Cyber Resilience

CVE-2025-36132

XSS in Ibm Planning Analytics Local 2.0.0 – 2.0.106

Published
30 September 2025
Modified
03 October 2025
Patch / advisory
CVSS Score v3.1 5.4
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N
EPSS Score 0.0018 7th percentile
Risk Priority 35 floored blend · peak EPSS

Summary

CVE-2025-36132 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Ibm Planning Analytics Local. Its CVSS base score is 5.4 (Medium).

Operationally, ranked at the 7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

IBM Planning Analytics Local 2.0.0 through 2.0.106 and 2.1.0 through 2.1.13 is vulnerable to cross-site scripting. This vulnerability allows an authenticated user to embed arbitrary JavaScript code in the Web UI thus altering the intended functionality potentially leading to credentials…

more

disclosure within a trusted session.

CWE(s)

Related Threats

CVEs Like This One

CVE-2023-28520Same product: Ibm Planning Analytics Local
CVE-2023-28530Same vendor: Ibm
CVE-2023-32332Same vendor: Ibm
CVE-2023-32339Same vendor: Ibm
CVE-2023-43057Same vendor: Ibm
CVE-2023-22860Same vendor: Ibm
CVE-2023-26270Same vendor: Ibm
CVE-2023-30436Same vendor: Ibm
CVE-2023-24957Same vendor: Ibm
CVE-2023-30435Same vendor: Ibm

Affected Assets

ibm
planning analytics local
2.0.0 — 2.0.106 · 2.1.0 — 2.1.13

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)
  • SI-10 Information Input Validation
  • SI-15 Information Output Filtering
  • AC-4 Information Flow Enforcement
Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.3.2

Mitigating Controls (NIST 800-53 r5) AI

prevent

Directly requires validation of all user-supplied input before it is rendered in the Web UI, blocking the arbitrary JavaScript that the authenticated attacker embeds to trigger this XSS.

prevent

Requires filtering/sanitization of information returned to users, preventing the malicious script from being executed in the browser and thereby stopping credential disclosure.

prevent

Enforces information-flow rules on data leaving the application, limiting the ability of injected script to exfiltrate session tokens or other sensitive values.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).

PR.PS-02 partial match
prevents

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

detects

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

prevents

Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.

prevents

Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.

prevents

Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.

none

Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.

References