Common Weakness Enumeration
CWE-125
AllowedOut-of-bounds Read
Abstraction: Base · Status: Draft
The product reads data past the end, or before the beginning, of the intended buffer.
11721 vulnerabilities reference this CWE, most recent first.
GHSA-9X77-R8VF-HC6H
Vulnerability from github – Published: 2025-04-12 03:30 – Updated: 2025-04-12 03:30
VLAI
Details
Out-of-bounds read in Microsoft Edge (Chromium-based) allows an unauthorized attacker to execute code over a network.
Severity
7.5 (High)
{
"affected": [],
"aliases": [
"CVE-2025-29834"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-04-12T02:15:22Z",
"severity": "HIGH"
},
"details": "Out-of-bounds read in Microsoft Edge (Chromium-based) allows an unauthorized attacker to execute code over a network.",
"id": "GHSA-9x77-r8vf-hc6h",
"modified": "2025-04-12T03:30:30Z",
"published": "2025-04-12T03:30:30Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-29834"
},
{
"type": "WEB",
"url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-29834"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-9X78-PM4G-7R7H
Vulnerability from github – Published: 2022-06-15 00:00 – Updated: 2022-06-23 00:00
VLAI
Details
Possible buffer over read due to improper calculation of string length while parsing Id3 tag in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables
Severity
7.5 (High)
{
"affected": [],
"aliases": [
"CVE-2021-35100"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-06-14T10:15:00Z",
"severity": "HIGH"
},
"details": "Possible buffer over read due to improper calculation of string length while parsing Id3 tag in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice \u0026 Music, Snapdragon Wearables",
"id": "GHSA-9x78-pm4g-7r7h",
"modified": "2022-06-23T00:00:27Z",
"published": "2022-06-15T00:00:26Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-35100"
},
{
"type": "WEB",
"url": "https://www.qualcomm.com/company/product-security/bulletins/april-2022-bulletin"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-9X9H-PRGP-9C4C
Vulnerability from github – Published: 2023-07-12 18:30 – Updated: 2024-04-04 06:04
VLAI
Details
Adobe InDesign versions ID18.3 (and earlier) and ID17.4.1 (and earlier) are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2023-29314"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-07-12T16:15:12Z",
"severity": "MODERATE"
},
"details": "Adobe InDesign versions ID18.3 (and earlier) and ID17.4.1 (and earlier) are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
"id": "GHSA-9x9h-prgp-9c4c",
"modified": "2024-04-04T06:04:44Z",
"published": "2023-07-12T18:30:38Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-29314"
},
{
"type": "WEB",
"url": "https://helpx.adobe.com/security/products/indesign/apsb23-38.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
}
]
}
GHSA-9X9P-7F3C-4RVQ
Vulnerability from github – Published: 2022-05-13 01:01 – Updated: 2025-04-20 03:30
VLAI
Details
A large out-of-bounds read on the heap vulnerability in Foxit PDF Reader can potentially be abused for information disclosure. Combined with another vulnerability, it can be used to leak heap memory layout and in bypassing ASLR.
Severity
{
"affected": [],
"aliases": [
"CVE-2016-8334"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2017-01-06T21:59:00Z",
"severity": "MODERATE"
},
"details": "A large out-of-bounds read on the heap vulnerability in Foxit PDF Reader can potentially be abused for information disclosure. Combined with another vulnerability, it can be used to leak heap memory layout and in bypassing ASLR.",
"id": "GHSA-9x9p-7f3c-4rvq",
"modified": "2025-04-20T03:30:50Z",
"published": "2022-05-13T01:01:12Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2016-8334"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/bid/93799"
},
{
"type": "WEB",
"url": "http://www.talosintelligence.com/reports/TALOS-2016-0201"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
}
]
}
GHSA-9XC9-4X73-F9WH
Vulnerability from github – Published: 2022-01-14 00:01 – Updated: 2022-01-15 00:02
VLAI
Details
This vulnerability allows remote attackers to disclose sensitive information on affected installations of Bentley View 10.15.0.75. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of JP2 files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated buffer. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-14835.
{
"affected": [],
"aliases": [
"CVE-2021-34882"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-01-13T22:15:00Z",
"severity": "MODERATE"
},
"details": "This vulnerability allows remote attackers to disclose sensitive information on affected installations of Bentley View 10.15.0.75. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of JP2 files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated buffer. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-14835.",
"id": "GHSA-9xc9-4x73-f9wh",
"modified": "2022-01-15T00:02:37Z",
"published": "2022-01-14T00:01:43Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-34882"
},
{
"type": "WEB",
"url": "https://www.bentley.com/en/common-vulnerability-exposure/BE-2021-0008"
},
{
"type": "WEB",
"url": "https://www.zerodayinitiative.com/advisories/ZDI-21-1471"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-9XF5-74JV-Q5Q9
Vulnerability from github – Published: 2023-03-28 21:30 – Updated: 2023-03-28 21:30
VLAI
Details
Adobe Dimension versions 3.4.7 (and earlier) is affected by an out-of-bounds read vulnerability when parsing a crafted file, which could result in a read past the end of an allocated memory structure. An attacker could leverage this vulnerability to execute code in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.
