Filtered by CWE-754
Total 445 CVE
CVE Vendors Products Updated CVSS v3.1
CVE-2021-31364 1 Juniper 14 Junos, Srx1500, Srx300 and 11 more 2024-11-21 5.9 Medium
An Improper Check for Unusual or Exceptional Conditions vulnerability combined with a Race Condition in the flow daemon (flowd) of Juniper Networks Junos OS on SRX300 Series, SRX500 Series, SRX1500, and SRX5000 Series with SPC2 allows an unauthenticated network based attacker sending specific traffic to cause a crash of the flowd/srxpfe process, responsible for traffic forwarding in SRX, which will cause a Denial of Service (DoS). Continued receipt and processing of this specific traffic will create a sustained Denial of Service (DoS) condition. This issue can only occur when specific packets are trying to create the same session and logging for session-close is configured as a policy action. Affected platforms are: SRX300 Series, SRX500 Series, SRX1500, and SRX5000 Series with SPC2. Not affected platforms are: SRX4000 Series, SRX5000 Series with SPC3, and vSRX Series. This issue affects Juniper Networks Junos OS SRX300 Series, SRX500 Series, SRX1500, and SRX5000 Series with SPC2: All versions prior to 17.4R3-S5; 18.3 versions prior to 18.3R3-S5; 18.4 versions prior to 18.4R3-S9; 19.1 versions prior to 19.1R3-S6; 19.2 versions prior to 19.2R1-S7, 19.2R3-S2; 19.3 versions prior to 19.3R2-S6, 19.3R3-S2; 19.4 versions prior to 19.4R1-S4, 19.4R3-S3; 20.1 versions prior to 20.1R2-S2, 20.1R3; 20.2 versions prior to 20.2R3; 20.3 versions prior to 20.3R2-S1, 20.3R3; 20.4 versions prior to 20.4R2.
CVE-2021-31361 1 Juniper 44 Junos, Ptx1000, Ptx1000-72q and 41 more 2024-11-21 5.3 Medium
An Improper Check for Unusual or Exceptional Conditions vulnerability combined with Improper Handling of Exceptional Conditions in Juniper Networks Junos OS on QFX Series and PTX Series allows an unauthenticated network based attacker to cause increased FPC CPU utilization by sending specific IP packets which are being VXLAN encapsulated leading to a partial Denial of Service (DoS). Continued receipted of these specific traffic will create a sustained Denial of Service (DoS) condition. This issue affects: Juniper Networks Junos OS on QFX Series: All versions prior to 17.3R3-S11; 17.4 versions prior to 17.4R2-S13, 17.4R3-S4; 18.1 versions prior to 18.1R3-S12; 18.2 versions prior to 18.2R2-S8, 18.2R3-S7; 18.3 versions prior to 18.3R3-S4; 18.4 versions prior to 18.4R1-S8, 18.4R2-S7, 18.4R3-S7; 19.1 versions prior to 19.1R1-S6, 19.1R2-S2, 19.1R3-S4; 19.2 versions prior to 19.2R1-S6, 19.2R3-S2; 19.3 versions prior to 19.3R3-S1; 19.4 versions prior to 19.4R2-S3, 19.4R3-S1; 20.1 versions prior to 20.1R2, 20.1R3; 20.2 versions prior to 20.2R2, 20.2R3; 20.3 versions prior to 20.3R1-S1, 20.3R2. Juniper Networks Junos OS on PTX Series: All versions prior to 18.4R3-S9; 19.1 versions prior to 19.1R3-S6; 19.2 versions prior to 19.2R1-S7, 19.2R3-S3; 19.3 versions prior to 19.3R2-S6, 19.3R3-S3; 19.4 versions prior to 19.4R1-S4, 19.4R3-S5; 20.1 versions prior to 20.1R2-S2, 20.1R3; 20.2 versions prior to 20.2R3-S1; 20.3 versions prior to 20.3R2-S1, 20.3R3; 20.4 versions prior to 20.4R2-S1, 20.4R3; 21.1 versions prior to 21.1R1-S1, 21.1R2.
CVE-2021-31351 1 Juniper 18 Junos, Mx10, Mx10000 and 15 more 2024-11-21 7.5 High
An Improper Check for Unusual or Exceptional Conditions in packet processing on the MS-MPC/MS-MIC utilized by Juniper Networks Junos OS allows a malicious attacker to send a specific packet, triggering the MS-MPC/MS-MIC to reset, causing a Denial of Service (DoS). Continued receipt and processing of this packet will create a sustained Denial of Service (DoS) condition. This issue only affects specific versions of Juniper Networks Junos OS on MX Series: 17.3R3-S11; 17.4R2-S13; 17.4R3 prior to 17.4R3-S5; 18.1R3-S12; 18.2R2-S8, 18.2R3-S7, 18.2R3-S8; 18.3R3-S4; 18.4R3-S7; 19.1R3-S4, 19.1R3-S5; 19.2R1-S6; 19.3R3-S2; 19.4R2-S4, 19.4R2-S5; 19.4R3-S2; 20.1R2-S1; 20.2R2-S2, 20.2R2-S3, 20.2R3; 20.3R2, 20.3R2-S1; 20.4R1, 20.4R1-S1, 20.4R2; 21.1R1; This issue does not affect any version of Juniper Networks Junos OS prior to 15.1X49-D240;
CVE-2021-29607 1 Google 1 Tensorflow 2024-11-21 5.3 Medium
TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. 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-2021-29544 1 Google 1 Tensorflow 2024-11-21 2.5 Low
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.
