Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-84390 is a critical-severity Inclusion of Sensitive Information in Source Code (CWE-540) vulnerability. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Information Repositories (T1213); ranked at the 43th 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 AC-3 (Access Enforcement) and SA-11 (Developer Testing and Evaluation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-76098
Vulnerability Data
A inclusion of sensitive information in source code vulnerability in Fortinet FortiMonitorOnSight 7.2.4 through 7.2.7, FortiMonitorOnSight 7.2.0 through 7.2.2 may allow attacker to improper access control via <insert attack vector here>
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Enforces access so that source containing embedded secrets cannot be reached by unauthorized parties.
Developer testing and static analysis locate hard-coded sensitive values before code is deployed.
Engineering principles require secrets to be externalized rather than embedded in source.
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.
Secure SDLC practices directly prohibit embedding secrets or sensitive data in source code.
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.
Classification helps identify source code containing sensitive data so it can be protected.
Access control limits who can view or retrieve source code that may contain secrets.
Secure SDLC practices include removing secrets from code before commit or deployment.
Secure coding standards explicitly prohibit hard-coding credentials or sensitive data.
Environment separation reduces risk of accidental exposure but does not address secrets already in code.
Directly restricts access to source code, preventing exposure of embedded sensitive information.