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.
11421 vulnerabilities reference this CWE, most recent first.
GHSA-C8RX-J79X-463V
Vulnerability from github – Published: 2024-05-03 03:31 – Updated: 2024-05-03 03:31
VLAI
Details
PDF-XChange Editor EMF File Parsing Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of PDF-XChange Editor. 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 EMF 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 object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-22146.
Severity
{
"affected": [],
"aliases": [
"CVE-2023-42112"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-05-03T03:15:49Z",
"severity": "LOW"
},
"details": "PDF-XChange Editor EMF File Parsing Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of PDF-XChange Editor. 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 parsing of EMF files.\nThe issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-22146.",
"id": "GHSA-c8rx-j79x-463v",
"modified": "2024-05-03T03:31:02Z",
"published": "2024-05-03T03:31:02Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-42112"
},
{
"type": "WEB",
"url": "https://www.tracker-software.com/support/security-bulletins.html"
},
{
"type": "WEB",
"url": "https://www.zerodayinitiative.com/advisories/ZDI-23-1485"
}
],
"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-C8V3-RQ8C-88PW
Vulnerability from github – Published: 2023-06-13 09:30 – Updated: 2024-04-04 04:45
VLAI
Details
A vulnerability has been identified in JT2Go (All versions < V14.2.0.3), Teamcenter Visualization V13.2 (All versions < V13.2.0.13), Teamcenter Visualization V13.3 (All versions < V13.3.0.10), Teamcenter Visualization V14.0 (All versions < V14.0.0.6), Teamcenter Visualization V14.1 (All versions < V14.1.0.8), Teamcenter Visualization V14.2 (All versions < V14.2.0.3). The affected applications contain an out of bounds read past the end of an allocated buffer while parsing a specially crafted CGM file. This vulnerability could allow an attacker to disclose sensitive information.
Severity
{
"affected": [],
"aliases": [
"CVE-2023-33122"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-06-13T09:15:18Z",
"severity": "MODERATE"
},
"details": "A vulnerability has been identified in JT2Go (All versions \u003c V14.2.0.3), Teamcenter Visualization V13.2 (All versions \u003c V13.2.0.13), Teamcenter Visualization V13.3 (All versions \u003c V13.3.0.10), Teamcenter Visualization V14.0 (All versions \u003c V14.0.0.6), Teamcenter Visualization V14.1 (All versions \u003c V14.1.0.8), Teamcenter Visualization V14.2 (All versions \u003c V14.2.0.3). The affected applications contain an out of bounds read past the end of an allocated buffer while parsing a specially crafted CGM file. This vulnerability could allow an attacker to disclose sensitive information.",
"id": "GHSA-c8v3-rq8c-88pw",
"modified": "2024-04-04T04:45:55Z",
"published": "2023-06-13T09:30:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-33122"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/pdf/ssa-538795.pdf"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
}
]
}
GHSA-C8XG-PFCC-G4HX
Vulnerability from github – Published: 2021-12-27 00:01 – Updated: 2022-01-11 00:02
VLAI
Details
MediaTek microchips, as used in NETGEAR devices through 2021-11-11 and other devices, mishandle the WPS (Wi-Fi Protected Setup) protocol.
