CVE-2026-32207 | Azure Machine Learning Notebook Spoofing Vulnerability

Improper neutralization of input during web page generation ('cross-site scripting') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.

Published: 2026-05-07 Last update: 2026-05-08 Assigner: [email protected] Source: [email protected]

Conclusion & alert: CVE-2026-32207 is rated Low Risk (38.4/100): CVSS High severity, with low exploitation likelihood (EPSS 0.03%). Mandatory action: Monitor for updates and reassess as exploit intelligence or EPSS changes.

Risk is dynamic; we continuously reassess and refresh what is shown on this page as upstream context changes.

Exploit prediction scoring system (EPSS) score for CVE-2026-32207

EPSS lead: Daily EPSS estimates relative likelihood of exploitation; percentile ranks this CVE among scored vulnerabilities (higher = more severe relative rank).

# Date Old EPSS score New EPSS score Delta (New - Old)
1 2026-05-22 0.05% 0.03% -0.02%
2 2026-05-13 0.05% 0.05% +0.00%
3 2026-05-09 0.05%

Full EPSS history (4 records total)

Common vulnerability scoring system (CVSS) metrics for CVE-2026-32207

CVSS metrics for this CVE.

Base score Version Severity Vector Exploitability Impact Score source
8.8 3.1 HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H Click to expand
Attack vector (AV:N)
Could be attacked over the internet or any normal routed network—not just someone sitting at the machine.
Attack complexity (AC:L)
Once they can reach the bug, pulling it off is straightforward—no weird race conditions or rare setup.
Privileges required (PR:N)
No account or special rights needed—anonymous or random user is enough.
User interaction (UI:R)
A real person has to do something—click, install, enable—otherwise it doesn’t land.
Scope (S:U)
Damage stays in the same “trust bubble” as the broken component—no big spill into unrelated systems.
Confidentiality (C:H)
Serious risk that confidential data gets exposed in a big way.
Integrity (I:H)
They could widely tamper with or forge data—trust in the data is badly hurt.
Availability (A:H)
Could take the service down hard or make it unusable for people who depend on it.
2.8 5.9 [email protected]
6.1 3.1 MEDIUM
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N Click to expand
Attack vector (AV:N)
Could be attacked over the internet or any normal routed network—not just someone sitting at the machine.
Attack complexity (AC:L)
Once they can reach the bug, pulling it off is straightforward—no weird race conditions or rare setup.
Privileges required (PR:N)
No account or special rights needed—anonymous or random user is enough.
User interaction (UI:R)
A real person has to do something—click, install, enable—otherwise it doesn’t land.
Scope (S:C)
Breaking this can reach past the original component and bite other resources—bigger blast radius.
Confidentiality (C:L)
Some sensitive info could get out, but not a total data dump.
Integrity (I:L)
Attackers could change some data, but it’s limited—not everything goes.
Availability (A:N)
Service keeps running; no real outage angle.
2.8 2.7 [email protected]

Weakness enumeration for CVE-2026-32207

GitHub Security Advisory for CVE-2026-32207

GHSA-h553-38x2-qp6q · Severity: high — Improper neutralization of input during web page generation ('cross-site scripting') in Azure...

Affected software / configurations for CVE-2026-32207

Vendor Product Version Raw CPE
microsoft azure_machine_learning cpe:2.3:a:microsoft:azure_machine_learning:-:*:*:*:*:*:*:*

References for CVE-2026-32207

cvelogic Threat Intelligence