Total
11736 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-34297 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-07-27 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The BMP_Loader.dll library in affected applications lacks proper validation of user-supplied data when parsing BMP files. This could result in an out of bounds write past the end of an allocated structure. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13059) | |||||
| CVE-2021-34319 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-07-27 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The BMP_loader.dll library in affected applications lacks proper validation of user-supplied data when parsing SGI files. This could result in an out of bounds write past the end of an allocated structure. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13404) | |||||
| CVE-2021-34314 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-07-27 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The BMP_loader.dll library in affected applications lacks proper validation of user-supplied data when parsing SGI files. This could result in an out of bounds write past the end of an allocated structure. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13355) | |||||
| CVE-2021-34316 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-07-27 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The DL180CoolType.dll library in affected applications lacks proper validation of user-supplied data when parsing PDF files. This could result in an out of bounds write past the end of an allocated structure. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13380) | |||||
| CVE-2020-36431 | 1 Unicorn-engine | 1 Unicorn Engine | 2021-07-27 | 2.1 LOW | 5.5 MEDIUM |
| Unicorn Engine 1.0.2 has an out-of-bounds write in helper_wfe_arm. | |||||
| CVE-2021-29566 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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. | |||||
| CVE-2021-29571 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 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/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. 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. | |||||
| CVE-2021-29558 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. 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. | |||||
| CVE-2021-29540 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the 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. | |||||
| CVE-2021-29537 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedResizeBilinear` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/50711818d2e61ccce012591eeb4fdf93a8496726/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L705-L706) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. 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. | |||||
| CVE-2021-29535 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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. | |||||
| CVE-2021-29536 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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. | |||||
| CVE-2021-29514 | 1 Google | 1 Tensorflow | 2021-07-26 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected. | |||||
| CVE-2019-8610 | 1 Apple | 6 Icloud, Iphone Os, Itunes and 3 more | 2021-07-21 | 6.8 MEDIUM | 8.8 HIGH |
| Multiple memory corruption issues were addressed with improved memory handling. This issue is fixed in iOS 12.3, macOS Mojave 10.14.5, tvOS 12.3, Safari 12.1.1, iTunes for Windows 12.9.5, iCloud for Windows 7.12. Processing maliciously crafted web content may lead to arbitrary code execution. | |||||
| CVE-2020-3621 | 1 Qualcomm | 126 Apq8009, Apq8009 Firmware, Apq8053 and 123 more | 2021-07-21 | 4.9 MEDIUM | 5.5 MEDIUM |
| u'Lack of check to ensure that the TX read index & RX write index that are read from shared memory are less than the FIFO size results into memory corruption and potential information leakage' in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking in APQ8009, APQ8017, APQ8053, APQ8096AU, APQ8098, Bitra, IPQ6018, IPQ8074, Kamorta, MDM9150, MDM9205, MDM9206, MDM9607, MDM9640, MDM9645, MDM9650, MDM9655, MSM8905, MSM8909, MSM8917, MSM8920, MSM8937, MSM8940, MSM8953, MSM8996, MSM8996AU, MSM8998, Nicobar, QCA8081, QCM2150, QCN7605, QCS404, QCS405, QCS605, QCS610, QM215, Rennell, SA415M, SA6155P, Saipan, SC7180, SC8180X, SDA660, SDA845, SDM429, SDM429W, SDM439, SDM450, SDM630, SDM632, SDM636, SDM660, SDM670, SDM710, SDM845, SDM850, SDX20, SDX24, SDX55, SM6150, SM7150, SM8150, SM8250, SXR1130, SXR2130 | |||||
| CVE-2020-0495 | 1 Google | 1 Android | 2021-07-21 | 2.1 LOW | 5.5 MEDIUM |
| In decode_Huffman of JBig2_SddProc.cpp, there is a possible out of bounds write due to an integer overflow. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-155473137 | |||||
| CVE-2019-12827 | 1 Digium | 2 Asterisk, Certified Asterisk | 2021-07-21 | 4.0 MEDIUM | 6.5 MEDIUM |
| Buffer overflow in res_pjsip_messaging in Digium Asterisk versions 13.21-cert3, 13.27.0, 15.7.2, 16.4.0 and earlier allows remote authenticated users to crash Asterisk by sending a specially crafted SIP MESSAGE message. | |||||
| CVE-2019-14080 | 1 Qualcomm | 80 Apq8053, Apq8053 Firmware, Apq8096au and 77 more | 2021-07-21 | 7.5 HIGH | 9.8 CRITICAL |
| Out of bound write can happen due to lack of check of array index value while parsing SDP attribute for SAR in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables in APQ8053, APQ8096AU, Kamorta, MDM9607, MDM9640, MDM9650, MSM8905, MSM8909, MSM8917, MSM8920, MSM8937, MSM8940, MSM8953, MSM8996AU, Nicobar, QCM2150, QCS605, QM215, Rennell, SA415M, SC7180, SC8180X, SDA660, SDA845, SDM429, SDM439, SDM450, SDM630, SDM632, SDM636, SDM660, SDM670, SDM710, SDM845, SDM850, SDX24, SM6150, SM7150, SM8150, SXR1130 | |||||
| CVE-2019-10056 | 1 Suricata-ids | 1 Suricata | 2021-07-21 | 5.0 MEDIUM | 7.5 HIGH |
| An issue was discovered in Suricata 4.1.3. The code mishandles the case of sending a network packet with the right type, such that the function DecodeEthernet in decode-ethernet.c is executed a second time. At this point, the algorithm cuts the first part of the packet and doesn't determine the current length. Specifically, if the packet is exactly 28 long, in the first iteration it subtracts 14 bytes. Then, it is working with a packet length of 14. At this point, the case distinction says it is a valid packet. After that it casts the packet, but this packet has no type, and the program crashes at the type case distinction. | |||||
| CVE-2019-8797 | 1 Apple | 5 Ipados, Iphone Os, Mac Os X and 2 more | 2021-07-21 | 9.3 HIGH | 7.8 HIGH |
| A memory corruption issue was addressed with improved memory handling. This issue is fixed in iOS 13.2 and iPadOS 13.2, macOS Catalina 10.15.1, tvOS 13.2, watchOS 6.1. An application may be able to execute arbitrary code with system privileges. | |||||