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HIGH

CVE-2024-27133

CVE-2024-27133 — Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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.

Published Updated Sources: cvelistV5, JFROG

Triage

Is it exploited, how likely is exploitation, what does it touch, and how severe do the scoring sources call it.

Exploitation

Unreported

no source claims exploitation

EPSS

1%

chance of exploitation in 30 days

Affects

lfprojects

mlflow

CVSS base

7.5

HIGH

CISA SSVC assessment

Three decision points CISA publishes for the CVEs it assesses · SSVC 2.0.3. A stakeholder decision, not a severity score.

CISA

Exploitation

PoC

none · proof-of-concept · active

Automatable

No

can an attacker script all four kill-chain steps

Technical impact

Partial

partial · total control of the vulnerable component

Affected scope

The catalog records vendors and products as separate lists, not pairs, so which product belongs to which vendor is not something this page can say.

Vendors (1)

Products (1)

mlflow

Every base score collected

Sources score independently and disagree; each row says who scored it and under which version.

ScoreVersionSeverityExpl.ImpactSource
7.5CVSS 3.1HIGHcvelistV5

Weakness & attack patterns

  • CWE-79

References

2 on the record

Elsewhere on this site

Not in any source we poll

Listed rather than left blank: an empty field and an unmeasured one look identical on screen, and only one is a reason to look elsewhere.

  • No confirmed IOCs, IP addresses, domains, file hashes, or malware artifacts supplied.
  • No organization-specific asset inventory, compensating-control status, or patch deployment evidence supplied.
  • No exploit packet captures, log samples, or incident case IDs supplied.