Vulnerabilities (CVE)

Possible out of bound memory access due to improper boundary check while creating HSYNC fence in Snapdragon Auto, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables

Possible buffer overflow due to lack of range check while processing a DIAG command for COEX management in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

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 `o ... 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.

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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. ... 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.

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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 Tens ... 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.

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TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10 ... TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values. 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.

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TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-fai ... TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. 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.

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Multiple buffer overflow vulnerabilities when parsing a specially crafted file in Esri ArcReader, ArcGIS Desktop, ArcGIS Engine 10.8.1 (and earlier) and ArcGIS Pro 2.7 (and earlier) allow an unauthenticated attacker to achieve arbitrary code execution in the context of the current user.

In the standard library in Rust before 1.52.0, the Zip implementation calls __iterator_get_unchecked() more than once for the same index (under certain conditions) when next_back() and next() are used together. This bug could lead to a memory safety violation due to an unmet safety requirement for the TrustedRandomAccess trait.

In the standard library in Rust before 1.51.0, the Zip implementation calls __iterator_get_unchecked() for the same index more than once when nested. This bug can lead to a memory safety violation due to an unmet safety requirement for the TrustedRandomAccess trait.

An issue was discovered in the quinn crate before 0.7.0 for Rust. It may have invalid memory access for certain versions of the standard library because it relies on a direct cast of std::net::SocketAddrV4 and std::net::SocketAddrV6 data structures.

Command Injection in Tenda G1 and G3 routers with firmware versions v15.11.0.17(9502)_CN or v15.11.0.16(9024)_CN allows remote attackers to execute arbitrary OS commands via a crafted "action/umountUSBPartition" request. This occurs because the "formSetUSBPartitionUmount" function executes the "doSystemCmd" function with untrusted input.

Command Injection in Tenda G0 routers with firmware versions v15.11.0.6(9039)_CN and v15.11.0.5(5876)_CN , and Tenda G1 and G3 routers with firmware versions v15.11.0.17(9502)_CN or v15.11.0.16(9024)_CN allows remote attackers to execute arbitrary OS commands via a crafted action/setDebugCfg request. This occurs because the "formSetDebugCfg" function executes glibc's system function with untrusted input.

When JTEKT Corporation TOYOPUC PLC versions PC10G-CPU, 2PORT-EFR, Plus CPU, Plus EX, Plus EX2, Plus EFR, Plus EFR2, Plus 2P-EFR, PC10P-DP, PC10P-DP-IO, Plus BUS-EX, Nano 10GX, Nano 2ET,PC10PE, PC10PE-16/16P, PC10E, FL/ET-T-V2H, PC10B,PC10B-P, Nano CPU, PC10P, and PC10GE receive an invalid frame, the outside area of a receive buffer for FL-net are overwritten. As a result, the PLC CPU detects a system error, and the affected products stop.

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 memory corruption condition. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13287)

An issue was discovered in the nb-connect crate before 1.0.3 for Rust. It may have invalid memory access for certain versions of the standard library because it relies on a direct cast of std::net::SocketAddrV4 and std::net::SocketAddrV6 data structures.

Windows Graphics Component Elevation of Privilege Vulnerability

An issue was discovered in sthttpd through 2.27.1. On systems where the strcpy function is implemented with memcpy, the de_dotdot function may cause a Denial-of-Service (daemon crash) due to overlapping memory ranges being passed to memcpy. This can triggered with an HTTP GET request for a crafted filename. NOTE: this is similar to CVE-2017-10671, but occurs in a different part of the de_dotdot function.

Insufficient bound checks in the System Management Unit (SMU) may result in access to an invalid address space that could result in denial of service.

Insufficient bound checks related to PCIE in the System Management Unit (SMU) may result in access to an invalid address space that could result in denial of service.

A malicious or compromised UApp or ABL may be used by an attacker to send a malformed system call to the bootloader, resulting in out-of-bounds memory accesses.

Insufficient bounds checking in an SMU mailbox register could allow an attacker to potentially read outside of the SRAM address range which could result in an exception handling leading to a potential denial of service.

