03f4c652d11f8_s390x",
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:e12e1c6d65d4b41e530057a37765f36afcfa4e1cf85996bb4ebe13cef713b7d3_amd64",
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:f4aa279db2108029bfd1aa1329bccb7144a166fccbbc1d670494f2106d847691_ppc64le"
          ],
          "restart_required": {
            "category": "none"
          },
          "url": "https://access.redhat.com/errata/RHSA-2026:24541"
        }
      ],
      "scores": [
        {
          "cvss_v3": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 7.5,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          },
          "products": [
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:a89b09f6ec94078c599339b7feee9a0ddfc8048b748169310ed03f4c652d11f8_s390x",
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:e12e1c6d65d4b41e530057a37765f36afcfa4e1cf85996bb4ebe13cef713b7d3_amd64",
            "Red Hat AI Inference Server 3.4:registry.redhat.io/rhaii/vllm-spyre-rhel9@sha256:f4aa279db2108029bfd1aa1329bccb7144a166fccbbc1d670494f2106d847691_ppc64le"
          ]
        }
      ],
      "threats": [
        {
          "category": "impact",
          "details": "Important"
        }
      ],
      "title": "urllib3: urllib3: Denial of Service due to excessive HTTP response decompression"
    }
  ]
}


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Tags
Taxonomy of the tags.





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.


Detection rules are retrieved from Rulezet.