CVE-2021-29534 1 Google 1 Tensorflow 2024-11-21 2.5 Low
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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-2021-29533 1 Google 1 Tensorflow 2024-11-21 2.5 Low
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. 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-2021-29531 1 Google 1 Tensorflow 2024-11-21 2.5 Low
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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-2021-27568 3 Json-smart Project, Oracle, Redhat 11 Json-smart-v1, Json-smart-v2, Communications Cloud Native Core Policy and 8 more 2024-11-21 5.9 Medium
An issue was discovered in netplex json-smart-v1 through 2015-10-23 and json-smart-v2 through 2.4. An exception is thrown from a function, but it is not caught, as demonstrated by NumberFormatException. When it is not caught, it may cause programs using the library to crash or expose sensitive information.
CVE-2021-26197 1 Jerryscript 1 Jerryscript 2024-11-21 6.5 Medium
An issue was discovered in JerryScript 2.4.0. There is a SEGV in main_print_unhandled_exception in main-utils.c file.
CVE-2021-26038 1 Joomla 1 Joomla\! 2024-11-21 7.5 High
An issue was discovered in Joomla! 2.5.0 through 3.9.27. Install action in com_installer lack the required hardcoded ACL checks for superusers. A default system is not affected cause the default ACL for com_installer is limited to super users already.
CVE-2021-25525 1 Samsung 1 Pay 2024-11-21 2 Low
Improper check or handling of exception conditions vulnerability in Samsung Pay (US only) prior to version 4.0.65 allows attacker to use NFC without user recognition.
CVE-2021-25481 2 Google, Samsung 2 Android, Exynos 2024-11-21 6.4 Medium
An improper error handling in Exynos CP booting driver prior to SMR Oct-2021 Release 1 allows local attackers to bypass a Secure Memory Protector of Exynos CP Memory.
CVE-2021-25425 1 Samsung 1 Health 2024-11-21 5.3 Medium
Improper check vulnerability in Samsung Health prior to version 6.17 allows attacker to read internal cache data via exported component.
CVE-2021-23372 1 Mongo-express Project 1 Mongo-express 2024-11-21 4.4 Medium
All versions of package mongo-express are vulnerable to Denial of Service (DoS) when exporting an empty collection as CSV, due to an unhandled exception, leading to a crash.
CVE-2021-22816 1 Schneider-electric 18 Scadapack 312e, Scadapack 312e Firmware, Scadapack 313e and 15 more 2024-11-21 7.5 High
A CWE-754: Improper Check for Unusual or Exceptional Conditions vulnerability exists that could cause a Denial of Service of the RTU when receiving a specially crafted request over Modbus, and the RTU is configured as a Modbus server. Affected Products: SCADAPack 312E, 313E, 314E, 330E, 333E, 334E, 337E, 350E and 357E RTUs with firmware V8.18.1 and prior
CVE-2021-22747 1 Schneider-electric 4 Tcm 4351b, Tcm 4351b Firmware, Triconex Model 3009 Mp and 1 more 2024-11-21 3.9 Low
Improper Check for Unusual or Exceptional Conditions vulnerability exists in Triconex Model 3009 MP installed on Tricon V11.3.x systems that could cause module reset when TCM receives malformed TriStation packets while the write-protect keyswitch is in the program position. This CVE ID is unique from CVE-2021-22742, CVE-2021-22744, CVE-2021-22745, and CVE-2021-22746.
CVE-2021-22746 1 Schneider-electric 4 Tcm 4351b, Tcm 4351b Firmware, Triconex Model 3009 Mp and 1 more 2024-11-21 3.9 Low
Improper Check for Unusual or Exceptional Conditions vulnerability exists in Triconex Model 3009 MP installed on Tricon V11.3.x systems that could cause module reset when TCM receives malformed TriStation packets while the write-protect keyswitch is in the program position. This CVE ID is unique from CVE-2021-22742, CVE-2021-22744, CVE-2021-22745, and CVE-2021-22747.
CVE-2021-22745 1 Schneider-electric 4 Tcm 4351b, Tcm 4351b Firmware, Triconex Model 3009 Mp and 1 more 2024-11-21 3.9 Low
Improper Check for Unusual or Exceptional Conditions vulnerability exists in Triconex Model 3009 MP installed on Tricon V11.3.x systems that could cause module reset when TCM receives malformed TriStation packets while the write-protect keyswitch is in the program position. This CVE ID is unique from CVE-2021-22742, CVE-2021-22744, CVE-2021-22746, and CVE-2021-22747.
CVE-2021-22744 1 Schneider-electric 4 Tcm 4351b, Tcm 4351b Firmware, Triconex Model 3009 Mp and 1 more 2024-11-21 3.9 Low
Improper Check for Unusual or Exceptional Conditions vulnerability exists in Triconex Model 3009 MP installed on Tricon V11.3.x systems that could cause module reset when TCM receives malformed TriStation packets while the write-protect keyswitch is in the program position. This CVE ID is unique from CVE-2021-22742, CVE-2021-22745, CVE-2021-22746, and CVE-2021-22747.