CyberSecBulletin
CVE-2026-62997NVD status: Deferred

kedro-plugins: Deserialization of Untrusted Data

Published Updated By the CyberSecBulletin desk

CVE-2026-62997 is a high-severity deserialization of untrusted data vulnerability in kedro-plugins from Kedro-org, with a CVSS 4.0 base score of 7.7 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. Affected kedro-plugins versions: >= 5.0.0, < 9.5.0. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.69% chance of exploitation within 30 days, higher than 53% of scored CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Check which version of kedro-plugins you run against the affected versions below, and install the vendor's latest release.
  2. Read the advisory on github.com for workarounds and exact fixed builds.
  3. Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
  4. Because the attack needs a user to take part, warn users about unexpected links and files related to this product until it is patched.

Affected products and versions

VendorProductAffected versionsFixed in
Kedro-orgkedro-plugins>= 5.0.0, < 9.5.0Not stated

Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.

How the severity score breaks down

Attack vector
NetworkCan be exploited remotely over a network, including the internet.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Attack requirements
PresentThe target must be in a specific state or configuration for the attack to work.
Privileges required
NoneNo account or login is needed.
User interaction
PassiveA user only needs to do something routine, such as viewing a page.
Confidentiality (vulnerable system)
HighSerious loss of confidentiality on the vulnerable system.
Integrity (vulnerable system)
HighSerious loss of integrity on the vulnerable system.
Availability (vulnerable system)
HighSerious loss of availability on the vulnerable system.
Confidentiality (other systems)
NoneNo loss of confidentiality on systems beyond the vulnerable one.
Integrity (other systems)
NoneNo loss of integrity on systems beyond the vulnerable one.
Availability (other systems)
NoneNo loss of availability on systems beyond the vulnerable one.

Vector: CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X. Scored by CNA (github.com).

Official description

Kedro-Datasets provides data connectors for Kedro. From version 5.0.0 until 9.5.0, kedro_datasets_experimental.pytorch.PyTorchDataset in kedro-datasets loads .pt model files with torch.load without enforcing weights_only=True, and user-supplied load_args are silently dropped. On PyTorch versions earlier than 2.6, a malicious pickle-backed model from an attacker-influenced shared registry, downloaded checkpoint, or partitioned external source can execute arbitrary code when a Kedro pipeline loads it. The issue affects only the opt-in kedro_datasets_experimental component and does not affect users who load only trusted files. This issue is fixed in version 9.5.0.

Source: the CVE record as published by its numbering authority, via NVD and CVE.org.

The underlying weakness: Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

How developers prevent this class of flaw

  • If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
  • When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
  • Explicitly define a final object() to prevent deserialization.

More Deserialization of Untrusted Data vulnerabilities (CWE-502)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
  3. Record last changed materially (score, affected products, status or references).

References

Recent Deserialization of Untrusted Data vulnerabilities

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