RHSA-2026:59518
Vulnerability from csaf_redhat - Published: 2026-08-25 15:32 - Updated: 2026-08-25 16:13Summary
Red Hat Security Advisory: Red Hat AI Inference Server Model Optimization Tools 3.3.6 (CUDA)
Severity
Important
Notes
Topic: Red Hat AI Inference Server Model Optimization Tools 3.3.6 (CUDA) is now available.
Details: Red Hat® AI Inference Server Model Optimization Tools
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.
A flaw was found in AIOHTTP, an asynchronous HTTP client/server framework for asyncio and Python. An attacker could exploit this vulnerability by providing untrusted input to the `CookieJar.load()` function. This could potentially lead to arbitrary code execution, allowing the attacker to run malicious code on the affected system. This issue is most likely to occur in applications that allow attacker-controlled files to be loaded.
7.2 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow prior to 12.3.0. When an uncompressed McIdas AREA image is loaded from a filename through the mmap raw codec path, attacker-controlled header words can set a row stride smaller than the natural row width. Pixel access such as Image.tobytes(), getpixel, convert, or save can then read beyond the mapped region, disclosing adjacent process memory or causing a fault.
9.1 (Critical)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. When processing a specially crafted font file, the library's font compilation function does not adequately check for excessive memory allocation. This oversight allows a remote attacker to trigger an unreasonable consumption of system memory, leading to a denial of service (DoS) for the application.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. This vulnerability allows a remote attacker to cause a Denial of Service (DoS) by providing a specially crafted BDF font file. The library's image processing function fails to properly validate dimensions from the font file, bypassing a critical security check designed to prevent excessive memory usage. This oversight can lead to the system consuming an unreasonable amount of memory, making it unavailable to legitimate users.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. A remote attacker could exploit this vulnerability by providing a specially crafted GD 2.x image file. The GdImageFile._open() function reads image dimensions without proper validation, leading to excessive memory allocation. This can result in a Denial of Service (DoS) due to C-heap exhaustion.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. A remote attacker could exploit a vulnerability in the library's image processing functions, specifically when handling image coordinates near certain limits. This flaw, a native heap out-of-bounds write, could lead to a denial of service (DoS), making the affected system or application unavailable.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. A remote attacker could exploit a vulnerability in the PdfParser.PdfStream.decode() function when processing a crafted FlateDecode PDF stream. By providing a specially designed PDF file, the attacker could cause the application to exhaust available memory, leading to a denial of service (DoS).
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. A remote attacker could exploit this vulnerability by providing a specially crafted JPEG2000 image file. Due to incorrect calculation of memory requirements for image tiles, processing this file can lead to excessive memory consumption, resulting in a denial of service (DoS) through out-of-memory failures.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in Pillow, a Python imaging library. This vulnerability allows an attacker to trigger controlled native heap corruption by supplying an output image whose mode does not match the transform's declared output mode when using the ImageCms.ImageCmsTransform.apply API. This can lead to a denial of service (DoS) condition, making the affected system or application unavailable.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in pyasn1, a generic ASN.1 library for Python. The Basic Encoding Rules (BER) decoder, used by CER and DER codecs, processes long-form tags by accumulating continuation octets without an upper bound. A remote attacker can exploit this by providing a specially crafted input, leading to the construction of an arbitrarily large integer. This can cause the CPU cost to grow quadratically, resulting in a Denial of Service (DoS) for any application decoding untrusted BER, CER, or DER input.
5.9 (Medium)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Moderate
A flaw was found in pyasn1, a Python library for Abstract Syntax Notation One (ASN.1). The BER, CER, and DER decoders process OBJECT IDENTIFIER and RELATIVE-OID values in quadratic time relative to the number of arcs. A remote attacker could exploit this by providing a specially crafted payload containing an OID with many arcs, leading to excessive CPU consumption and a denial of service (DoS) in applications that decode untrusted ASN.1 data. The corresponding encoders also exhibit this quadratic behavior when re-encoding attacker-supplied values.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A remote attacker can exploit this by providing specially crafted BER/CER/DER-encoded ASN.1 data with a large exponent in the REAL value. When the application subsequently prints, logs, compares, or performs arithmetic on the decoded value, this can cause excessive CPU and memory consumption, leading to a denial of service (DoS).
