Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessPublish malicious bundle to model zoo/HF/NGC
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DeliveryVictim loads bundle via monai.bundle.load/run
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ExploitConfigWorkflow.__init__ passes logging.conf to fileConfig
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Executioneval() of handler class= field
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ImpactArbitrary code execution as victim user
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Code injection prevention, sandbox exec
MITRE ATT&CK
2 techniques across 2 tactics: Execution, Initial Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires the victim to obtain and load an attacker-controlled MONAI bundle through any entrypoint that constructs a workflow - monai.bundle.load() (the 'load weights' verb), monai.bundle.run(), run_workflow(), create_workflow(), or direct ConfigWorkflow(config_file=...) - and the bundle must contain a configs/logging.conf file. No special non-default configuration is needed: ConfigWorkflow.__init__ defaults logging_file to the bundle's own configs/logging.conf and calls logging.config.fileConfig() on it with no trust check, so the default behavior is vulnerable whenever that file is present; the payload fires at object construction, before initialize() or run(), and independently of any MONAI $-expression in the main config. The principal limiting factor is user interaction (CVSS UI:A): the attacker cannot reach a target that never loads their bundle, making this a supply-chain/social-engineering vector rather than direct remote exploitation; no authentication is required of the victim (PR:N) and code runs with the loading user's privileges. Setting logging_file=False disables the fileConfig call per the code. |
| Impact | This is a genuine high-priority issue rather than a CVSS-inflated one, though its real-world reach is gated by user interaction. The supplied CVSS 4.0 vector (AV:N/AC:L/AT:N/PR:N/UI:A, VC:H/VI:H/VA:H, score 8.6) describes a network-reachable, low-complexity, unauthenticated flaw with full confidentiality/integrity/availability impact, but the UI:A (Active user interaction) metric is decisive: exploitation requires a victim to deliberately load or run an attacker-published MONAI bundle, so this is a supply-chain social-engineering vector, not a wormable remote service bug. Exploit maturity is strong: the GHSA advisory ships a complete working PoC and reports a successful dynamic reproduction (ATTACKER_CODE_RAN: True, live id -u/whoami output), so publicly available exploit code exists and is confirmed functional. The vuln.today decision label is this_week. Two signals are absent: no EPSS score is provided in the input, and there is no CISA KEV listing, so there is no evidence of active in-the-wild exploitation despite the confirmed PoC - the current risk is 'proven-exploitable, not yet observed exploited.' The signals are internally consistent (network/low-complexity delivery, user-interaction gate, confirmed code execution); the main caveat is that 'network' reach depends entirely on the victim fetching an untrusted bundle. |
| Exploit ScenarioDerived | An attacker publishes a MONAI bundle (e.g. 'coolseg') to a widely-trusted channel such as the model zoo, Hugging Face, or NGC, with a benign-looking train.json and weights but a malicious configs/logging.conf. A researcher or inference service calls monai.bundle.load()/run() on it; during ConfigWorkflow.__init__ the logging.conf is passed to logging.config.fileConfig(), which eval()s the handler class= field and runs the attacker's Python as the victim user. A confirmed working PoC and successful dynamic reproduction are documented in the GHSA advisory. |
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Alert meAnalysisAIv1 – Oct 28, 2026
Remote code execution in MONAI's bundle workflow loader (versions 1.2.0 through 1.6.0, fixed in 1.6.1) lets an attacker who publishes a malicious model bundle run arbitrary Python in the context of anyone who loads or runs it. Because ConfigWorkflow.__init__ defaults to the bundle's own configs/logging.conf and hands it to logging.config.fileConfig() without any trust check, a crafted INI handler section executes at object construction - before initialize() or run() - and independently of any MONAI $-expression in the main config, so a bundle with a completely benign train.json still triggers it. Exploitation is gated by user interaction: the victim must fetch and load the attacker's bundle via monai.bundle.load(), monai.bundle.run(), run_workflow(), create_workflow(), or a direct ConfigWorkflow(config_file=...), making this primarily a supply-chain/social-engineering vector against researchers and inference services rather than direct remote exploitation; a public proof-of-concept with dynamic reproduction is published in the upstream advisory, and the issue is prioritized for remediation this week.
