Vulnerabilities (CVE)

NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer, where sign conversion issuescasting an unsigned primitive to signed may lead to denial of service or information disclosure.

An integer conversion vulnerability exists in the SORBAx64.dll RecvPacket functionality of WellinTech KingHistorian 35.01.00.05. A specially crafted network packet can lead to a buffer overflow. An attacker can send a malicious packet to trigger this vulnerability.

Oxenstored 32->31 bit integer truncation issues Integers in Ocaml are 63 or 31 bits of signed precision. The Ocaml Xenbus library takes a C uint32_t out of the ring and casts it directly to an Ocaml integer. In 64-bit Ocaml builds this is fine, but in 32-bit builds, it truncates off the most significant bit, and then creates unsigned/signed confusion in the remainder. This in turn can feed a negative value into logic not expecting a negative value, resulting in unexpected exceptions being thrown ... Oxenstored 32->31 bit integer truncation issues Integers in Ocaml are 63 or 31 bits of signed precision. The Ocaml Xenbus library takes a C uint32_t out of the ring and casts it directly to an Ocaml integer. In 64-bit Ocaml builds this is fine, but in 32-bit builds, it truncates off the most significant bit, and then creates unsigned/signed confusion in the remainder. This in turn can feed a negative value into logic not expecting a negative value, resulting in unexpected exceptions being thrown. The unexpected exception is not handled suitably, creating a busy-loop trying (and failing) to take the bad packet out of the xenstore ring.

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A vulnerability has been identified in SIPLUS TIM 1531 IRC (6AG1543-1MX00-7XE0) (All versions < V2.4.8), TIM 1531 IRC (6GK7543-1MX00-0XE0) (All versions < V2.4.8). Casting an internal value could lead to floating point exception under certain circumstances. This could allow an attacker to cause a denial of service condition on affected devices.

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.

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 ... 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.

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NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer handler, where an unprivileged regular user can cause an integer to be truncated, which may lead to denial of service or data tampering.

NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer handler, where an unprivileged regular user can cause truncation errors when casting a primitive to a primitive of smaller size causes data to be lost in the conversion, which may lead to denial of service or information disclosure.

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.

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.

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.

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 evaluated

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).

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 mini ... 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.

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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 TensorF ... 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.

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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 d ... 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.

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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 wh ... 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.

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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` ... 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.

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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 ... 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.

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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 ... 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.

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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 a ... 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.

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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.

Cranelift is an open-source code generator maintained by Bytecode Alliance. It translates a target-independent intermediate representation into executable machine code. There is a bug in 0.73 of the Cranelift x64 backend that can create a scenario that could result in a potential sandbox escape in a Wasm program. This bug was introduced in the new backend on 2020-09-08 and first included in a release on 2020-09-30, but the new backend was not the default prior to 0.73. The recently-released vers ... Cranelift is an open-source code generator maintained by Bytecode Alliance. It translates a target-independent intermediate representation into executable machine code. There is a bug in 0.73 of the Cranelift x64 backend that can create a scenario that could result in a potential sandbox escape in a Wasm program. This bug was introduced in the new backend on 2020-09-08 and first included in a release on 2020-09-30, but the new backend was not the default prior to 0.73. The recently-released version 0.73 with default settings, and prior versions with an explicit build flag to select the new backend, are vulnerable. The bug in question performs a sign-extend instead of a zero-extend on a value loaded from the stack, under a specific set of circumstances. If those circumstances occur, the bug could allow access to memory addresses upto 2GiB before the start of the Wasm program heap. If the heap bound is larger than 2GiB, then it would be possible to read memory from a computable range dependent on the size of the heaps bound. The impact of this bug is highly dependent on heap implementation, specifically: * if the heap has bounds checks, and * does not rely exclusively on guard pages, and * the heap bound is 2GiB or smaller * then this bug cannot be used to reach memory from another Wasm program heap. The impact of the vulnerability is mitigated if there is no memory mapped in the range accessible using this bug, for example, if there is a 2 GiB guard region before the Wasm program heap. The bug in question performs a sign-extend instead of a zero-extend on a value loaded from the stack, when the register allocator reloads a spilled integer value narrower than 64 bits. This interacts poorly with another optimization: the instruction selector elides a 32-to-64-bit zero-extend operator when we know that an instruction producing a 32-bit value actually zeros the upper 32 bits of its destination register. Hence, we rely on these zeroed bits, but the type of the value is still i32, and the spill/reload reconstitutes those bits as the sign extension of the i32’s MSB. The issue would thus occur when: * An i32 value in a Wasm program is greater than or equal to 0x8000_0000; * The value is spilled and reloaded by the register allocator due to high register pressure in the program between the value’s definition and its use; * The value is produced by an instruction that we know to be “special” in that it zeroes the upper 32 bits of its destination: add, sub, mul, and, or; * The value is then zero-extended to 64 bits in the Wasm program; * The resulting 64-bit value is used. Under these circumstances there is a potential sandbox escape when the i32 value is a pointer. The usual code emitted for heap accesses zero-extends the Wasm heap address, adds it to a 64-bit heap base, and accesses the resulting address. If the zero-extend becomes a sign-extend, the program could reach backward and access memory up to 2GiB before the start of its heap. In addition to assessing the nature of the code generation bug in Cranelift, we have also determined that under specific circumstances, both Lucet and Wasmtime using this version of Cranelift may be exploitable. See referenced GitHub Advisory for more details.

