rainbutterfly/cve_corpus huggingface dataset:
CVE-2022-21721 DOS Vulnerability in next.js
Next.js is a React framework. Starting with version 12.0.0 and prior to version 12.0.9, vulnerable code could allow a bad actor to trigger a denial of service attack for anyone using i18n functionality. In order to be affected by this CVE, one must use next start or a custom server and the built-in i18n support. Deployments on Vercel, along with similar environments where invalid requests are filtered before reaching Next.js, are not affected. A patch has been released, `next@12.0.9`, that mitigates this issue. As a workaround, one may ensure `/${locale}/_next/` is blocked from reaching the Next.js instance until it becomes feasible to upgrade.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: 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
Published: 2022-01-28T22:00:17.000Z
CVE-2022-21722 Potential out-of-bound read during RTP/RTCP parsing in PJSIP
PJSIP is a free and open source multimedia communication library written in C language implementing standard based protocols such as SIP, SDP, RTP, STUN, TURN, and ICE. In version 2.11.1 and prior, there are various cases where it is possible that certain incoming RTP/RTCP packets can potentially cause out-of-bound read access. This issue affects all users that use PJMEDIA and accept incoming RTP/RTCP. A patch is available as a commit in the `master` branch. There are no known workarounds.
Problem types: cwe_id: CWE-125
description: CWE-125: Out-of-bounds Read
Affected products: vendor: pjsip
product: pjproject
CVSS v3.1: version: 3.1
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H
attackVector: NETWORK
attackComplexity: LOW
privilegesRequired: NONE
userInteraction: NONE
scope: UNCHANGED
confidentialityImpact: HIGH
integrityImpact: NONE
availabilityImpact: HIGH
baseScore: 9.1
baseSeverity: CRITICAL
Published: 2022-01-27T00:00:00.000Z
CVE-2022-21723 Out-of-bounds read in multipart parsing in PJSIP
PJSIP is a free and open source multimedia communication library written in C language implementing standard based protocols such as SIP, SDP, RTP, STUN, TURN, and ICE. In versions 2.11.1 and prior, parsing an incoming SIP message that contains a malformed multipart can potentially cause out-of-bound read access. This issue affects all PJSIP users that accept SIP multipart. The patch is available as commit in the `master` branch. There are no known workarounds.
Problem types: cwe_id: CWE-125
description: CWE-125: Out-of-bounds Read
Affected products: vendor: pjsip
product: pjproject
CVSS v3.1: version: 3.1
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H
attackVector: NETWORK
attackComplexity: LOW
privilegesRequired: NONE
userInteraction: NONE
scope: UNCHANGED
confidentialityImpact: HIGH
integrityImpact: NONE
availabilityImpact: HIGH
baseScore: 9.1
baseSeverity: CRITICAL
Published: 2022-01-27T00:00:00.000Z
CVE-2022-21724 Unchecked Class Instantiation when providing Plugin Classes
pgjdbc is the offical PostgreSQL JDBC Driver. A security hole was found in the jdbc driver for postgresql database while doing security research. The system using the postgresql library will be attacked when attacker control the jdbc url or properties. pgjdbc instantiates plugin instances based on class names provided via `authenticationPluginClassName`, `sslhostnameverifier`, `socketFactory`, `sslfactory`, `sslpasswordcallback` connection properties. However, the driver did not verify if the class implements the expected interface before instantiating the class. This can lead to code execution loaded via arbitrary classes. Users using plugins are advised to upgrade. There are no known workarounds for this issue.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: HIGH
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 7
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
version: 3.1
Published: 2022-02-02T11:48:52.000Z
CVE-2022-21725 Division by zero in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T12:21:02.000Z
CVE-2022-21726 Out of bounds read in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 8.1
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
version: 3.1
Published: 2022-02-03T11:01:42.000Z
CVE-2022-21727 Integer overflow in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 7.6
baseSeverity: HIGH
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
version: 3.1
Published: 2022-02-03T11:07:40.000Z
CVE-2022-21728 Out of bounds read in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 8.1
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
version: 3.1
Published: 2022-02-03T10:55:55.000Z
CVE-2022-21729 Overflow and uncaught divide by zero in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `UnravelIndex` is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T12:28:25.000Z
