5.5

CVE-2022-29210

TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function used total estimated `AllocatedBytes()`, which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. `int32_t`). It also tried to access individual tensor bytes through `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the `.data()` buffer. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.

Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Google ≫ Tensorflow Version2.8.0
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.04% 0.102
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
nvd@nist.gov 5.5 1.8 3.6
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
nvd@nist.gov 2.1 3.9 2.9
AV:L/AC:L/Au:N/C:N/I:N/A:P
security-advisories@github.com 5.5 1.8 3.6
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CWE-120 Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')

The product copies an input buffer to an output buffer without verifying that the size of the input buffer is less than the size of the output buffer, leading to a buffer overflow.

CWE-122 Heap-based Buffer Overflow

A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().

CWE-787 Out-of-bounds Write

The product writes data past the end, or before the beginning, of the intended buffer.