RemediationAI
Vendor-released patch: MONAI 1.6.1. Upgrade the monai package to 1.6.1 or later (pip install --upgrade 'monai>=1.6.1') per advisory https://github.com/Project-MONAI/MONAI/security/advisories/GHSA-wvpx-5qmp-46g3. Where upgrading cannot be done immediately, pass logging_file=False to the workflow so ConfigWorkflow skips the logging.config.fileConfig() call entirely - the trade-off is that the bundle's own logging configuration is then not applied and logging falls back to defaults, and any code paths that construct workflows implicitly through monai.bundle.load()/run() would need to be wrapped or patched to supply that argument. Additionally, treat bundles as code: inspect or strip configs/logging.conf from any third-party bundle before loading it, and restrict loading to bundles from trusted, verified publishers (model zoo, NGC, vetted Hugging Face repos) until the upgrade is applied; the upstream advisory notes that remediating the fileConfig call is the complete fix, so review-before-load should be considered an interim control rather than a substitute for patching.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
MONAI bundles package a model's weights alongside JSON configuration that MONAI's workflow machinery interprets, and they are distributed widely through the MONAI model zoo, Hugging Face, and NGC. The root cause is CWE-94 (improper control of generation of code): monai/bundle/workflows.py sets logging_file to <bundle>/configs/logging.conf by default and, when that path exists, calls logging.config.fileConfig() with no validation. Python's fileConfig resolves the class= and args= fields of each INI handler section using eval(), so an attacker-supplied handler class expression such as a tuple-indexing trick around __import__('os').system(...) is executed as Python the moment the workflow object is constructed. This is a distinct primitive from the separately reported MONAI $-expression / _target_ RCE: the payload lives in a plain INI file rather than the MONAI $-DSL, so it evades the review heuristic of checking bundles for $ expressions, and it fires at construction time rather than at initialize(). The affected distribution is the PyPI package pypi/monai, vulnerable from 1.2.0 up to (but not including) 1.6.1. The assessed vector is CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - no victim authentication is needed and code runs with the loading user's privileges, but the attacker cannot reach a target that never loads their bundle.
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Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
Bundle is fetched over the network (AV:N) with no auth (PR:N) and reliable triggering (AC:L), but a victim must load the untrusted bundle (UI:R); full code execution yields C:H/I:H/A:H.
Primary rating from Vendor (vulncheck).
CVSS VectorVendor: vulncheck
Lifecycle Timeline
2DescriptionCVE.org
MONAI from 1.2.0 before 1.6.1 contains a remote code execution vulnerability in ConfigWorkflow.__init__, which passes a bundle's configs/logging.conf to logging.config.fileConfig that eval()s handler class and args fields. Attackers can publish a malicious bundle whose logging.conf runs arbitrary Python at workflow construction when a victim loads or runs the bundle.
Technical POC Analysis
Tracking note: the supplied upstream advisory (GHSA-wvpx-5qmp-46g3) scores this 8.8 and says "No known CVE" at publication; the CVE ID and 8.6 score come from the tracking entry.
Full technical POC analysis - root cause, step-by-step exploitation and patch breakdown - is part of the Pro and Business plans.
Executive ViewAI
A high-severity vulnerability in MONAI's bundle workflow loader allows arbitrary code execution when users load malicious model bundles, primarily affecting AI researchers and inference services that use third-party bundles. Leadership should care because this supply-chain risk can compromise intellectual property and research integrity, requiring immediate user awareness and changes to bundle verification processes.
No vendor-released patch identified at time of analysis. Interim mitigations include: only load bundles from trusted sources; review bundle configuration files (especially logging.conf) before loading; run bundles in isolated environments (e.g., containers, sandboxes) with minimal privileges; monitor for suspicious Python process activity during bundle loading.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
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