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Trend Micro Password Manager (Consumer) version 5.0.0.1217 and below is vulnerable to an Integer Truncation Privilege Escalation vulnerability which could allow a local attacker to trigger a buffer overflow and escalate privileges on affected installations. An attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability.

TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit ... TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument.

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A specifically crafted packet sent by an attacker to EIPStackGroup OpENer EtherNet/IP commits and versions prior to Feb 10, 2021 may cause a denial-of-service condition.

An issue was discovered in GNOME GLib before 2.66.6 and 2.67.x before 2.67.3. The function g_bytes_new has an integer overflow on 64-bit platforms due to an implicit cast from 64 bits to 32 bits. The overflow could potentially lead to memory corruption.

An issue was discovered in GNOME GLib before 2.66.7 and 2.67.x before 2.67.4. If g_byte_array_new_take() was called with a buffer of 4GB or more on a 64-bit platform, the length would be truncated modulo 2**32, causing unintended length truncation.

Due to unexpected data type conversions, a use-after-free could have occurred when interacting with the font cache. We presume that with enough effort this could have been exploited to run arbitrary code. This vulnerability affects Firefox < 88.

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.

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.

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-193363621

Nagios NRPE 3.2.1 has a Heap-Based Buffer Overflow, as demonstrated by interpretation of a small negative number as a large positive number during a bzero call.

An exploitable signed comparison vulnerability exists in the ARMv7 memcpy() implementation of GNU glibc 2.30.9000. Calling memcpy() (on ARMv7 targets that utilize the GNU glibc implementation) with a negative value for the 'num' parameter results in a signed comparison vulnerability. If an attacker underflows the 'num' parameter to memcpy(), this vulnerability could lead to undefined behavior such as writing to out-of-bounds memory and potentially remote code execution. Furthermore, this memcpy( ... An exploitable signed comparison vulnerability exists in the ARMv7 memcpy() implementation of GNU glibc 2.30.9000. Calling memcpy() (on ARMv7 targets that utilize the GNU glibc implementation) with a negative value for the 'num' parameter results in a signed comparison vulnerability. If an attacker underflows the 'num' parameter to memcpy(), this vulnerability could lead to undefined behavior such as writing to out-of-bounds memory and potentially remote code execution. Furthermore, this memcpy() implementation allows for program execution to continue in scenarios where a segmentation fault or crash should have occurred. The dangers occur in that subsequent execution and iterations of this code will be executed with this corrupted data.

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In FreeRDP before version 2.1.2, there is an integer casting vulnerability in update_recv_secondary_order. All clients with +glyph-cache /relax-order-checks are affected. This is fixed in version 2.1.2.

An issue was discovered in the nanorand crate before 0.5.1 for Rust. It caused any random number generator (even ChaCha) to return all zeroes because integer truncation was mishandled.

Vulnerability in the Oracle VM VirtualBox product of Oracle Virtualization (component: Core). Supported versions that are affected are Prior to 5.2.40, prior to 6.0.20 and prior to 6.1.6. Easily exploitable vulnerability allows high privileged attacker with logon to the infrastructure where Oracle VM VirtualBox executes to compromise Oracle VM VirtualBox. While the vulnerability is in Oracle VM VirtualBox, attacks may significantly impact additional products. Successful attacks of this vulnerabi ... Vulnerability in the Oracle VM VirtualBox product of Oracle Virtualization (component: Core). Supported versions that are affected are Prior to 5.2.40, prior to 6.0.20 and prior to 6.1.6. Easily exploitable vulnerability allows high privileged attacker with logon to the infrastructure where Oracle VM VirtualBox executes to compromise Oracle VM VirtualBox. While the vulnerability is in Oracle VM VirtualBox, attacks may significantly impact additional products. Successful attacks of this vulnerability can result in takeover of Oracle VM VirtualBox. CVSS 3.0 Base Score 8.2 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.0/AV:L/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:H).

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An information disclosure vulnerability exists in the /proc/pid/syscall functionality of Linux Kernel 5.1 Stable and 5.4.66. More specifically, this issue has been introduced in v5.1-rc4 (commit 631b7abacd02b88f4b0795c08b54ad4fc3e7c7c0) and is still present in v5.10-rc4, so it’s likely that all versions in between are affected. An attacker can read /proc/pid/syscall to trigger this vulnerability, which leads to the kernel leaking memory contents.

An issue was discovered in the Linux kernel before 5.8.15. scalar32_min_max_or in kernel/bpf/verifier.c mishandles bounds tracking during use of 64-bit values, aka CID-5b9fbeb75b6a.