CWE:
 

Sorry. No results for Bugtraq WLB2


CVEMAP Search Results

CVE
Details
Description
2023-09-15
Waiting for details
CVE-2023-41880

Updating...
 

 
Wasmtime is a standalone runtime for WebAssembly. Wasmtime versions from 10.0.0 to versions 10.02, 11.0.2, and 12.0.1 contain a miscompilation of the WebAssembly `i64x2.shr_s` instruction on x86_64 platforms when the shift amount is a constant value that is larger than 32. Only x86_64 is affected so all other targets are not affected by this. The miscompilation results in the instruction producing an incorrect result, namely the low 32-bits of the second lane of the vector are derived from the low 32-bits of the second lane of the input vector instead of the high 32-bits. The primary impact of this issue is that any WebAssembly program using the `i64x2.shr_s` with a constant shift amount larger than 32 may produce an incorrect result. This issue is not an escape from the WebAssembly sandbox. Execution of WebAssembly guest programs will still behave correctly with respect to memory sandboxing and isolation from the host. Wasmtime considers non-spec-compliant behavior as a security issue nonetheless. This issue was discovered through fuzzing of Wasmtime's code generator Cranelift. Wasmtime versions 10.0.2, 11.0.2, and 12.0.2 are all patched to no longer have this miscompilation. This issue only affects x86_64 hosts and the only workaround is to either scan for this pattern in wasm modules which is nontrivial or to disable the SIMD proposal for WebAssembly. Users prior to 10.0.0 are unaffected by this vulnerability.

 
2023-05-22
Waiting for details
CVE-2023-28709

Updating...
 

 
The fix for CVE-2023-24998 was incomplete for Apache Tomcat 11.0.0-M2 to 11.0.0-M4, 10.1.5 to 10.1.7, 9.0.71 to 9.0.73 and 8.5.85 to 8.5.87. If non-default HTTP connector settings were used such that the maxParameterCount could be reached using query string parameters and a request was submitted that supplied exactly maxParameterCount parameters in the query string, the limit for uploaded request parts could be bypassed with the potential for a denial of service to occur.

 
2023-03-08
Waiting for details
CVE-2023-27477

Updating...
 

 
wasmtime is a fast and secure runtime for WebAssembly. Wasmtime's code generation backend, Cranelift, has a bug on x86_64 platforms for the WebAssembly `i8x16.select` instruction which will produce the wrong results when the same operand is provided to the instruction and some of the selected indices are greater than 16. There is an off-by-one error in the calculation of the mask to the `pshufb` instruction which causes incorrect results to be returned if lanes are selected from the second vector. This codegen bug has been fixed in Wasmtiem 6.0.1, 5.0.1, and 4.0.1. Users are recommended to upgrade to these updated versions. If upgrading is not an option for you at this time, you can avoid this miscompilation by disabling the Wasm simd proposal. Additionally the bug is only present on x86_64 hosts. Other platforms such as AArch64 and s390x are not affected.

 
2023-02-13
Waiting for details
CVE-2023-0818

Updating...
 

 
Off-by-one Error in GitHub repository gpac/gpac prior to v2.3.0-DEV.

 
2022-12-22
Waiting for details
CVE-2022-36354

Updating...
 

 
A heap out-of-bounds read vulnerability exists in the RLA format parser of OpenImageIO master-branch-9aeece7a and v2.3.19.0. More specifically, in the way run-length encoded byte spans are handled. A malformed RLA file can lead to an out-of-bounds read of heap metadata which can result in sensitive information leak. An attacker can provide a malicious file to trigger this vulnerability.

 
2022-11-08
Waiting for details
CVE-2022-3821

Updating...
 

 
An off-by-one Error issue was discovered in Systemd in format_timespan() function of time-util.c. An attacker could supply specific values for time and accuracy that leads to buffer overrun in format_timespan(), leading to a Denial of Service.

 
2022-11-07
Waiting for details
CVE-2022-3872

Updating...
 

 
An off-by-one read/write issue was found in the SDHCI device of QEMU. It occurs when reading/writing the Buffer Data Port Register in sdhci_read_dataport and sdhci_write_dataport, respectively, if data_count == block_size. A malicious guest could use this flaw to crash the QEMU process on the host, resulting in a denial of service condition.

 
2022-02-23
Medium
CVE-2021-4070

Vendor: V2fly
Software: V2ray-core
 

 
Off-by-one Error in GitHub repository v2fly/v2ray-core prior to 4.44.0.

 
2021-12-14
Low
CVE-2021-44007

Vendor: Siemens
Software: Jt2go
 

 
A vulnerability has been identified in JT2Go (All versions < V13.2.0.5), Teamcenter Visualization (All versions < V13.2.0.5). The Tiff_Loader.dll contains an off-by-one error in the heap while parsing specially crafted TIFF files. This could allow an attacker to cause a denial-of-service condition.

 
2021-05-14
Medium
CVE-2021-29529

Vendor: Google
Software: Tensorflow
 

 
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. 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.

 

 


Copyright 2024, cxsecurity.com

 

Back to Top