{
"affected": [],
"aliases": [
"CVE-2021-32468"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-12-26T00:15:00Z",
"severity": "HIGH"
},
"details": "MediaTek microchips, as used in NETGEAR devices through 2021-11-11 and other devices, mishandle the WPS (Wi-Fi Protected Setup) protocol.",
"id": "GHSA-c8xg-pfcc-g4hx",
"modified": "2022-01-11T00:02:09Z",
"published": "2021-12-27T00:01:59Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-32468"
},
{
"type": "WEB",
"url": "https://corp.mediatek.com/product-security-bulletin/January-2022"
},
{
"type": "WEB",
"url": "https://kb.netgear.com/000064368/Security-Advisory-for-WiFi-WPS-and-IEEE-1905-Vulnerabilities-on-Multiple-Products-PSV-2021-0298-PSV-2021-0300"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-C934-GQC3-VR25
Vulnerability from github – Published: 2023-11-17 12:30 – Updated: 2023-11-17 12:30
VLAI
Details
Adobe After Effects version 24.0.2 (and earlier) and 23.6 (and earlier) are 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-2023-47069"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-11-17T11:15:08Z",
"severity": "HIGH"
},
"details": "Adobe After Effects version 24.0.2 (and earlier) and 23.6 (and earlier) are 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-c934-gqc3-vr25",
"modified": "2023-11-17T12:30:19Z",
"published": "2023-11-17T12:30:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-47069"
},
{
"type": "WEB",
"url": "https://helpx.adobe.com/security/products/after_effects/apsb23-66.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-C93H-PCJ4-FRJ7
Vulnerability from github – Published: 2024-12-02 06:31 – Updated: 2025-02-03 21:31
VLAI
Details
In Telephony, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09289881; Issue ID: MSV-2025.
Severity
7.5 (High)
{
"affected": [],
"aliases": [
"CVE-2024-20129"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-12-02T04:15:05Z",
"severity": "HIGH"
},
"details": "In Telephony, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09289881; Issue ID: MSV-2025.",
"id": "GHSA-c93h-pcj4-frj7",
"modified": "2025-02-03T21:31:48Z",
"published": "2024-12-02T06:31:49Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-20129"
},
{
"type": "WEB",
"url": "https://corp.mediatek.com/product-security-bulletin/December-2024"
}
],
"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-C97C-6VC2-H97M
Vulnerability from github – Published: 2022-05-13 01:25 – Updated: 2022-05-13 01:25
VLAI
Details
An issue was discovered in FreeXL before 1.0.5. There is a heap-based buffer over-read in a memcpy call of the parse_SST function.
Severity
8.8 (High)
{
"affected": [],
"aliases": [
"CVE-2018-7437"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2018-02-23T21:29:00Z",
"severity": "HIGH"
},
"details": "An issue was discovered in FreeXL before 1.0.5. There is a heap-based buffer over-read in a memcpy call of the parse_SST function.",
"id": "GHSA-c97c-6vc2-h97m",
"modified": "2022-05-13T01:25:06Z",
"published": "2022-05-13T01:25:06Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-7437"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=1547885"
},
{
"type": "WEB",
"url": "https://groups.google.com/forum/#!topic/spatialite-users/b-d9iB5TDPE"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2018/03/msg00000.html"
},
{
"type": "WEB",
"url": "https://security.gentoo.org/glsa/202007-44"
},
{
"type": "WEB",
"url": "https://www.debian.org/security/2018/dsa-4129"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C984-XPMC-9M56
Vulnerability from github – Published: 2022-05-24 16:46 – Updated: 2024-04-04 00:46
VLAI
Details
Lack of input validation before copying can lead to a buffer over read in WLAN function in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8996AU, QCA6574AU, QCS605, SD 425, SD 427, SD 430, SD 435, SD 450, SD 625, SD 636, SD 675, SD 712 / SD 710 / SD 670, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM630, SDM660, SDX20, SDX24, SM7150
Severity
9.8 (Critical)
{
"affected": [],
"aliases": [
"CVE-2018-11937"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2019-05-24T17:29:00Z",
"severity": "CRITICAL"
},
"details": "Lack of input validation before copying can lead to a buffer over read in WLAN function in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8996AU, QCA6574AU, QCS605, SD 425, SD 427, SD 430, SD 435, SD 450, SD 625, SD 636, SD 675, SD 712 / SD 710 / SD 670, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM630, SDM660, SDX20, SDX24, SM7150",
"id": "GHSA-c984-xpmc-9m56",
"modified": "2024-04-04T00:46:54Z",
"published": "2022-05-24T16:46:33Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-11937"
},
{
"type": "WEB",
"url": "https://www.codeaurora.org/security-bulletin/2019/04/01/april-2019-code-aurora-security-bulletin"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C98F-FQ4V-V6R3
Vulnerability from github – Published: 2025-05-06 09:31 – Updated: 2025-05-06 09:31
VLAI
Details
Transient DOS while processing of a registration acceptance OTA due to incorrect ciphering key data IE.