Severity
7.8 (High)
{
"affected": [],
"aliases": [
"CVE-2023-25891"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-03-28T20:15:00Z",
"severity": "HIGH"
},
"details": "Adobe Dimension versions 3.4.7 (and earlier) is affected by an out-of-bounds read vulnerability when parsing a crafted file, which could result in a read past the end of an allocated memory structure. An attacker could leverage this vulnerability to execute code in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
"id": "GHSA-9xf5-74jv-q5q9",
"modified": "2023-03-28T21:30:19Z",
"published": "2023-03-28T21:30:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-25891"
},
{
"type": "WEB",
"url": "https://helpx.adobe.com/security/products/dimension/apsb23-20.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-9XGG-F64G-3XRF
Vulnerability from github – Published: 2024-05-03 03:31 – Updated: 2024-05-03 03:31
VLAI
Details
Foxit PDF Reader combobox Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of Foxit PDF Reader. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the handling of combobox fields. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated buffer. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-21870.
Severity
{
"affected": [],
"aliases": [
"CVE-2023-51550"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-05-03T03:16:13Z",
"severity": "LOW"
},
"details": "Foxit PDF Reader combobox Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of Foxit PDF Reader. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the handling of combobox fields. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated buffer. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-21870.",
"id": "GHSA-9xgg-f64g-3xrf",
"modified": "2024-05-03T03:31:06Z",
"published": "2024-05-03T03:31:06Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-51550"
},
{
"type": "WEB",
"url": "https://www.foxit.com/support/security-bulletins.html"
},
{
"type": "WEB",
"url": "https://www.zerodayinitiative.com/advisories/ZDI-23-1864"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
}
]
}
GHSA-9XGV-7FJQ-CCW2
Vulnerability from github – Published: 2022-09-01 00:00 – Updated: 2022-09-08 00:00
VLAI
Details
A race condition was found in the Linux kernel's IP framework for transforming packets (XFRM subsystem) when multiple calls to xfrm_probe_algs occurred simultaneously. This flaw could allow a local attacker to potentially trigger an out-of-bounds write or leak kernel heap memory by performing an out-of-bounds read and copying it into a socket.
Severity
7.0 (High)
{
"affected": [],
"aliases": [
"CVE-2022-3028"
],
"database_specific": {
"cwe_ids": [
"CWE-125",
"CWE-362"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-08-31T16:15:00Z",
"severity": "HIGH"
},
"details": "A race condition was found in the Linux kernel\u0027s IP framework for transforming packets (XFRM subsystem) when multiple calls to xfrm_probe_algs occurred simultaneously. This flaw could allow a local attacker to potentially trigger an out-of-bounds write or leak kernel heap memory by performing an out-of-bounds read and copying it into a socket.",
"id": "GHSA-9xgv-7fjq-ccw2",
"modified": "2022-09-08T00:00:28Z",
"published": "2022-09-01T00:00:24Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-3028"
},
{
"type": "WEB",
"url": "https://github.com/torvalds/linux/commit/ba953a9d89a00c078b85f4b190bc1dde66fe16b5"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2022/10/msg00000.html"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2022/11/msg00001.html"
},
{
"type": "WEB",
"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/F3MYP7WX4PNE6RCITVXA43CECBZT4CL6"
},
{
"type": "WEB",
"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JKVA75UHKVOHNOEPCLUHTFGWCOOUBDM3"
},
{
"type": "WEB",
"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PEQYVCNYUWB4CJ2YRAYNF2GGFQ7SUYC4"
},
{
"type": "WEB",
"url": "https://lore.kernel.org/all/YtoWqEkKzvimzWS5@gondor.apana.org.au/T"
},
{
"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20230214-0004"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-9XH4-23Q4-V6WR
Vulnerability from github – Published: 2021-05-21 14:26 – Updated: 2024-11-13 15:59
VLAI
Summary
Heap buffer overflow and undefined behavior in `FusedBatchNorm`
Details
Impact
The implementation of tf.raw_ops.FusedBatchNorm is vulnerable to a heap buffer overflow:
import tensorflow as tf
x = tf.zeros([10, 10, 10, 6], dtype=tf.float32)
scale = tf.constant([0.0], shape=[1], dtype=tf.float32)
offset = tf.constant([0.0], shape=[1], dtype=tf.float32)
mean = tf.constant([0.0], shape=[1], dtype=tf.float32)
variance = tf.constant([0.0], shape=[1], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False
tf.raw_ops.FusedBatchNorm(
x=x, scale=scale, offset=offset, mean=mean, variance=variance,
epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,
data_format=data_format, is_training=is_training)
If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers:
import tensorflow as tf
import numpy as np
x = tf.zeros([10, 10, 10, 1], dtype=tf.float32)
scale = tf.constant([], shape=[0], dtype=tf.float32)
offset = tf.constant([], shape=[0], dtype=tf.float32)
mean = tf.constant([], shape=[0], dtype=tf.float32)
variance = tf.constant([], shape=[0], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False
tf.raw_ops.FusedBatchNorm(
x=x, scale=scale, offset=offset, mean=mean, variance=variance,
epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,
data_format=data_format, is_training=is_training)
The implementation fails to validate that scale, offset, mean and variance (the last two only when required) all have the same number of elements as the number of channels of x. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary.