CVE-2022-21730 Out of bounds read in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 8.1
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
version: 3.1
Published: 2022-02-03T10:48:29.000Z
CVE-2022-21731 Type confusion leading to segfault in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T11:37:56.000Z
CVE-2022-21732 Memory exhaustion in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 4.3
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
version: 3.1
Published: 2022-02-03T11:21:48.000Z
CVE-2022-21733 Memory exhaustion in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 4.3
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
version: 3.1
Published: 2022-02-03T11:28:10.000Z
CVE-2022-21734 `CHECK`-failures in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `MapStage` is vulnerable a `CHECK`-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T12:59:18.000Z
CVE-2022-21735 Division by zero in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T12:53:48.000Z
CVE-2022-21736 Undefined behavior in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseTensorSliceDataset` has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value. The 3 input arguments to `SparseTensorSliceDataset` represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 7.6
baseSeverity: HIGH
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
version: 3.1
Published: 2022-02-03T12:08:03.000Z
CVE-2022-21737 Assertion failure based denial of service in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T13:43:21.000Z
CVE-2022-21738 Integer overflow leading to crash in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T13:19:05.000Z
CVE-2022-21739 Null pointer dereference in TensorFlow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T13:13:52.000Z
CVE-2022-21740 Heap overflow in Tensorflow
Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 7.6
baseSeverity: HIGH
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
version: 3.1
Published: 2022-02-03T14:30:47.000Z
CVE-2022-21741 Division by zero in TFLite
Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Problem types: description: n/a
Affected products: vendor: n/a
product: n/a
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-02-03T14:27:31.000Z
CVE-2022-21742 Realtek USB FE/1GbE/2.5GbE/5GbE NIC Family - Buffer Overflow
Realtek USB driver has a buffer overflow vulnerability due to insufficient parameter length verification in the API function. An unauthenticated LAN attacker can exploit this vulnerability to disrupt services.
Problem types: cwe_id: CWE-120
description: CWE-120 Buffer Overflow
Affected products: vendor: Realtek
product: USB FE/1GbE/2.5GbE/5GbE NIC Family
vendor: Realtek
product: USB FE/1GbE/2.5GbE/5GbE NIC Family
vendor: Realtek
product: USB FE/1GbE/2.5GbE/5GbE NIC Family
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 6.2
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Credits: lang: en
value: Realtek
Published: 2022-06-20T05:30:28.159Z
CVE-2022-21743 
In ion, there is a possible use after free due to an integer overflow. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS06371108; Issue ID: ALPS06371108.
Problem types: description: Elevation of Privilege
Affected products: vendor: MediaTek, Inc.
product: MT6580, MT6735, MT6737, MT6739, MT6750, MT6750S, MT6753, MT6757, MT6757C, MT6757CD, MT6757CH, MT6761, MT6762, MT6763, MT6765, MT6768, MT6769, MT6771, MT6779, MT6781, MT6785, MT6797, MT6833, MT6853, MT6853T, MT6873, MT6875, MT6877, MT6883, MT6885, MT6889, MT6893, MT8167, MT8168, MT8173, MT8185, MT8321, MT8362A, MT8365, MT8385, MT8666, MT8675, MT8695, MT8696, MT8765, MT8766, MT8768, MT8786, MT8788, MT8789, MT8791, MT8797
Published: 2022-05-03T20:06:47.000Z
CVE-2022-21744 
In Modem 2G RR, there is a possible out of bounds write due to a missing bounds check. This could lead to remote code execution when decoding GPRS Packet Neighbour Cell Data (PNCD) improper neighbouring cell size with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00810064; Issue ID: ALPS06641626.
Problem types: description: Remote Code Execution
Affected products: vendor: MediaTek, Inc.
product: MT2731, MT2735, MT6297, MT6725, MT6735, MT6737, MT6739, MT6750, MT6750S, MT6755, MT6757, MT6757P, MT6758, MT6761, MT6762, MT6762D, MT6762M, MT6763, MT6765, MT6765T, MT6767, MT6768, MT6769, MT6769T, MT6769Z, MT6771, MT6775, MT6779, MT6781, MT6783, MT6785, MT6785T, MT6789, MT6797, MT6799, MT6833, MT6853, MT6855, MT6873, MT6875, MT6877, MT6879, MT6880, MT6883, MT6885, MT6889, MT6890, MT6891, MT6893, MT6895, MT6983, MT8666, MT8667, MT8675, MT8735A, MT8735B, MT8765, MT8766, MT8768, MT8771, MT8781, MT8786, MT8788, MT8789, MT8791, MT8797
Published: 2022-07-06T13:05:13.000Z