CyberSecBulletin
CVE-2026-120859NVD status: Deferred

PyMoDAQ: Improper Neutralization of Directives in Dynamically Evaluated Code

Published Updated By the CyberSecBulletin desk

CVE-2026-120859 is a high-severity improper neutralization of directives in dynamically evaluated code vulnerability in PyMoDAQ, with a CVSS 3.1 base score of 7.8 out of 10. It can be exploited with local access to the system by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. The record lists version 4.4.13 as the first without the flaw, so updating PyMoDAQ to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.19% chance of exploitation within 30 days, which is low compared with other CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Update PyMoDAQ to 4.4.13 or a later version.
  2. Update pymodaq_data to 5.1.15 or 5.2.14 or 5.3.10, whichever matches your release line, or a later version.
  3. Update pymodaq_gui to 5.1.15 or 5.2.14 or 5.3.10, whichever matches your release line, or a later version.
  4. Read the advisory on github.com for workarounds and exact fixed builds.
  5. 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
PyMoDAQPyMoDAQbefore 4.4.134.4.13
PyMoDAQpymodaq_databefore 5.1.15; 5.2.0 up to, but not including, 5.2.14; 5.3.0 up to, but not including, 5.3.105.1.15, 5.2.14, 5.3.10
PyMoDAQpymodaq_guibefore 5.1.15; 5.2.0 up to, but not including, 5.2.14; 5.3.0 up to, but not including, 5.3.105.1.15, 5.2.14, 5.3.10
PyMoDAQpymodaq_utilsbefore 5.1.15; 5.2.0 up to, but not including, 5.2.14; 5.3.0 up to, but not including, 5.3.105.1.15, 5.2.14, 5.3.10

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
LocalThe attacker needs local access or must trick a user into running something.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Privileges required
NoneNo account or login is needed.
User interaction
RequiredA user must take an action such as opening a file or link.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
HighAll data handled by the component can be read.
Integrity
HighData or code can be modified at will.
Availability
HighThe component can be taken down completely.

Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H. Scored by CNA (vulncheck.com).

Scoring systemScoreSeverityScored by
CVSS 4.08.5HighCNA (vulncheck.com)
CVSS 3.17.8HighCNA (vulncheck.com)

Official description

PyMoDAQ before 4.4.13, and pymodaq_data, pymodaq_gui, and pymodaq_utils before 5.1.15, 5.2.x before 5.2.14, and 5.3.x before 5.3.10, contain deserialization of untrusted data and eval injection vulnerabilities that allow attackers to execute arbitrary code by supplying crafted files that a user opens. Attackers can store pickled objects in HDF5 string nodes that StringARRAY.array_to_string() passes to pickle.loads() when the node is browsed or read, place Python expressions in HDF5 attributes that JsonConverter.json2object() evaluates, supply a .dock file that load_layout_state() unpickles from the Dashboard Load layout action, or embed Python expressions in XML settings files that elt_to_dict() and set_txt_from_elt() evaluate.

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

The underlying weakness: Improper Neutralization of Directives in Dynamically Evaluated Code

The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes code syntax before using the input in a dynamic evaluation call (e.g. eval).

How developers prevent this class of flaw

  • If possible, refactor your code so that it does not need to use eval() at all.
  • For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures, so the python documentation discourages use of ast.literal_eval() on untrusted data.

More Improper Neutralization of Directives in Dynamically Evaluated Code vulnerabilities (CWE-95)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: total).
  3. Record last changed materially (score, affected products, status or references).

References

Recent Improper Neutralization of Directives in Dynamically Evaluated Code vulnerabilities

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