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
References
95 references
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"title": "Statement"
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{
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
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"details": "If the application does not need JPEG2000 support, block .jp2, .j2k, .jpf, and .jpx uploads at the input layer.\n\nFor services that do process JPEG2000, set memory limits on the process or container (LimitAS= in systemd, or memory limits in Kubernetes/Podman) so a crafted image can only crash the worker, not the whole host. Add automatic restarts (Restart=always in systemd, or container restart policies) so the service recovers from OOM kills without someone having to intervene.",
"product_ids": [
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]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
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"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": [
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]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "Pillow: Pillow: Denial of Service via crafted JPEG2000 image"
},
{
"cve": "CVE-2026-59205",
"cwe": {
"id": "CWE-843",
"name": "Access of Resource Using Incompatible Type (\u0027Type Confusion\u0027)"
},
"discovery_date": "2026-07-14T17:02:11.367224+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2500052"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Pillow, a Python imaging library. This vulnerability allows an attacker to trigger controlled native heap corruption by supplying an output image whose mode does not match the transform\u0027s declared output mode when using the ImageCms.ImageCmsTransform.apply API. This can lead to a denial of service (DoS) condition, making the affected system or application unavailable.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "Pillow: Pillow: Controlled native heap corruption in ImageCms.ImageCmsTransform.apply API",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "The impact is limited to denial of service. While the underlying issue is heap corruption via mode mismatch, it does not provide a controlled write primitive exploitable for code execution in affected Red Hat products.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
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]
},
"references": [
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"category": "self",
"summary": "Canonical URL",
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},
{
"category": "external",
"summary": "RHBZ#2500052",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2500052"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-59205",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-59205"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-59205",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59205"
},
{
"category": "external",
"summary": "https://github.com/python-pillow/Pillow/commit/a9ffc42bedf4fc0a7ef8d6486e7f9e81e3397721",
"url": "https://github.com/python-pillow/Pillow/commit/a9ffc42bedf4fc0a7ef8d6486e7f9e81e3397721"
},
{
"category": "external",
"summary": "https://github.com/python-pillow/Pillow/pull/9715",
"url": "https://github.com/python-pillow/Pillow/pull/9715"
},
{
"category": "external",
"summary": "https://github.com/python-pillow/Pillow/releases/tag/12.3.0",
"url": "https://github.com/python-pillow/Pillow/releases/tag/12.3.0"
},
{
"category": "external",
"summary": "https://github.com/python-pillow/Pillow/security/advisories/GHSA-9hw9-ch79-4vh6",
"url": "https://github.com/python-pillow/Pillow/security/advisories/GHSA-9hw9-ch79-4vh6"
}
],
"release_date": "2026-07-14T15:48:39.962000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-08-25T15:32:43+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:59518",
"product_ids": [
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"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:59518"
},
{
"category": "workaround",
"details": "Most applications using Pillow\u0027s color management via profileToProfile() or applyTransform() are not exposed. Only code that calls ImageCmsTransform.apply() directly with a user-controlled output image whose mode does not match the transform can trigger the heap corruption. Audit your code for direct apply() calls to confirm.\n\nRHEL builds ship with ASLR, full RELRO/PIE, and FORTIFY_SOURCE by default, making escalation from crash to code execution much harder. For DoS containment, configure automatic service restart (Restart=always in systemd, or container restart policies) so the process recovers without manual intervention.",
"product_ids": [
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]
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"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"
},
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"threats": [
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"category": "impact",
"details": "Important"
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"title": "Pillow: Pillow: Controlled native heap corruption in ImageCms.ImageCmsTransform.apply API"
},
{
"cve": "CVE-2026-59884",
"cwe": {
"id": "CWE-770",
"name": "Allocation of Resources Without Limits or Throttling"
},
"discovery_date": "2026-07-14T18:07:49.497763+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2500204"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in pyasn1, a generic ASN.1 library for Python. The Basic Encoding Rules (BER) decoder, used by CER and DER codecs, processes long-form tags by accumulating continuation octets without an upper bound. A remote attacker can exploit this by providing a specially crafted input, leading to the construction of an arbitrarily large integer. This can cause the CPU cost to grow quadratically, resulting in a Denial of Service (DoS) for any application decoding untrusted BER, CER, or DER input.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "python-pyasn1: pyasn1: Denial of Service via crafted BER input",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "A flaw was found in pyasn1\u0027s BER decoder. The decoder parses long-form tags by accumulating continuation octets without an upper bound, allowing crafted input to force construction of an arbitrarily large integer with quadratic CPU cost. On Python 3.11+, this can also trigger unhandled ValueError exceptions. Exploitation requires that an application passes untrusted BER, CER, or DER input directly to the pyasn1 decoder \u2014 pyasn1 is a library and does not independently accept network input. Many common uses of pyasn1 involve parsing trusted certificates or local configuration and are not exposed to this flaw. The realistic impact is a denial-of-service of the consuming Python process, with automatic recovery in typical service deployments.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64",
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"references": [
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"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-59884"
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{
"category": "external",
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"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2500204"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-59884",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-59884"
},
{
"category": "external",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59884"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/commit/628e36ecbb5277a3f01572ce418ef54271b165a5",
"url": "https://github.com/pyasn1/pyasn1/commit/628e36ecbb5277a3f01572ce418ef54271b165a5"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.4",
"url": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.4"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-m4p7-r5rc-7g4j",
"url": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-m4p7-r5rc-7g4j"
}
],
