#VU86630 Incorrect Calculation of Buffer Size in TensorFlow - CVE-2022-41887

Vulnerability identifier: #VU86630

Vulnerability risk: Medium

CVSSv4.0: 6.6 [CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:U/U:Green]

CVE-ID: CVE-2022-41887

CWE-ID: CWE-131

Exploitation vector: Network

Exploit availability: No

Vulnerable software:
TensorFlow
Server applications / Other server solutions

Vendor: TensorFlow

Description

The vulnerability allows a remote attacker to perform a denial of service (DoS) attack.

The vulnerability exists due to `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. A remote attacker can trigger resource exhaustion and perform a denial of service (DoS) attack.

Mitigation
Install updates from vendor's website.

Vulnerable software versions

TensorFlow: 2.9.3, 2.10.1

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External links
https://github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8fvv-46hw-vpg3
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h

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Q & A

Can this vulnerability be exploited remotely?

Yes. This vulnerability can be exploited by a remote non-authenticated attacker via the Internet.

Is there known malware, which exploits this vulnerability?

No. We are not aware of malware exploiting this vulnerability.