Total
9170 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-0419 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336713. | |||||
| CVE-2021-0418 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336706. | |||||
| CVE-2021-0417 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336702. | |||||
| CVE-2021-0416 | 1 Google | 1 Android | 2021-08-24 | 4.9 MEDIUM | 5.5 MEDIUM |
| In memory management driver, there is a possible system crash due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS05403499; Issue ID: ALPS05336700. | |||||
| CVE-2021-36982 | 1 Monitorapp | 2 Application Insight Manager, Application Insight Web Application Firewall | 2021-08-24 | 9.3 HIGH | 8.1 HIGH |
| AIMANAGER before B115 on MONITORAPP Application Insight Web Application Firewall (AIWAF) devices with Manager 2.1.0 allows OS Command Injection because of missing input validation on one of the parameters of an HTTP request. | |||||
| CVE-2021-20775 | 1 Cybozu | 1 Garoon | 2021-08-24 | 4.0 MEDIUM | 4.3 MEDIUM |
| Improper input validation vulnerability in Bulletin of Cybozu Garoon 4.10.0 to 5.5.0 allows a remote authenticated attacker to obtain the data of Comment and Space without the viewing privilege. | |||||
| CVE-2021-20764 | 1 Cybozu | 1 Garoon | 2021-08-24 | 5.0 MEDIUM | 5.3 MEDIUM |
| Improper input validation vulnerability in Attaching Files of Cybozu Garoon 4.0.0 to 5.0.2 allows a remote attacker to alter the data of Attaching Files. | |||||
| CVE-2021-20762 | 1 Cybozu | 1 Garoon | 2021-08-24 | 4.0 MEDIUM | 4.3 MEDIUM |
| Improper input validation vulnerability in E-mail of Cybozu Garoon 4.0.0 to 5.0.2 allows a remote authenticated to alter the data of E-mail without the appropriate privilege. | |||||
| CVE-2021-20761 | 1 Cybozu | 1 Garoon | 2021-08-24 | 3.5 LOW | 2.7 LOW |
| Improper input validation vulnerability in E-mail of Cybozu Garoon 4.0.0 to 5.0.2 allows a remote attacker with an administrative privilege to alter the data of E-mail without the appropriate privilege. | |||||
| CVE-2021-20760 | 1 Cybozu | 1 Garoon | 2021-08-24 | 4.0 MEDIUM | 4.3 MEDIUM |
| Improper input validation vulnerability in User Profile of Cybozu Garoon 4.0.0 to 5.0.2 allows a remote authenticated attacker to alter the data of User Profile without the appropriate privilege. | |||||
| CVE-2021-20754 | 1 Cybozu | 1 Garoon | 2021-08-24 | 4.0 MEDIUM | 4.3 MEDIUM |
| Improper input validation vulnerability in Workflow of Cybozu Garoon 4.0.0 to 5.0.2 allows a remote authenticated attacker to alter the data of Workflow without the appropriate privilege. | |||||
| CVE-2021-33199 | 1 Expressionengine | 1 Expressionengine | 2021-08-23 | 7.5 HIGH | 9.8 CRITICAL |
| In Expression Engine before 6.0.3, addonIcon in Addons/file/mod.file.php relies on the untrusted input value of input->get('file') instead of the fixed file names of icon.png and icon.svg. | |||||
| CVE-2021-0083 | 1 Intel | 192 Optane Persistent Memory Firmware, Xeon Bronze 3204, Xeon Bronze 3206r and 189 more | 2021-08-20 | 2.1 LOW | 4.4 MEDIUM |
| Improper input validation in some Intel(R) Optane(TM) PMem versions before versions 1.2.0.5446 or 2.2.0.1547 may allow a privileged user to potentially enable denial of service via local access. | |||||
| CVE-2021-3048 | 1 Paloaltonetworks | 1 Pan-os | 2021-08-19 | 4.3 MEDIUM | 5.9 MEDIUM |
| Certain invalid URL entries contained in an External Dynamic List (EDL) cause the Device Server daemon (devsrvr) to stop responding. This condition causes subsequent commits on the firewall to fail and prevents administrators from performing commits and configuration changes even though the firewall remains otherwise functional. If the firewall then restarts, it results in a denial-of-service (DoS) condition and the firewall stops processing traffic. This issue impacts: PAN-OS 9.0 versions earlier than PAN-OS 9.0.14; PAN-OS 9.1 versions earlier than PAN-OS 9.1.9; PAN-OS 10.0 versions earlier than PAN-OS 10.0.5. PAN-OS 8.1 and PAN-OS 10.1 versions are not impacted. | |||||
| CVE-2021-0062 | 2 Intel, Microsoft | 2 Graphics Drivers, Windows | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| Improper input validation in some Intel(R) Graphics Drivers before version 27.20.100.8935 may allow an authenticated user to potentially enable escalation of privilege via local access. | |||||
| CVE-2021-37665 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37663 | 1 Google | 1 Tensorflow | 2021-08-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37677 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37674 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||
| CVE-2021-37673 | 1 Google | 1 Tensorflow | 2021-08-19 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | |||||