CVE-2025-48938
Cli Go-Gh ≤ 2.12.1
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H/E:U/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-48938 is a low-severity Trust Boundary Violation (CWE-501) vulnerability in Cli Go-Gh. Its CVSS base score is 2.6 (Low).
Operationally, ranked at the 38th 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-4 (Information Flow Enforcement) and AC-16 (Security and Privacy Attributes) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-16493
Vulnerability Data
go-gh is a collection of Go modules to make authoring GitHub CLI extensions easier. A security vulnerability has been identified in versions prior to 2.12.1 where an attacker-controlled GitHub Enterprise Server could result in executing arbitrary commands on a user's…
more
machine by replacing HTTP URLs provided by GitHub with local file paths for browsing. In `2.12.1`, `Browser.Browse()` has been enhanced to allow and disallow a variety of scenarios to avoid opening or executing files on the filesystem without unduly impacting HTTP URLs. No known workarounds are available other than upgrading.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement directly stops trusted and untrusted data from being combined by applying rules that govern allowable data movements and combinations.
Associating explicit security attributes with data objects enables enforcement mechanisms that keep trust levels from being mixed inside structures.
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-development practices (coding standards, reviews, validation) directly prevent mixing trusted and untrusted data inside the same structures.
Documented data-flow representations make trust boundaries explicit and help surface mixing of trusted/untrusted data.
Logical segmentation and access controls enforce separation between trust domains, reducing the chance of co-mingled data structures.
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.
Secure architecture principles require explicit trust zones and data segregation, mitigating mixing of trusted/untrusted data.
Secure coding standards can enforce input validation and data tagging, but do not guarantee architectural separation.
Secure development lifecycle mandates separation of trusted and untrusted data flows, directly preventing mixing in the same structure.
Application security requirements include explicit trust-boundary definitions and data classification at interfaces.
Network segregation reduces external mixing but does not address internal data-structure trust violations.
Information access restriction limits who sees data but does not prevent mixing trusted and untrusted data within structures.