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Total
49350 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-20393 | 1 Ibm | 1 Qradar User Behavior Analytics | 2021-05-20 | 5.0 MEDIUM | 7.5 HIGH |
| IBM QRadar User Behavior Analytics 1.0.0 through 4.1.0 could allow a remote attacker to obtain sensitive information when a detailed technical error message is returned in the browser. This information could be used in further attacks against the system. IBM X-Force ID: 196001. | |||||
| CVE-2021-31466 | 2 Foxitsoftware, Microsoft | 2 3d, Windows | 2021-05-20 | 6.8 MEDIUM | 7.8 HIGH |
| This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Reader 10.1.3.37598. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of U3D objects in PDF files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated data structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13583. | |||||
| CVE-2020-22809 | 1 Windscribe | 1 Windscribe | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| In Windscribe v1.83 Build 20, 'WindscribeService' has an Unquoted Service Path that facilitates privilege escalation. | |||||
| CVE-2021-32819 | 1 Squirrelly | 1 Squirrelly | 2021-05-20 | 6.8 MEDIUM | 8.8 HIGH |
| Squirrelly is a template engine implemented in JavaScript that works out of the box with ExpressJS. Squirrelly mixes pure template data with engine configuration options through the Express render API. By overwriting internal configuration options remote code execution may be triggered in downstream applications. There is currently no fix for these issues as of the publication of this CVE. The latest version of squirrelly is currently 8.0.8. For complete details refer to the referenced GHSL-2021-023. | |||||
| CVE-2021-29609 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| 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_add_op.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-2021-29515 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not validate that the tensor arguments are non-empty. 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-2021-29529 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer 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-2021-29601 | 1 Google | 1 Tensorflow | 2021-05-20 | 3.6 LOW | 7.1 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. 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-2021-29518 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior. 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-2021-29530 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. 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-2021-29578 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor 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. | |||||
| CVE-2021-29579 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. 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-2021-29582 | 1 Google | 1 Tensorflow | 2021-05-20 | 3.6 LOW | 7.1 HIGH |
| 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. | |||||
| CVE-2021-29577 | 1 Google | 1 Tensorflow | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. 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-2021-29569 | 1 Google | 1 Tensorflow | 2021-05-20 | 3.6 LOW | 7.1 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/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. | |||||
| CVE-2021-23891 | 1 Mcafee | 1 Total Protection | 2021-05-20 | 4.6 MEDIUM | 7.8 HIGH |
| Privilege Escalation vulnerability in McAfee Total Protection (MTP) prior to 16.0.32 allows a local user to gain elevated privileges by impersonating a client token which could lead to the bypassing of MTP self-defense. | |||||
| CVE-2021-23892 | 1 Mcafee | 1 Endpoint Security For Linux Threat Prevention | 2021-05-20 | 6.9 MEDIUM | 7.0 HIGH |
| By exploiting a time of check to time of use (TOCTOU) race condition during the Endpoint Security for Linux Threat Prevention and Firewall (ENSL TP/FW) installation process, a local user can perform a privilege escalation attack to obtain administrator privileges for the purpose of executing arbitrary code through insecure use of predictable temporary file locations. | |||||
| CVE-2021-30482 | 1 Jetbrains | 1 Upsource | 2021-05-20 | 5.0 MEDIUM | 7.5 HIGH |
| In JetBrains UpSource before 2020.1.1883, application passwords were not revoked correctly | |||||
| CVE-2021-29600 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `OneHot` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72). An attacker can craft a model such that at least one of the dimensions of `indices` would be 0. In turn, the `prefix_dim_size` value would become 0. 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-2021-20222 | 1 Redhat | 1 Keycloak | 2021-05-19 | 5.1 MEDIUM | 7.5 HIGH |
| A flaw was found in keycloak. The new account console in keycloak can allow malicious code to be executed using the referrer URL. The highest threat from this vulnerability is to data confidentiality and integrity as well as system availability. | |||||
| CVE-2021-29512 | 1 Google | 1 Tensorflow | 2021-05-19 | 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-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. 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-2021-27396 | 1 Siemens | 1 Tecnomatix Plant Simulation | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in Tecnomatix Plant Simulation (All versions < V16.0.5). The PlantSimCore.dll library lacks proper validation of user-supplied data when parsing SPP files. This could result in a stack based buffer overflow, a different vulnerability than CVE-2021-27398. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13279) | |||||
