Security Digest · Vulnerability record

CVE-2024-27133: MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution

Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

CVSS 7.5 High EPSS 0.7% · p51

Should you act?

Normal patch cycle

No exploitation signal; fix it in your next routine update if you are affected. This signal is computed from CISA KEV, EPSS and CVSS data; it is not an editorial verdict.

  • Not in CISA KEV, but CISA’s SSVC assessment records a public proof-of-concept, so attack code exists.
  • EPSS 0.7%, percentile 51: FIRST’s model estimates a 0.7% chance of exploitation activity in the next 30 days, higher than 51% of all scored CVEs (moderate). EPSS is a probability, not a verdict.
  • Needs a user to click or open something. Phishing makes that realistic, but it is not wormable.
  • Only applies if your dependency tree includes mlflow (PyPI) < 2.10.0, fixed in 2.10.0. Check your lockfile, including transitive dependencies.

What it is

Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over dataset table fields.

From the GitHub advisory

Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over dataset table fields.

Weakness type: CWE-79.

Product: mlflow (PyPI) · Assigned by: JFROG · Published: 2024-02-23

Affected and fixed versions

EcosystemPackageVulnerableFirst fixed
PyPImlflow< 2.10.02.10.0
VendorProductAffected versions (per CVE record)
mlflow<= 2.9.2

Severity scores

Scored byCVSSScoreVector
JFROG3.17.5 HighCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
GitHub3.19.6 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
  • Attack vector: network (remotely reachable)
  • Attack complexity: high (needs special conditions)
  • Privileges required: none (no login)
  • User interaction: required (a user must click/open something)
  • Scope: unchanged

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 poc, automatable no, technical impact partial.
  • FIRST EPSS (model of 2026-10-21): 0.66% probability of exploitation activity in the next 30 days; percentile 51.

Timeline

  • — CVE record published by JFROG
  • — GitHub-reviewed advisory GHSA-3v79-q7ph-j75h published (critical)
  • — CVE record last updated

Sources and references

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

Vulnerability records

  1. GitHub Advisory GHSA-3v79-q7ph-j75h github.com
  2. CVE.org record CVE-2024-27133 cve.org
  3. NVD entry CVE-2024-27133 nvd.nist.gov

Other references from the CVE record and advisory

  1. research.jfrog.com research.jfrog.com
  2. github.com github.com
  3. github.com github.com
  4. github.com github.com
  5. github.com github.com

Critical PyPI advisories · Today’s Security Digest