| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SplitV` can trigger a segfault is an attacker supplies negative arguments. This occurs whenever `size_splits` contains more than one value and at least one value is negative. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. |
| Vyper is a Pythonic Smart Contract Language for the EVM. In affected versions external functions did not properly validate the bounds of decimal arguments. The can lead to logic errors. This issue has been resolved in version 0.3.0. |
| Redis is an open source, in-memory database that persists on disk. An integer overflow bug in the underlying string library can be used to corrupt the heap and potentially result with denial of service or remote code execution. The vulnerability involves changing the default proto-max-bulk-len configuration parameter to a very large value and constructing specially crafted network payloads or commands. The problem is fixed in Redis versions 6.2.6, 6.0.16 and 5.0.14. An additional workaround to mitigate the problem without patching the redis-server executable is to prevent users from modifying the proto-max-bulk-len configuration parameter. This can be done using ACL to restrict unprivileged users from using the CONFIG SET command. |
| When parsing a file that is submitted to the DPDecoder service as a job, the service will use the combination of decoding parameters that were submitted with the job along with fields that were parsed for the submitted video by the R3D SDK to calculate the size of a heap buffer. Due to an integer overflow with regards to this calculation, this can result in an undersized heap buffer being allocated. When this heap buffer is written to, a heap-based buffer overflow will occur. This can result in code execution under the context of the application. |
| The bpf verifier in the Linux kernel did not properly handle mod32 destination register truncation when the source register was known to be 0. A local attacker with the ability to load bpf programs could use this gain out-of-bounds reads in kernel memory leading to information disclosure (kernel memory), and possibly out-of-bounds writes that could potentially lead to code execution. This issue was addressed in the upstream kernel in commit 9b00f1b78809 ("bpf: Fix truncation handling for mod32 dst reg wrt zero") and in Linux stable kernels 5.11.2, 5.10.19, and 5.4.101. |
| Integer Underflow in Zephyr in IEEE 802154 Fragment Reassembly Header Removal. Zephyr versions >= >=2.4.0 contain Integer Overflow to Buffer Overflow (CWE-680). For more information, see https://github.com/zephyrproject-rtos/zephyr/security/advisories/GHSA-w44j-66g7-xw99 |
| In Go before 1.14.14 and 1.15.x before 1.15.7, crypto/elliptic/p224.go can generate incorrect outputs, related to an underflow of the lowest limb during the final complete reduction in the P-224 field. |
| The _deposit function in the smart contract implementation for Stable Yield Credit (yCREDIT), an Ethereum token, has certain incorrect calculations. An attacker can obtain more yCREDIT tokens than they should. |
| An issue was discovered in the anymap crate through 0.12.1 for Rust. It violates soundness via conversion of a *u8 to a *u64. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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. |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. |
| An issue was discovered in OpenPOWER 2.6 firmware. unpack_timestamp() calls le32_to_cpu() for endian conversion of a uint16_t "year" value, resulting in a type mismatch that can truncate a higher integer value to a smaller one, and bypass a timestamp check. The fix is to use the right endian conversion function. |
| In Enbra EWM in Version 1.7.29 together with several tested wireless M-Bus Sensors the events backflow and "no flow" are not reconized or misinterpreted. This may lead to wrong values and missing events. |
| A vulnerability has been identified in JT Utilities (All versions < V13.0.2.0). When parsing specially crafted JT files, a hash function is called with an incorrect argument leading the application to crash. An attacker could leverage this vulnerability to cause a Denial-of-Service condition in the application. |
| Hiredis is a minimalistic C client library for the Redis database. In affected versions Hiredis is vulnurable to integer overflow if provided maliciously crafted or corrupted `RESP` `mult-bulk` protocol data. When parsing `multi-bulk` (array-like) replies, hiredis fails to check if `count * sizeof(redisReply*)` can be represented in `SIZE_MAX`. If it can not, and the `calloc()` call doesn't itself make this check, it would result in a short allocation and subsequent buffer overflow. Users of hiredis who are unable to update may set the [maxelements](https://github.com/redis/hiredis#reader-max-array-elements) context option to a value small enough that no overflow is possible. |
| Redis is an open source, in-memory database that persists on disk. The redis-cli command line tool and redis-sentinel service may be vulnerable to integer overflow when parsing specially crafted large multi-bulk network replies. This is a result of a vulnerability in the underlying hiredis library which does not perform an overflow check before calling the calloc() heap allocation function. This issue only impacts systems with heap allocators that do not perform their own overflow checks. Most modern systems do and are therefore not likely to be affected. Furthermore, by default redis-sentinel uses the jemalloc allocator which is also not vulnerable. The problem is fixed in Redis versions 6.2.6, 6.0.16 and 5.0.14. |
