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MEDIUM

CVE-2023-25661

CVE-2023-25661 — Denial of Service in TensorFlow

TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.

Published Updated Sources: cvelistV5, GitHub_M

Triage

Is it exploited, how likely is exploitation, what does it touch, and how severe do the scoring sources call it.

Exploitation

Unreported

no source claims exploitation

EPSS

0%

chance of exploitation in 30 days

Affects

tensorflow

tensorflow

CVSS base

6.5

MEDIUM

CISA SSVC assessment

Three decision points CISA publishes for the CVEs it assesses · SSVC 2.0.3. A stakeholder decision, not a severity score.

CISA

Exploitation

PoC

none · proof-of-concept · active

Automatable

No

can an attacker script all four kill-chain steps

Technical impact

Partial

partial · total control of the vulnerable component

Affected scope

The catalog records vendors and products as separate lists, not pairs, so which product belongs to which vendor is not something this page can say.

Vendors (1)

Products (1)

tensorflow

Every base score collected

Sources score independently and disagree; each row says who scored it and under which version.

ScoreVersionSeverityExpl.ImpactSource
6.5CVSS 3.1MEDIUMcvelistV5

Weakness & attack patterns

  • CWE-20

Attack patterns reported against this CVE. The ATT&CK techniques below are inferred from its weakness class.

  • T1562.003Impair Defenses: Impair Command History Logging
  • T1574.006Hijack Execution Flow: Dynamic Linker Hijacking
  • T1574.007Hijack Execution Flow: Path Interception by PATH Environment Variable

References

2 on the record

Elsewhere on this site

Not in any source we poll

Listed rather than left blank: an empty field and an unmeasured one look identical on screen, and only one is a reason to look elsewhere.

  • No confirmed IOCs, IP addresses, domains, file hashes, or malware artifacts supplied.
  • No organization-specific asset inventory, compensating-control status, or patch deployment evidence supplied.
  • No exploit packet captures, log samples, or incident case IDs supplied.