Insufficient bound checks in System Management Unit (SMU) PCIe Hot Plug table may result in access/updates from/to invalid address space that could result in denial of service.

Insufficient bounds checking in System Management Unit (SMU) may cause invalid memory accesses/updates that could result in SMU hang and subsequent failure to service any further requests from other components.

A vulnerability has been identified in SIMATIC HMI Comfort Outdoor Panels V15 7\" & 15\" (incl. SIPLUS variants) (All versions < V15.1 Update 6), SIMATIC HMI Comfort Outdoor Panels V16 7\" & 15\" (incl. SIPLUS variants) (All versions < V16 Update 4), SIMATIC HMI Comfort Panels V15 4\" - 22\" (incl. SIPLUS variants) (All versions < V15.1 Update 6), SIMATIC HMI Comfort Panels V16 4\" - 22\" (incl. SIPLUS variants) (All versions < V16 Update 4), SIMATIC HMI KTP Mobile Panels V15 KTP400F, KTP700, KT ... A vulnerability has been identified in SIMATIC HMI Comfort Outdoor Panels V15 7\" & 15\" (incl. SIPLUS variants) (All versions < V15.1 Update 6), SIMATIC HMI Comfort Outdoor Panels V16 7\" & 15\" (incl. SIPLUS variants) (All versions < V16 Update 4), SIMATIC HMI Comfort Panels V15 4\" - 22\" (incl. SIPLUS variants) (All versions < V15.1 Update 6), SIMATIC HMI Comfort Panels V16 4\" - 22\" (incl. SIPLUS variants) (All versions < V16 Update 4), SIMATIC HMI KTP Mobile Panels V15 KTP400F, KTP700, KTP700F, KTP900 and KTP900F (All versions < V15.1 Update 6), SIMATIC HMI KTP Mobile Panels V16 KTP400F, KTP700, KTP700F, KTP900 and KTP900F (All versions < V16 Update 4), SIMATIC WinCC Runtime Advanced V15 (All versions < V15.1 Update 6), SIMATIC WinCC Runtime Advanced V16 (All versions < V16 Update 4). SmartVNC has an out-of-bounds memory access vulnerability that could be triggered on the server side when sending data from the client, which could result in a Denial-of-Service condition.

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An improper boundary check in secure_log of LDFW and BL31 prior to SMR Dec-2021 Release 1 allows arbitrary memory write and code execution.

Lack of boundary checking of a buffer in libSPenBase library of Samsung Notes prior to Samsung Note version 4.3.02.61 allows OOB read

An improper input validation vulnerability in libsapeextractor library prior to SMR Sep-2021 Release 1 allows attackers to execute arbitrary code in mediaextractor process.

An improper input validation vulnerability in sflacfd_get_frm() in libsflacextractor library prior to SMR MAY-2021 Release 1 allows attackers to execute arbitrary code on mediaextractor process.

An improper input validation vulnerability in sdfffd_parse_chunk_FVER() in libsdffextractor library prior to SMR MAY-2021 Release 1 allows attackers to execute arbitrary code on mediaextractor process.

An improper input validation vulnerability in sdfffd_parse_chunk_PROP() in libsdffextractor library prior to SMR MAY-2021 Release 1 allows attackers to execute arbitrary code on mediaextractor process.

An improper input validation vulnerability in scmn_mfal_read() in libsapeextractor library prior to SMR MAY-2021 Release 1 allows attackers to execute arbitrary code on mediaextractor process.