"release_date": "2026-07-14T16:41:10.277000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-08-25T15:32:43+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:59518",
"product_ids": [
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"category": "workaround",
"details": "Update to pyasn1 version 0.6.4 or later when available for your product stream. The impact is limited to availability (denial of service) \u2014 an attacker cannot access or modify data. Applications that do not process untrusted ASN.1/BER input are at reduced risk.",
"product_ids": [
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"scores": [
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"cvss_v3": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 5.9,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"products": [
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]
}
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"threats": [
{
"category": "impact",
"details": "Moderate"
}
],
"title": "python-pyasn1: pyasn1: Denial of Service via crafted BER input"
},
{
"cve": "CVE-2026-59885",
"cwe": {
"id": "CWE-1050",
"name": "Excessive Platform Resource Consumption within a Loop"
},
"discovery_date": "2026-07-14T18:17:12.157807+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2500380"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in pyasn1, a Python library for Abstract Syntax Notation One (ASN.1). The BER, CER, and DER decoders process OBJECT IDENTIFIER and RELATIVE-OID values in quadratic time relative to the number of arcs. A remote attacker could exploit this by providing a specially crafted payload containing an OID with many arcs, leading to excessive CPU consumption and a denial of service (DoS) in applications that decode untrusted ASN.1 data. The corresponding encoders also exhibit this quadratic behavior when re-encoding attacker-supplied values.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "pyasn1: python-pyasn1: pyasn1: Denial of Service via crafted ASN.1 OBJECT IDENTIFIER",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "A flaw was found in pyasn1. The BER, CER, and DER decoders process OBJECT IDENTIFIER and RELATIVE-OID values in quadratic time relative to the number of arcs. A small crafted payload containing an OID with many arcs consumes excessive CPU per decode() call, allowing denial of service in applications that decode untrusted ASN.1 data (certificates, LDAP, SNMP, Kerberos). The corresponding encoders exhibit the same behavior when re-encoding attacker-supplied values. The arc-size limit introduced for CVE-2026-23490 does not mitigate this issue. This issue is fixed in pyasn1 version 0.6.4.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
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"references": [
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"summary": "Canonical URL",
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"category": "external",
"summary": "RHBZ#2500380",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2500380"
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{
"category": "external",
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"url": "https://www.cve.org/CVERecord?id=CVE-2026-59885"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-59885",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59885"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/commit/45bdb19eb7df4b3780fe9c912c63e99bffc39dd9",
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"url": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.4"
},
{
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"url": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-8ppf-4f7h-5ppj"
}
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"release_date": "2026-07-14T16:40:00.515000+00:00",
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"date": "2026-08-25T15:32:43+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:59518",
"product_ids": [
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"product_ids": [
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"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": [
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"threats": [
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"category": "impact",
"details": "Important"
}
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"title": "pyasn1: python-pyasn1: pyasn1: Denial of Service via crafted ASN.1 OBJECT IDENTIFIER"
},
{
"cve": "CVE-2026-59886",
"cwe": {
"id": "CWE-770",
"name": "Allocation of Resources Without Limits or Throttling"
},
"discovery_date": "2026-07-14T17:01:19.689422+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2500041"
}
],
"notes": [
{
"category": "description",
"text": "A remote attacker can exploit this by providing specially crafted BER/CER/DER-encoded ASN.1 data with a large exponent in the REAL value. When the application subsequently prints, logs, compares, or performs arithmetic on the decoded value, this can cause excessive CPU and memory consumption, leading to a denial of service (DoS).",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "pyasn1: pyasn1: Denial of Service via crafted ASN.1 REAL values",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This flaw in pyasn1, rated as Important, could lead to a denial of service in Red Hat products that process untrusted ASN.1 data. A remote attacker could send a specially crafted BER, CER, or DER encoded REAL value with a large exponent, causing applications to consume excessive resources during decoding operations such as printing, logging, or arithmetic, thereby rendering the service unavailable.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-59886"
},
{
"category": "external",
"summary": "RHBZ#2500041",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2500041"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-59886",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-59886"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-59886",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59886"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/commit/e60c691cb91addb8fcefa2f537e85ede6fb1e886",
"url": "https://github.com/pyasn1/pyasn1/commit/e60c691cb91addb8fcefa2f537e85ede6fb1e886"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.4",
"url": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.4"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-hm4w-wwcw-mr6r",
"url": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-hm4w-wwcw-mr6r"
}
],
"release_date": "2026-07-14T16:38:29.691000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-08-25T15:32:43+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:59518",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:59518"
},
{
"category": "workaround",
"details": "When processing untrusted ASN.1 data with pyasn1, avoid calling prettyPrint(), str(), float(), int(), or performing comparisons or arithmetic on decoded Real (ASN.1 REAL type) objects. Instead, inspect the raw (mantissa, base, exponent) tuple directly. Where logging decoded ASN.1 structures is necessary, filter out or sanitize Real-typed values before conversion.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64"
]
}
],
"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 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:5417790c2abbff7a0b4ca9fcd672a8e613a1cdfe2cf8afa10ec47a8883905189_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/model-opt-cuda-rhel9@sha256:946b96330ca0c947dd81e282f084505b44c960b95e0597d9f33cf2b401ee5861_arm64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "pyasn1: pyasn1: Denial of Service via crafted ASN.1 REAL values"
}
]
}
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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.
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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.
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.
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