| CVE-2021-27398 | 1 Siemens | 1 Tecnomatix Plant Simulation | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in Tecnomatix Plant Simulation (All versions < V16.0.5). The PlantSimCore.dll library lacks proper validation of user-supplied data when parsing SPP files. This could result in a stack based buffer overflow, a different vulnerability than CVE-2021-27396. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13290) | |||||
| CVE-2021-32611 | 1 Antisip | 1 Exosip2 | 2021-05-19 | 5.0 MEDIUM | 7.5 HIGH |
| A NULL pointer dereference vulnerability exists in eXcall_api.c in Antisip eXosip2 through 5.2.0 when handling certain 3xx redirect responses. | |||||
| CVE-2016-8379 | 1 Moxa | 19 Iologik E1200 Series Firmware, Iologik E1210, Iologik E1211 and 16 more | 2021-05-19 | 4.3 MEDIUM | 8.1 HIGH |
| An issue was discovered in Moxa ioLogik E1210, firmware Version V2.4 and prior, ioLogik E1211, firmware Version V2.3 and prior, ioLogik E1212, firmware Version V2.4 and prior, ioLogik E1213, firmware Version V2.5 and prior, ioLogik E1214, firmware Version V2.4 and prior, ioLogik E1240, firmware Version V2.3 and prior, ioLogik E1241, firmware Version V2.4 and prior, ioLogik E1242, firmware Version V2.4 and prior, ioLogik E1260, firmware Version V2.4 and prior, ioLogik E1262, firmware Version V2.4 and prior, ioLogik E2210, firmware versions prior to V3.13, ioLogik E2212, firmware versions prior to V3.14, ioLogik E2214, firmware versions prior to V3.12, ioLogik E2240, firmware versions prior to V3.12, ioLogik E2242, firmware versions prior to V3.12, ioLogik E2260, firmware versions prior to V3.13, and ioLogik E2262, firmware versions prior to V3.12. Users are restricted to using short passwords. | |||||
| CVE-2016-8372 | 1 Moxa | 19 Iologik E1200 Series Firmware, Iologik E1210, Iologik E1211 and 16 more | 2021-05-19 | 4.3 MEDIUM | 8.1 HIGH |
| An issue was discovered in Moxa ioLogik E1210, firmware Version V2.4 and prior, ioLogik E1211, firmware Version V2.3 and prior, ioLogik E1212, firmware Version V2.4 and prior, ioLogik E1213, firmware Version V2.5 and prior, ioLogik E1214, firmware Version V2.4 and prior, ioLogik E1240, firmware Version V2.3 and prior, ioLogik E1241, firmware Version V2.4 and prior, ioLogik E1242, firmware Version V2.4 and prior, ioLogik E1260, firmware Version V2.4 and prior, ioLogik E1262, firmware Version V2.4 and prior, ioLogik E2210, firmware versions prior to V3.13, ioLogik E2212, firmware versions prior to V3.14, ioLogik E2214, firmware versions prior to V3.12, ioLogik E2240, firmware versions prior to V3.12, ioLogik E2242, firmware versions prior to V3.12, ioLogik E2260, firmware versions prior to V3.13, and ioLogik E2262, firmware versions prior to V3.12. A password is transmitted in a format that is not sufficiently secure. | |||||
| CVE-2021-29499 | 1 Sylabs | 1 Singularity Image Format | 2021-05-19 | 4.0 MEDIUM | 7.5 HIGH |
| SIF is an open source implementation of the Singularity Container Image Format. The `siftool new` command and func siftool.New() produce predictable UUID identifiers due to insecure randomness in the version of the `github.com/satori/go.uuid` module used as a dependency. A patch is available in version >= v1.2.3 of the module. Users are encouraged to upgrade. As a workaround, users passing CreateInfo struct should ensure the `ID` field is generated using a version of `github.com/satori/go.uuid` that is not vulnerable to this issue. | |||||
| CVE-2021-32471 | 1 Mit | 1 Universal Turing Machine | 2021-05-19 | 7.2 HIGH | 7.8 HIGH |
| Insufficient input validation in the Marvin Minsky 1967 implementation of the Universal Turing Machine allows program users to execute arbitrary code via crafted data. For example, a tape head may have an unexpected location after the processing of input composed of As and Bs (instead of 0s and 1s). NOTE: the discoverer states "this vulnerability has no real-world implications." | |||||
| CVE-2021-31520 | 1 Trendmicro | 1 Im Security | 2021-05-19 | 6.8 MEDIUM | 8.1 HIGH |
| A weak session token authentication bypass vulnerability in Trend Micro IM Security 1.6 and 1.6.5 could allow an remote attacker to guess currently logged-in administrators' session session token in order to gain access to the product's web management interface. | |||||
| CVE-2021-23010 | 1 F5 | 1 Big-ip Application Security Manager | 2021-05-19 | 5.0 MEDIUM | 7.5 HIGH |
| On versions 16.0.x before 16.0.1.1, 15.1.x before 15.1.2, 14.1.x before 14.1.3.1, 13.1.x before 13.1.3.5, and 12.1.x before 12.1.5.3, when the BIG-IP ASM/Advanced WAF system processes WebSocket requests with JSON payloads using the default JSON Content Profile in the ASM Security Policy, the BIG-IP ASM bd process may produce a core file. Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated. | |||||
| CVE-2021-31470 | 2 Foxitsoftware, Microsoft | 2 3d, Windows | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Reader 10.1.1.37576. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of U3D objects in PDF files. The issue results from the lack of validating the existence of an object prior to performing operations on the object. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-12947. | |||||
| CVE-2021-31465 | 2 Foxitsoftware, Microsoft | 2 3d, Windows | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Reader 10.1.3.37598. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of U3D objects in PDF files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated data structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13582. | |||||
| CVE-2021-32096 | 1 Nsa | 1 Emissary | 2021-05-19 | 6.8 MEDIUM | 8.8 HIGH |
| The ConsoleAction component of U.S. National Security Agency (NSA) Emissary 5.9.0 allows a CSRF attack that results in injecting arbitrary Ruby code (for an eval call) via the CONSOLE_COMMAND_STRING parameter. | |||||
