6.1Medium

CVE-2026-55093

Tract is a tiny, no-nonsense, self-contained TensorFlow and ONNX inference toolkit. Prior to 0.21.16, 0.22.2, and 0.23.1, tract-nnef uses unchecked usize multiplication in nnef/src/tensors.rs read_tensor for attacker-controlled tensor dimensions, the allocation size, and the reported tensor length. Loading a crafted NNEF archive through model_for_path or model_for_read reaches the default DatLoader and can make the wrapped size check accept a small allocation while data/src/tensor.rs as_slice_unchecked creates a much larger logical slice. Model construction through as_uniform can then read beyond the heap allocation and disclose adjacent data, and later access can terminate the process with a segmentation fault. The affected dense numeric tensor path does not include the independently guarded bool, String, or block-quant paths, and no out-of-bounds write or code execution was demonstrated. This issue is fixed in versions 0.21.16, 0.22.2, and 0.23.1.

What this means for your business

  • An attacker can use it only with access to the machine itself, without a login, but only after tricking someone into an action such as opening a file or a link.
  • FIRST's prediction model gives it a 0.2% chance of attack attempts being seen in the next 30 days, ranking above 9% of all known flaws.

What to do

  1. 1Ask your IT team or provider whether any of your systems use the affected product.
  2. 2If you do, follow the vendor's guidance. No patch reference has been published yet.

Not sure if your company is exposed?

Fastnexa’s certified penetration testers can check whether attackers could use this flaw, or others like it, against your websites, apps and network. The full test is free for our first 10 founding clients until 31 December 2026.

Scoring

CVSS
6.1 (v3.1)
Vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:H
Weakness
CWE-125
Assigned by
security-advisories@github.com

Dates

Published
2026-09-14
Last modified
2026-09-14
Sources
NVD

References