CVE-2026-47117: OpenMed vulnerable to remote code injection through privacy-filter model loading path

Should you act?

Critical and remotely reachable

No known exploitation yet, but it is network-reachable without credentials. This signal is computed from CISA KEV, EPSS and CVSS data; it is not an editorial verdict.

• No confirmed exploitation. It is not in CISA’s KEV catalog and CISA’s SSVC assessment records no known exploitation. That can change quickly after a public write-up; re-check if you are affected.
• EPSS 1.3%, percentile 70: FIRST’s model estimates a 1.3% chance of exploitation activity in the next 30 days, higher than 70% of all scored CVEs (moderate). EPSS is a probability, not a verdict.
• Remotely reachable with no login and no user interaction. If the vulnerable service is exposed to the internet, prioritize it.
• Only applies if your dependency tree includes openmed (PyPI) < 1.5.2, fixed in 1.5.2. Check your lockfile, including transitive dependencies.

What it is

OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied modelname parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path that loads Hugging Face models with trustremotecode=True. An unauthenticated attacker can supply a malicious model repository containing custom Transformers code via automap in config.json or tokenizerconfig.json, which is imported and executed with the privileges of the OpenMed service process.

From the GitHub advisory

OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied modelname parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path that loads Hugging Face models with trustremotecode=True. An unauthenticated attacker can supply a malicious model repository containing custom Transformers code via automap in config.json or tokenizerconfig.json, which is imported and executed with the privileges of the OpenMed service process.

Weakness type: CWE-94.

Product: openmed (PyPI) · Assigned by: VulnCheck · Published: 2026-06-02

Affected and fixed versions

Severity scores

• Attack vector: network (remotely reachable)
• Attack complexity: low
• Attack requirements: none
• Privileges required: none (no login)
• User interaction: none

CVSS measures how bad a flaw is if exploited, not how likely exploitation is. Read it next to the exploitation data below.

Exploitation and urgency

• CISA KEV: not listed (no confirmed in-the-wild exploitation known to CISA).
• CISA SSVC assessment: exploitation none, automatable yes, technical impact total.
• FIRST EPSS (model of 2026-10-21): 1.29% probability of exploitation activity in the next 30 days; percentile 70.

Timeline

• 2026-06-02 — CVE record published by VulnCheck
• 2026-06-02 — GitHub-reviewed advisory GHSA-m3v4-v5gx-7wf5 published (critical)
• 2026-10-08 — CVE record last updated

Sources and references

Original sources first. Version and fix details should always be confirmed against the vendor or project advisory.

Vendor and project advisories, patches

1. Release Notes github.com
2. Patch Commit github.com

Vulnerability records

1. GitHub Advisory GHSA-m3v4-v5gx-7wf5 github.com
2. CVE.org record CVE-2026-47117 cve.org
3. NVD entry CVE-2026-47117 nvd.nist.gov

Other references from the CVE record and advisory

1. Researcher Disclosure github.com
2. Pull Request github.com
3. vulncheck.com vulncheck.com

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