In ISC DHCP 4.1-ESV-R1 -> 4.1-ESV-R16, ISC DHCP 4.4.0 -> 4.4.2 (Other branches of ISC DHCP (i.e., releases in the 4.0.x series or lower and releases in the 4.3.x series) are beyond their End-of-Life (EOL) and no longer supported by ISC. From inspection it is clear that the defect is also present in releases from those series, but they have not been officially tested for the vulnerability), The outcome of encountering the defect while reading a lease that will trigger it varies, according to: the ... In ISC DHCP 4.1-ESV-R1 -> 4.1-ESV-R16, ISC DHCP 4.4.0 -> 4.4.2 (Other branches of ISC DHCP (i.e., releases in the 4.0.x series or lower and releases in the 4.3.x series) are beyond their End-of-Life (EOL) and no longer supported by ISC. From inspection it is clear that the defect is also present in releases from those series, but they have not been officially tested for the vulnerability), The outcome of encountering the defect while reading a lease that will trigger it varies, according to: the component being affected (i.e., dhclient or dhcpd) whether the package was built as a 32-bit or 64-bit binary whether the compiler flag -fstack-protection-strong was used when compiling In dhclient, ISC has not successfully reproduced the error on a 64-bit system. However, on a 32-bit system it is possible to cause dhclient to crash when reading an improper lease, which could cause network connectivity problems for an affected system due to the absence of a running DHCP client process. In dhcpd, when run in DHCPv4 or DHCPv6 mode: if the dhcpd server binary was built for a 32-bit architecture AND the -fstack-protection-strong flag was specified to the compiler, dhcpd may exit while parsing a lease file containing an objectionable lease, resulting in lack of service to clients. Additionally, the offending lease and the lease immediately following it in the lease database may be improperly deleted. if the dhcpd server binary was built for a 64-bit architecture OR if the -fstack-protection-strong compiler flag was NOT specified, the crash will not occur, but it is possible for the offending lease and the lease which immediately followed it to be improperly deleted.

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A CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability that could cause a Denial of Service on the Modicon PLC controller / simulator when updating the controller application with a specially crafted project file exists in Modicon M580 CPU (part numbers BMEP* and BMEH*, all versions), Modicon M340 CPU (part numbers BMXP34*, all versions), Modicon MC80 (part numbers BMKC80*, all versions), Modicon Momentum Ethernet CPU (part numbers 171CBU*, all versions) ... A CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability that could cause a Denial of Service on the Modicon PLC controller / simulator when updating the controller application with a specially crafted project file exists in Modicon M580 CPU (part numbers BMEP* and BMEH*, all versions), Modicon M340 CPU (part numbers BMXP34*, all versions), Modicon MC80 (part numbers BMKC80*, all versions), Modicon Momentum Ethernet CPU (part numbers 171CBU*, all versions), PLC Simulator for EcoStruxureª Control Expert, including all Unity Pro versions (former name of EcoStruxureª Control Expert, all versions), PLC Simulator for EcoStruxureª Process Expert including all HDCS versions (former name of EcoStruxureª Process Expert, all versions), Modicon Quantum CPU (part numbers 140CPU*, all versions), Modicon Premium CPU (part numbers TSXP5*, all versions).

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A CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability exists inIGSS Definition (Def.exe) V15.0.0.21140 and prior that could result in disclosure of information or remote code e+F15xecution due to missing length check on user supplied data, when a malicious CGF file is imported to IGSS Definition.

A CWE-119:Improper restriction of operations within the bounds of a memory buffer vulnerability exists in PowerLogic ION7400, PM8000 and ION9000 (All versions prior to V3.0.0), which could cause the meter to reboot or allow for remote code execution.

A CWE-119:Improper restriction of operations within the bounds of a memory buffer vulnerability exists in PowerLogic ION8650, ION8800, ION7650, ION7700/73xx, and ION83xx/84xx/85xx/8600 (see security notifcation for affected versions), which could cause the meter to reboot.

A CWE-119:Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability exists in Interactive Graphical SCADA System (IGSS) Definition (Def.exe) V15.0.0.21041 and prior, which could result in arbitrary read or write conditions when malicious CGF (Configuration Group File) file is imported to IGSS Definition due to an unchecked pointer address.

A CWE-119:Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability exists in Interactive Graphical SCADA System (IGSS) Definition (Def.exe) V15.0.0.21041 and prior, which could result in arbitrary read or write conditions when malicious CGF (Configuration Group File) file is imported to IGSS Definition due to missing validation of input data.

A CWE-119:Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability exists in Interactive Graphical SCADA System (IGSS) Definition (Def.exe) V15.0.0.21041 and prior, which could cause remote code execution when malicious CGF (Configuration Group File) file is imported to IGSS Definition.