Severity
7.5 (High)
{
"affected": [],
"aliases": [
"CVE-2024-49847"
],
"database_specific": {
"cwe_ids": [
"CWE-125",
"CWE-126"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-05-06T09:15:22Z",
"severity": "HIGH"
},
"details": "Transient DOS while processing of a registration acceptance OTA due to incorrect ciphering key data IE.",
"id": "GHSA-c98f-fq4v-v6r3",
"modified": "2025-05-06T09:31:33Z",
"published": "2025-05-06T09:31:33Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-49847"
},
{
"type": "WEB",
"url": "https://docs.qualcomm.com/product/publicresources/securitybulletin/may-2025-bulletin.html"
}
],
"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-C9F3-9WFR-WGH7
Vulnerability from github – Published: 2020-12-10 19:07 – Updated: 2024-10-28 20:02
VLAI
Summary
Lack of validation in data format attributes in TensorFlow
Details
Impact
The tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC.
However, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.
>>> import tensorflow as tf
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='1234', dst_format='1234')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='HHHH', dst_format='WWWW')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='H', dst_format='W')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1234', dst_format='1253')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1234', dst_format='1223')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1224', dst_format='1423')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='432')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='12345678', dst_format='87654321')
munmap_chunk(): invalid pointer
Aborted
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],
src_format='12345678', dst_format='87654321')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[71364624, 0],
[71365824, 0],
[ 560, 0],
[ 48, 0]], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],
src_format='12345678', dst_format='87654321')
free(): invalid next size (fast)
Aborted
A similar issue occurs in tf.raw_ops.DataFormatDimMap, for the same reasons:
>>> tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format='1234',
>>> dst_format='8765')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[1954047348, 1954047348],
[1852793646, 1852793646],
[1954047348, 1954047348],
[1852793632, 1852793632]], dtype=int32)>
Patches
We have patched the issue in GitHub commit ebc70b7a592420d3d2f359e4b1694c236b82c7ae and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.
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 members of the Aivul Team from Qihoo 360.
Severity
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.15.5"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.0.0"
},
{
"fixed": "2.0.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.1.0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.15.5"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.0.0"
},
{
"fixed": "2.0.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.1.0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.15.5"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.0.0"
},
{
"fixed": "2.0.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.1.0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2020-26267"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2020-12-10T19:05:08Z",
"nvd_published_at": "2020-12-10T23:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nThe `tf.raw_ops.DataFormatVecPermute` API does not validate the `src_format` and `dst_format` attributes. [The code](https://github.com/tensorflow/tensorflow/blob/304b96815324e6a73d046df10df6626d63ac12ad/tensorflow/core/kernels/data_format_ops.cc) assumes that these two arguments define a permutation of `NHWC`.\n\nHowever, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.