GitHub Copilot and Visual Studio Code
CVE-2025-62453 — GitHub Copilot and Visual Studio Code Security Feature Bypass Vulnerability
Executive Summary
Improper validation of generative ai output in GitHub Copilot and Visual Studio Code allows an authorized attacker to bypass a security feature locally.
Overview
5
CVSS MEDIUM
Important
MS Severity
Not Exploited
MS Exploit Status
Less Likely
MS Exploit Likelihood
CVSS Vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:N/I:H/A:N/E:U/RL:O/RC:C
ATTACK VECTOR
Local
ATTACK COMPLEXITY
Low
PRIVILEGES REQUIRED
Low
USER INTERACTION
Required
SCOPE
Unchanged
CONFIDENTIALITY
None
INTEGRITY
High
AVAILABILITY
None
EXPLOIT CODE MATURITY
Unproven
REMEDIATION LEVEL
Official Fix
REPORT CONFIDENCE
Confirmed
Temporal Score: 4.4
EPSS Score
0.00419
probability of exploitation in the next 30 days
0.34781 percentile - updated 2026-08-14
View on FIRST.org
Affected Products
1 affected product
| Product | KB Article | Severity | Impact | Restart Required |
|---|---|---|---|---|
| Visual Studio Code | Release Notes (Security Update) |
Important | Security Feature Bypass | Maybe |
Patches
1 patch
| Article | Type | Restart |
|---|---|---|
Release Notes |
Security Update | Maybe |
Known Exploits
No known exploits have been linked for this CVE yet. When available, exploit references will be sourced from public repositories and may be unverified, incomplete, or non-functional. Always review code carefully before use in any environment.
Acknowledgments
Name: Lam Jun Rong Company name: NUS Greyhats URL: https://jro.sg
References
On This Page