EUVD-2026-87847
GHSA-wfpp-6gx5-h8xr
Severity by source
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/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
Local low-priv account (AV:L/PR:L); AC:H because exploitation depends on a shared/world-writable cache_dir plus a victim reading the poisoned cache; full code execution in victim context yields C/I/A:H.
Primary rating from Vendor (VulnCheck).
CVSS VectorVendor: VulnCheck
Lifecycle Timeline
4DescriptionCVE.org
In MONAI 1.6.0, PersistentDataset (monai/data/dataset.py) explicitly rejects the combination track_meta=True with weights_only=True, forcing users who cache MetaTensors (the default tensor type in MONAI >= 1.0) to run torch.load(hashfile, weights_only=False). Related cache helpers in monai/data/utils.py also call pickle.loads on cached content and derive cache keys with hashlib.md5. As a result, a local user with write access to a shared or world-writable cache_dir (e.g. /tmp/monai_cache, HPC scratch, ~/.cache/monai) can place a malicious pickle file that is deserialized the next time another user's MONAI pipeline reads the cache, resulting in arbitrary code execution in that user's context. All released versions of the monai pip package are affected; no patched version is available as of the advisory.
Articles & Coverage 1
AnalysisAI
Local code execution in MONAI 1.6.0 and all released versions allows an authenticated low-privileged local attacker to run arbitrary code as another user by writing a malicious pickle file to a shared or world-writable MONAI cache directory (e.g., /tmp/monai_cache, HPC scratch, ~/.cache/monai). The victim must subsequently run a PersistentDataset pipeline that caches MetaTensors (the default in MONAI >= 1.0), which forces torch.load(weights_only=False) and pickle.loads on the poisoned file. …
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Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata
Vulnerability AssessmentAI
| Exploitation | Requires: (1) a local account on the same host as the victim; (2) a shared or world-writable MONAI cache_dir such as /tmp/monai_cache, HPC scratch, or ~/.cache/monai that the attacker can write to; and (3) a victim subsequently running a MONAI PersistentDataset pipeline that caches MetaTensors (the default tensor type in MONAI >= 1.0), which forces torch.load(weights_only=False) and pickle.loads on the poisoned cache file. … Additional conditions and limiting factors are described in the full assessment. |
| Risk Assessment | The vendor CVSS 4.0 vector (AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H = 8.5) frames this as a local, low-privilege but high-impact code-execution flaw, and that aligns with the description: an already-authenticated local user leverages an insecure-deserialization primitive (CWE-502) to run code as a *different* user. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in. |
| Exploit Scenario | Full exploit scenario with step-by-step reproduction available after sign-in. |
| Remediation | No vendor-released patch identified at time of analysis. … Detailed patch versions, workarounds, and compensating controls in full report. |
Recommended ActionAI
Within 24 hours, inventory all MONAI deployments, confirm whether MONAI 1.6.0 or any other released version is present, locate all MONAI cache directories such as /tmp/monai_cache, HPC scratch, and ~/.cache/monai, and immediately restrict them to per-user permissions (for example 0700) or move them to private per-user paths; remove or quarantine existing cache files, especially any MetaTensor cache artifacts, and temporarily disable PersistentDataset caching or replace it with non-persistent/in-memory pipelines where operationally feasible. …
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External POC / Exploit Code
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