\n\n```python\n\u003e\u003e\u003e import tensorflow as tf\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format=\u00271234\u0027, dst_format=\u00271234\u0027)\n\u003ctf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format=\u0027HHHH\u0027, dst_format=\u0027WWWW\u0027)\n\u003ctf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format=\u0027H\u0027, dst_format=\u0027W\u0027)\n\u003ctf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)\u003e\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], \n src_format=\u00271234\u0027, dst_format=\u00271253\u0027)\n\u003ctf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],\n src_format=\u00271234\u0027, dst_format=\u00271223\u0027)\n\u003ctf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],\n src_format=\u00271224\u0027, dst_format=\u00271423\u0027)\n\u003ctf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format=\u00271234\u0027, dst_format=\u0027432\u0027)\n\u003ctf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],\n src_format=\u002712345678\u0027, dst_format=\u002787654321\u0027)\nmunmap_chunk(): invalid pointer\nAborted\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], \n src_format=\u002712345678\u0027, dst_format=\u002787654321\u0027)\n\u003ctf.Tensor: shape=(4, 2), dtype=int32, numpy=\narray([[71364624, 0],\n [71365824, 0],\n [ 560, 0],\n [ 48, 0]], dtype=int32)\u003e\n...\n\u003e\u003e\u003e tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], \n src_format=\u002712345678\u0027, dst_format=\u002787654321\u0027)\nfree(): invalid next size (fast)\nAborted\n```\n\nA similar issue occurs in `tf.raw_ops.DataFormatDimMap`, for the same reasons:\n\n```python\n\u003e\u003e\u003e tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format=\u00271234\u0027,\n\u003e\u003e\u003e dst_format=\u00278765\u0027)\n\u003ctf.Tensor: shape=(4, 2), dtype=int32, numpy=\narray([[1954047348, 1954047348],\n [1852793646, 1852793646],\n [1954047348, 1954047348],\n [1852793632, 1852793632]], dtype=int32)\u003e\n```\n\n### Patches\nWe have patched the issue in GitHub commit [ebc70b7a592420d3d2f359e4b1694c236b82c7ae](https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\n\nSince this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.\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 members of the Aivul Team from Qihoo 360.",
"id": "GHSA-c9f3-9wfr-wgh7",
"modified": "2024-10-28T20:02:35Z",
"published": "2020-12-10T19:07:26Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9f3-9wfr-wgh7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-26267"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-298.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-333.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-140.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Lack of validation in data format attributes in TensorFlow"
}
GHSA-C9F5-29F6-C35W
Vulnerability from github – Published: 2024-12-20 06:30 – Updated: 2025-02-04 17:26
VLAI
Summary
Browsershot Improper Input Validation vulnerability
Details
Versions of the package spatie/browsershot before 5.0.3 are vulnerable to Improper Input Validation due to improper URL validation through the setUrl method. An attacker can exploit this vulnerability by utilizing view-source:file://, which allows for arbitrary file reading on a local file.
Note:
This is a bypass of the fix for CVE-2024-21544.
Severity
{
"affected": [
{
"package": {
"ecosystem": "Packagist",
"name": "spatie/browsershot"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.0.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2024-21549"
],
"database_specific": {
"cwe_ids": [
"CWE-125",
"CWE-20",
"CWE-200"
],
"github_reviewed": true,
"github_reviewed_at": "2024-12-20T15:08:54Z",
"nvd_published_at": "2024-12-20T05:15:06Z",
"severity": "MODERATE"
},
"details": "Versions of the package spatie/browsershot before 5.0.3 are vulnerable to Improper Input Validation due to improper URL validation through the setUrl method. An attacker can exploit this vulnerability by utilizing view-source:file://, which allows for arbitrary file reading on a local file.\n\n**Note:**\n\nThis is a bypass of the fix for [CVE-2024-21544](https://security.snyk.io/vuln/SNYK-PHP-SPATIEBROWSERSHOT-8496745).",
"id": "GHSA-c9f5-29f6-c35w",
"modified": "2025-02-04T17:26:43Z",
"published": "2024-12-20T06:30:45Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-21549"
},
{
"type": "WEB",
"url": "https://github.com/spatie/browsershot/commit/f791ce0ae8dd99367dbfa30588ee31e1196e1728"
},
{
"type": "PACKAGE",
"url": "https://github.com/spatie/browsershot"
},
{
"type": "WEB",
"url": "https://github.com/spatie/browsershot/discussions/906"
},
{
"type": "WEB",
"url": "https://security.snyk.io/vuln/SNYK-PHP-SPATIEBROWSERSHOT-8533023"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:H/SI:N/SA:N/E:P",
"type": "CVSS_V4"
}
],
"summary": "Browsershot Improper Input Validation vulnerability"
}
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.