Quick answer
Direct answer
Risk scores
| CVSS metric | What it means |
|---|---|
| Attack vector (AV:N) | Network: reachable remotely |
| Attack complexity (AC:H) | High complexity |
| Attack requirements (AT:P) | Attack requirements present |
| Privileges required (PR:H) | High privileges required |
| User interaction (UI:P) | Passive user interaction |
| Confidentiality (VC:H) | High confidentiality impact |
| Integrity (VI:H) | High integrity impact |
| Availability (VA:H) | High availability impact |
CVSS:4.0/AV:N/AC:H/AT:P/PR:H/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/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
About Project-Monai Monai
CVE-2026-100846 affects Project-Monai Monai, a product from Project-Monai. Before acting, confirm where Project-Monai Monai runs in your estate, who owns it and whether it is reachable from the internet, because exposure decides real risk more than the score alone.
What the flaw is
In plain terms: MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algo_from_pickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algo_from_pickle on an attacker-supplied pickle file, an object defining __reduce__ is executed during deserialization, resulting in arbitrary code execution in the context of the application.
The weakness class is Deserialization of Untrusted Data. The application rebuilds objects from attacker controlled data, which can run code.
Based on its CVSS vector, the flaw can be reached over the network, needs some level of access, and relies on a user taking an action. Apply the vendor fix and confirm exposure on internet facing and business critical assets first.
Affected versions and timeline
| Field | Detail |
|---|---|
| Product | Project-Monai Monai |
| Affected versions | Monai before 1.5.2 |
| Published | Sep 27, 2026 |
| Last modified | Oct 8, 2026 |
| Added to CISA KEV | Not listed |
| Assigning CNA | disclosure@vulncheck.com |
How to detect it
- Inventory every instance of Project-Monai Monai and record the running version against the affected range above.
- Check external attack surface scans for internet facing instances of the component.
- Review logs on affected systems for unusual requests, errors or new processes around the vulnerable function.
- Confirm with an authenticated vulnerability scan once your scanner has a check for this CVE.
How to fix it
- Apply the fixed version of Project-Monai Monai named in the vendor advisory.
- If patching must wait, restrict network access to the affected service and put it behind authentication or a web application firewall rule.
- Rescan after the change to prove the exposure is gone, then close the ticket.
CTEM action plan
| CTEM stage | What to do for this CVE |
|---|---|
| Scope | Add every business service that depends on Project-Monai Monai to the current CTEM cycle. |
| Discover | Find all instances, including shadow and cloud deployments, and record versions and exposure. |
| Prioritize | Rank using EPSS and CVSS together with asset exposure and business impact. |
| Validate | Confirm the flaw is reachable and exploitable in your environment and that compensating controls work. |
| Mobilize | Assign the fix to the asset owner with a due date matched to the priority, then verify closure. |
CWE References
- CWE-502: Deserialization of Untrusted Data More CVEs with this weakness
Technical References
Frequently asked questions
Related CVEs
MONAI before 1.6.0 is vulnerable to OS command injection in the nnUNetV2Runner component (monai.apps.nnunet.nnunetv2_runner). User-controlled values taken from the YAML configuration file (notably dataset_name_or_id) and from CLI/kwargs arguments are concatenated into a command string without quoting or validation and then passed to subprocess with shell=True, so shell metacharacters (e.g., ';' on Linux, '&' on Windows) are interpreted. If a victim loads and processes a crafted configuration file — for example by instantiating nnUNetV2Runner with the malicious YAML and invoking a training/validation job such as train_single_model() — arbitrary commands are executed with the privileges of the user running the job.
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