There is an integer overflow vulnerability in LDAP server of some Huawei products. Due to insufficient input validation, a remote attacker could exploit this vulnerability by sending malformed packets to the target devices. Successful exploit could cause the affected system crash.

There is an integer overflow vulnerability in LDAP client of some Huawei products. Due to insufficient input validation, a remote attacker could exploit this vulnerability by sending malformed packets to the target devices. Successful exploit could cause the affected system crash.

honor 8 Pro with software Duke-L09C10B120 and earlier versions,Duke-L09C432B120 and earlier versions,Duke-L09C636B120 and earlier versions has an integer overflow vulnerability. The attacker sends a response message to the device, which contains an illegal length field, it could produce an integer overflow and restart the modem system.

Huawei DP300 V500R002C00 have an integer overflow vulnerability due to the lack of validation. An authenticated local attacker can craft specific XML files to the affected products and parse this file, which result in DoS attacks.

Huawei Mate 9 Pro smartphones with software LON-AL00BC00B139D; LON-AL00BC00B229 have an integer overflow vulnerability. The camera driver does not validate the external input parameters and causes an integer overflow, which in the after processing results in a buffer overflow. An attacker tricks the user to install a crafted application, successful exploit could cause malicious code execution.

Huawei DP300 V500R002C00, RP200 V500R002C00, V600R006C00, TE30 V100R001C10, V500R002C00, V600R006C00, TE40 V500R002C00, V600R006C00, TE50 V500R002C00, V600R006C00, TE60 V100R001C10, V500R002C00, V600R006C00 have an integer overflow vulnerability. An unauthenticated, remote attacker may send specially crafted messages to the affected products. Due to insufficient input validation, successful exploit may cause integer overflow and some process abnormal.

The Bdat driver of Prague smart phones with software versions earlier than Prague-AL00AC00B211, versions earlier than Prague-AL00BC00B211, versions earlier than Prague-AL00CC00B211, versions earlier than Prague-TL00AC01B211, versions earlier than Prague-TL10AC01B211 has integer overflow vulnerability due to the lack of parameter validation. An attacker tricks a user into installing a malicious APP and execute it as a specific privilege; the APP can then send a specific parameter to the driver of the smart phone, causing arbitrary code execution.

Huawei AR3200 with software V200R006C10, V200R006C11, V200R007C00, V200R007C01, V200R007C02, V200R008C00, V200R008C10, V200R008C20, V200R008C30 has an integer overflow vulnerability. The software does not sufficiently validate certain field in SCTP messages, a remote unauthenticated attacker could send a crafted SCTP message to the device. Successful exploit could system reboot.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Integer Overflow or Wraparound in GitHub repository polonel/trudesk prior to 1.2.2.

Integer Overflow or Wraparound in GitHub repository polonel/trudesk prior to 1.2.3.

An issue has been found in PowerDNS Authoritative Server versions up to and including 3.4.10, 4.0.1 allowing an authorized user to crash the server by inserting a specially crafted record in a zone under their control then sending a DNS query for that record. The issue is due to an integer overflow when checking if the content of the record matches the expected size, allowing an attacker to cause a read past the buffer boundary.

An issue was discovered in Squid before 4.15 and 5.x before 5.0.6. Due to an input-validation bug, it is vulnerable to a Denial of Service attack (against all clients using the proxy). A client sends an HTTP Range request to trigger this.

An integer overflow in the getnum function in lua_struct.c in Redis before 6.0.3 allows context-dependent attackers with permission to run Lua code in a Redis session to cause a denial of service (memory corruption and application crash) or possibly bypass intended sandbox restrictions via a large number, which triggers a stack-based buffer overflow. NOTE: this issue exists because of a CVE-2015-8080 regression.

An integer overflow exists in pywin32 prior to version b301 when adding an access control entry (ACE) to an access control list (ACL) that would cause the size to be greater than 65535 bytes. An attacker who successfully exploited this vulnerability could crash the vulnerable process.

A vulnerability in the Secure Copy (SCP) feature of Cisco Adaptive Security Appliance (ASA) Software could allow an authenticated, remote attacker to cause a denial of service (DoS) condition. The vulnerability is due to the use of an incorrect data type for a length variable. An attacker could exploit this vulnerability by initiating the transfer of a large file to an affected device via SCP. To exploit this vulnerability, the attacker would need to have valid privilege level 15 credentials on the affected device. A successful exploit could allow the attacker to cause the length variable to roll over, which could cause the affected device to crash.

An Integer Signedness issue (for a return code) in the res_pjsip_sdp_rtp module in Digium Asterisk versions 15.7.1 and earlier and 16.1.1 and earlier allows remote authenticated users to crash Asterisk via a specially crafted SDP protocol violation.

A user authorized to perform database queries may trigger denial of service by issuing specially crafted queries, which use the $mod operator to overflow negative values. This issue affects: MongoDB Inc. MongoDB Server v4.4 versions prior to 4.4.1; v4.2 versions prior to 4.2.9; v4.0 versions prior to 4.0.20; v3.6 versions prior to 3.6.20.

Integer format vulnerability in the ticket number generator in Enhancesoft osTicket before 1.10.2 allows remote attackers to cause a denial-of-service (preventing the creation of new tickets) via a large number of digits in the ticket number format setting.

Allowing long password leads to denial of service in polonel/trudesk in GitHub repository polonel/trudesk prior to 1.2.2. This vulnerability can be abused by doing a DDoS attack for which genuine users will not able to access resources/applications.

The microweber application allows large characters to insert in the input field "fist & last name" which can allow attackers to cause a Denial of Service (DoS) via a crafted HTTP request. in microweber/microweber in GitHub repository microweber/microweber prior to 1.2.12.

Qemu emulator <= 3.0.0 built with the NE2000 NIC emulation support is vulnerable to an integer overflow, which could lead to buffer overflow issue. It could occur when receiving packets over the network. A user inside guest could use this flaw to crash the Qemu process resulting in DoS.

An issue was discovered in Squid before 4.15 and 5.x before 5.0.6. An integer overflow problem allows a remote server to achieve Denial of Service when delivering responses to HTTP Range requests. The issue trigger is a header that can be expected to exist in HTTP traffic without any malicious intent.

In TigerVNC 1.7.1 (SMsgReader.cxx SMsgReader::readClientCutText), by causing an integer overflow, an authenticated client can crash the server.

Tensorflow is an Open Source Machine Learning Framework. The implementation of `UnravelIndex` is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.