Incorrect Conversion between Numeric Types

An integer conversion error in Hermes bytecode generation, prior to commit 6aa825e480d48127b480b08d13adf70033237097, could have been used to perform Out-Of-Bounds operations and subsequently execute arbitrary code. Note that this is only exploitable in cases where Hermes is used to execute untrusted JavaScript. Hence, most React Native applications are not affected.Show less

Besu is a Java-based Ethereum client. In versions newer than 22.1.3 and prior to 22.7.1, Besu is subject to an Incorrect Conversion between Numeric Types. An error in 32 bit signed and unsigned types in the calculation of available gas in the CALL operations (including DELEGATECALL) results in incorrect gas being passed into called contracts and incorrect gas being returned after call execution. Where the amount of gas makes a difference in the success or failure, or if the gas is a negative 64 bit value, the execution will result in a different state root than expected, resulting in a consensus failure in networks with multiple EVM implementations. In networks with a single EVM implementation this can be used to execute with significantly more gas than then transaction requested, possibly exceeding gas limitations. This issue is patched in version 22.7.1. As a workaround, reverting to version 22.1.3 or earlier will prevent incorrect execution.Show less

An integer coercion error was found in the openvswitch kernel module. Given a sufficiently large number of actions, while copying and reserving memory for a new action of a new flow, the reserve_sfa_size() function does not return -EMSGSIZE as expected, potentially leading to an out-of-bounds write access. This flaw allows a local user to crash or potentially escalate their privileges on the system.Show less

The Apache Xalan Java XSLT library is vulnerable to an integer truncation issue when processing malicious XSLT stylesheets. This can be used to corrupt Java class files generated by the internal XSLTC compiler and execute arbitrary Java bytecode. Users are recommended to update to version 2.7.3 or later. Note: Java runtimes (such as OpenJDK) include repackaged copies of Xalan.Show less

A vulnerability was found in FFmpeg 2.0. It has been classified as problematic. Affected is an unknown function of the file libavcodec/dxtroy.c. The manipulation leads to integer coercion error. It is possible to launch the attack remotely. It is recommended to apply a patch to fix this issue.Show less

A vulnerability was found in FFmpeg 2.0. It has been declared as problematic. Affected by this vulnerability is the function decode_frame of the file libavcodec/ansi.c. The manipulation leads to integer coercion error. The attack can be launched remotely. It is recommended to apply a patch to fix this issue.Show less

On F5 BIG-IP 16.1.x versions prior to 16.1.2.2, 15.1.x versions prior to 15.1.5.1, 14.1.x versions prior to 14.1.4.6, 13.1.x versions prior to 13.1.5, and all versions of 12.1.x and 11.6.x, when an Internet Content Adaptation Protocol (ICAP) profile is configured on a virtual server, undisclosed traffic can cause an increase in Traffic Management Microkernel (TMM) memory resource utilization. Note: Software versions which have reached End of Technical Support (EoTS) are not evaluatedShow less

A flaw was found in the sctp_make_strreset_req function in net/sctp/sm_make_chunk.c in the SCTP network protocol in the Linux kernel with a local user privilege access. In this flaw, an attempt to use more buffer than is allocated triggers a BUG_ON issue, leading to a denial of service (DOS).Show less

slaacd in OpenBSD 6.9 and 7.0 before 2022-03-22 has an integer signedness error and resultant heap-based buffer overflow triggerable by a crafted IPv6 router advertisement. NOTE: privilege separation and pledge can prevent exploitation.Show less

In C2SoftMP3::process() of C2SoftMp3Dec.cpp, there is a possible out of bounds write due to a heap buffer overflow. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-9Android ID: A-193363621Show less

Besu is an Ethereum client written in Java. Starting in version 21.10.0, changes in the implementation of the SHL, SHR, and SAR operations resulted in the introduction of a signed type coercion error in values that represent negative values for 32 bit signed integers. Smart contracts that ask for shifts between approximately 2 billion and 4 billion bits (nonsensical but valid values for the operation) will fail to execute and hence fail to validate. In networks where vulnerable versions are mining with other clients or non-vulnerable versions this will result in a fork and the relevant transactions will not be included in the fork. In networks where vulnerable versions are not mining (such as Rinkeby) no fork will result and the validator nodes will stop accepting blocks. In networks where only vulnerable versions are mining the relevant transaction will not be included in any blocks. When the network adds a non-vulnerable version the network will act as in the first case. Besu 21.10.2 contains a patch for this issue. Besu 21.7.4 is not vulnerable and clients can roll back to that version. There is a workaround available: Once a transaction with the relevant shift operations is included in the canonical chain, the only remediation is to make sure all nodes are on non-vulnerable versions.Show less

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.Show less

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.Show less

An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. When processing the 'hdlr' FOURCC code, a specially crafted MPEG-4 input can cause an improper memory allocation resulting in a heap-based buffer overflow that causes memory corruption. An attacker can convince a user to open a video to trigger this vulnerability.Show less

An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. A specially crafted MPEG-4 input can cause an improper memory allocation resulting in a heap-based buffer overflow that causes memory corruption. The FOURCC code, 'trik', is parsed by the function within the library. An attacker can convince a user to open a video to trigger this vulnerability.Show less

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.Show less

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.Show less

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.Show less