| CVE-2021-29586 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling `ComputePaddingHeightWidth`(https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90). Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero. 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-2021-31468 | 2 Foxitsoftware, Microsoft | 2 3d, Windows | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Reader 10.1.3.37598. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of U3D files embedded in PDF documents. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated data structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13620. | |||||
| CVE-2021-29525 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) does a division by a quantity that is controlled by the caller. 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-2021-29597 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SpaceToBatchNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. 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-2020-0504 | 1 Intel | 1 Graphics Driver | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| Buffer overflow in Intel(R) Graphics Drivers before versions 15.40.44.5107, 15.45.30.5103, and 26.20.100.7158 may allow an authenticated user to potentially enable escalation of privilege and denial of service via local access. | |||||
| CVE-2021-29598 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SVDF` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/7f283ff806b2031f407db64c4d3edcda8fb9f9f5/tensorflow/lite/kernels/svdf.cc#L99-L102). An attacker can craft a model such that `params->rank` would be 0. 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-2020-0508 | 1 Intel | 1 Graphics Driver | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| Incorrect default permissions in the installer for Intel(R) Graphics Drivers before versions 15.33.49.5100, 15.36.38.5117, 15.40.44.5107, 15.45.30.5103, and 26.20.100.7212 may allow an authenticated user to potentially enable escalation of privilege via local access. | |||||
| CVE-2019-19023 | 2 Linuxfoundation, Pivotal | 2 Harbor, Vmware Harbor Registry | 2021-05-19 | 6.5 MEDIUM | 8.8 HIGH |
| Cloud Native Computing Foundation Harbor prior to 1.8.6 and 1.9.3 has a Privilege Escalation Vulnerability in the VMware Harbor Container Registry for the Pivotal Platform. | |||||
| CVE-2020-0515 | 1 Intel | 1 Graphics Driver | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| Uncontrolled search path element in the installer for Intel(R) Graphics Drivers before versions 26.20.100.7584, 15.45.30.5103, 15.40.44.5107, 15.36.38.5117, and 15.33.49.5100 may allow an authenticated user to potentially enable escalation of privilege via local access | |||||
| CVE-2019-19025 | 2 Linuxfoundation, Pivotal | 2 Harbor, Vmware Harbor Registry | 2021-05-19 | 6.8 MEDIUM | 8.8 HIGH |
| Cloud Native Computing Foundation Harbor prior to 1.8.6 and 1.9.3 allows CSRF in the VMware Harbor Container Registry for the Pivotal Platform. | |||||
| CVE-2021-29594 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. TFLite's convolution code(https://github.com/tensorflow/tensorflow/blob/09c73bca7d648e961dd05898292d91a8322a9d45/tensorflow/lite/kernels/conv.cc) has multiple division where the divisor is controlled by the user and not checked to be non-zero. 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-2021-29593 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `BatchToSpaceNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/b5ed552fe55895aee8bd8b191f744a069957d18d/tensorflow/lite/kernels/batch_to_space_nd.cc#L81-L82). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. 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-2021-29592 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D 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. | |||||
| CVE-2021-29596 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `EmbeddingLookup` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e4b29809543b250bc9b19678ec4776299dd569ba/tensorflow/lite/kernels/embedding_lookup.cc#L73-L74). An attacker can craft a model such that the first dimension of the `value` input is 0. 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-2020-28383 | 1 Siemens | 3 Jt2go, Solid Edge, Teamcenter Visualization | 2021-05-19 | 6.8 MEDIUM | 7.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.1.0.1), Solid Edge SE2020 (All Versions < SE2020MP12), Solid Edge SE2021 (All Versions < SE2021MP2), Teamcenter Visualization (All versions < V13.1.0.1). Affected applications lack proper validation of user-supplied data when parsing PAR files. This can result in an out of bounds write past the memory location that is a read only image address. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-11885) | |||||
| CVE-2020-26991 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-05-19 | 6.8 MEDIUM | 8.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.1.0.2), Teamcenter Visualization (All versions < V13.1.0.2). Affected applications lack proper validation of user-supplied data when parsing ASM files. This could lead to pointer dereferences of a value obtained from untrusted source. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-11899) | |||||
| CVE-2020-26990 | 1 Siemens | 2 Jt2go, Teamcenter Visualization | 2021-05-19 | 6.8 MEDIUM | 8.8 HIGH |
| A vulnerability has been identified in JT2Go (All versions < V13.1.0.1), Teamcenter Visualization (All versions < V13.1.0.1). Affected applications lack proper validation of user-supplied data when parsing ASM files. A crafted ASM file could trigger a type confusion condition. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-11897) | |||||