JMP Security Notice: CVE-2026-109618 and CVE-2026-109619

JMP promptly initiated a review of its products, services, and relevant infrastructure for exposure to CVE-2026-109618 and CVE-2026-109619.

Our assessment of JMP products has not identified exposure to these vulnerabilities. Where remediation was required within supporting environments, appropriate security updates and controls have been applied and validated.
We have identified no evidence of successful exploitation or unauthorized access to JMP systems or customer information associated with these vulnerabilities.
JMP continues to monitor the issue and relevant vendor guidance. No action is required by JMP customers at this time.
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Similar to predictor screening, the idea is to get a list of columns ordered by their contribution explaining the variability within X containing missings and/or outliers.

In PCA, one can plot the partial contribution of the variables. However, this visualization does not consider the different importance between PCs. The eigenvalues table includes the percentage of data explained.

In the PLS platform, this is possible. PCA requires now multiple manual steps.

See the answer here:

https://community.jmp.com/t5/Discussions/PCA-total-variable-contribtion/m-p/338594#M58665

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JMP Security Notice: CVE-2026-109618 and CVE-2026-109619

JMP Wish List

PCA loadings (column contribution with only X's)