If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior.
Patches
We have patched the issue in GitHub commit 6972f9dfe325636b3db4e0bc517ee22a159365c0.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
Severity
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2021-29583"
],
"database_specific": {
"cwe_ids": [
"CWE-125",
"CWE-476",
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T17:28:58Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nThe implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow:\n \n```python\nimport tensorflow as tf\n\nx = tf.zeros([10, 10, 10, 6], dtype=tf.float32)\nscale = tf.constant([0.0], shape=[1], dtype=tf.float32)\noffset = tf.constant([0.0], shape=[1], dtype=tf.float32)\nmean = tf.constant([0.0], shape=[1], dtype=tf.float32)\nvariance = tf.constant([0.0], shape=[1], dtype=tf.float32)\nepsilon = 0.0\nexponential_avg_factor = 0.0\ndata_format = \"NHWC\"\nis_training = False\n \ntf.raw_ops.FusedBatchNorm(\n x=x, scale=scale, offset=offset, mean=mean, variance=variance,\n epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,\n data_format=data_format, is_training=is_training)\n```\n \nIf the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers:\n\n```python \nimport tensorflow as tf\nimport numpy as np\n\nx = tf.zeros([10, 10, 10, 1], dtype=tf.float32)\nscale = tf.constant([], shape=[0], dtype=tf.float32)\noffset = tf.constant([], shape=[0], dtype=tf.float32)\nmean = tf.constant([], shape=[0], dtype=tf.float32)\nvariance = tf.constant([], shape=[0], dtype=tf.float32)\nepsilon = 0.0\nexponential_avg_factor = 0.0\ndata_format = \"NHWC\"\nis_training = False\n\ntf.raw_ops.FusedBatchNorm(\n x=x, scale=scale, offset=offset, mean=mean, variance=variance, \n epsilon=epsilon, exponential_avg_factor=exponential_avg_factor,\n data_format=data_format, is_training=is_training)\n``` \n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary.\n\nIf the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [6972f9dfe325636b3db4e0bc517ee22a159365c0](https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.",
"id": "GHSA-9xh4-23q4-v6wr",
"modified": "2024-11-13T15:59:06Z",
"published": "2021-05-21T14:26:35Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9xh4-23q4-v6wr"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29583"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-511.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-709.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-220.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Heap buffer overflow and undefined behavior in `FusedBatchNorm`"
}
GHSA-9XH8-4CJJ-QF63
Vulnerability from github – Published: 2024-05-16 21:31 – Updated: 2024-05-16 21:31
VLAI
Details
Out-of-bounds read in Intel(R) Media SDK and some Intel(R) oneVPL software before version 23.3.5 may allow an authenticated user to potentially enable escalation of privilege via local access.
Severity
{
"affected": [],
"aliases": [
"CVE-2023-22656"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-05-16T21:15:50Z",
"severity": "LOW"
},
"details": "Out-of-bounds read in Intel(R) Media SDK and some Intel(R) oneVPL software before version 23.3.5 may allow an authenticated user to potentially enable escalation of privilege via local access.",
"id": "GHSA-9xh8-4cjj-qf63",
"modified": "2024-05-16T21:31:58Z",
"published": "2024-05-16T21:31:58Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-22656"
},
{
"type": "WEB",
"url": "https://www.intel.com/content/www/us/en/security-center/advisory/intel-sa-00935.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:N",
"type": "CVSS_V3"
}
]
}
Mitigation MIT-5
Implementation
Strategy: Input Validation
- Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
- When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
- Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.
Mitigation
Architecture and Design
Strategy: Language Selection
Use a language that provides appropriate memory abstractions.
CAPEC-540: Overread Buffers
An adversary attacks a target by providing input that causes an application to read beyond the boundary of a defined buffer. This typically occurs when a value influencing where to start or stop reading is set to reflect positions outside of the valid memory location of the buffer. This type of attack may result in exposure of sensitive information, a system crash, or arbitrary code execution.