In apusys, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07571104; Issue ID: ALPS07571104.
In keyinstall, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07589148; Issue ID: ALPS07589148.
Out of bounds read in Tab Strip in Google Chrome prior to 92.0.4515.131 allowed an attacker who convinced a user to install a malicious extension to perform an out of bounds memory read via a crafted HTML page.
Out of bounds read in Tab Groups in Google Chrome prior to 90.0.4430.212 allowed an attacker who convinced a user to install a malicious extension to perform an out of bounds memory read via a crafted HTML page.
Out of bounds memory access in V8 in Google Chrome prior to 123.0.6312.105 allowed a remote attacker to perform arbitrary read/write via a crafted HTML page. (Chromium security severity: High)
TensorFlow is an end-to-end open source platform for machine learning. The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. 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.
Inappropriate implementation in V8 in Google Chrome prior to 123.0.6312.105 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page. (Chromium security severity: High)
TensorFlow is an end-to-end open source platform for machine learning. An attacker can access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. 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.
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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.
In imgsys, there is a possible out of bounds read due to a race condition. This could lead to local information disclosure with System execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS07326455; Issue ID: ALPS07326418.
TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. 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.
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixTriangularSolve`(https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails. 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.
The CSSParser::parseFontFaceSrc function in WebCore/css/CSSParser.cpp in WebKit, as used in Google Chrome before 8.0.552.224, Chrome OS before 8.0.552.343, webkitgtk before 1.2.6, and other products does not properly parse Cascading Style Sheets (CSS) token sequences, which allows remote attackers to cause a denial of service (out-of-bounds read) via a crafted local font, related to "Type Confusion."
TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. 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.
Out of bounds read in GPU Video in Google Chrome prior to 111.0.5563.110 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)
Out of bounds read in ANGLE in Google Chrome prior to 111.0.5563.110 allowed a remote attacker who had compromised the renderer process to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. 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.
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. 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.
TensorFlow is an end-to-end open source platform for machine learning. An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument. 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.
In tmu_get_temp_lut of tmu.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In km_exp_did_inner of kmv.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In ss_AnalyzeOssReturnResUssdArgIe of ss_OssAsnManagement.c, there is a possible out of bounds read due to improper input validation. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In ProtocolPsDedicatedBearInfoAdapter::processQosSession of protocolpsadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with baseband firmware compromise required. User interaction is not needed for exploitation.
Out of bounds read in WebRTC in Google Chrome prior to 110.0.5481.77 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: High)
Out of bounds read in V8 in Google Chrome prior to 121.0.6167.139 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page. (Chromium security severity: Medium)
In EUTRAN_LCS_DecodeFacilityInformationElement of LPP_LcsManagement.c, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure after authenticating the cell connection with no additional execution privileges needed. User interaction is not needed for exploitation.
In sendHciCommand of bluetooth_hci.cc, there is a possible out of bounds read due to a heap buffer overflow. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation.
Out of bounds read in Swiftshader in Google Chrome prior to 123.0.6312.58 allowed a remote attacker to perform out of bounds memory access via a crafted HTML page. (Chromium security severity: Medium)
In update_freq_data of , there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In plugin_extern_func of , there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In lpm_req_handler of , there is a possible out of bounds memory access due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.
In SAEMM_DiscloseGuti of SAEMM_RadioMessageCodec.c, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In tmu_tz_control of tmu.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.
Out of bounds memory access in V8 in Google Chrome prior to 116.0.5845.110 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: High)
In acpm_tmu_ipc_handler of tmu_plugin.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
Out of bounds memory access in Fonts in Google Chrome prior to 116.0.5845.110 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: Medium)
In _s5e9865_mif_set_rate of exynos_dvfs.c, there is a possible out of bounds read due to improper casting. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In gpu_slc_liveness_update of pixel_gpu_slc.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In MP3 encoder, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with System execution privileges needed.
In ProtocolCdmaCallWaitingIndAdapter::GetCwInfo() of protocolsmsadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure with baseband firmware compromise required. User interaction is not needed for exploitation.
In wlan driver, there is a possible missing params check. This could lead to local denial of service in wlan services.
In camera driver, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with System execution privileges needed
In camera driver, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with System execution privileges needed
In wlan driver, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service in wlan services.
Due to length check, an attacker with privilege access on a Linux Nonsecure operating system can trigger a vulnerability and leak the secure memory from the Trusted Application
In camera driver, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with System execution privileges needed
In wlan driver, there is a possible missing params check. This could lead to local denial of service in wlan services.
In constraint_check of fvp.c, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.
In isp, there is a possible out of bounds read due to a missing bounds check. This could lead to local denial of service with System execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS09071481; Issue ID: MSV-1730.
In m4u, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08996900; Issue ID: MSV-1635.