Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:NSummary
CVE-2026-48147 is a medium-severity Incorrect Regular Expression (CWE-185) vulnerability. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 2th 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 SA-11 (Developer Testing and Evaluation) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-32606
Vulnerability Data
Budibase is an open-source low-code platform. Prior to 3.35.4, the buildMatcherRegex() / matches() functions in packages/backend-core/src/middleware/matchers.ts route patterns are compiled into unanchored regular expressions and tested against ctx.request.url, which includes the full query string. The CSRF middleware in the Budibase…
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Worker uses this matching system to decide whether to skip CSRF token validation. An unauthenticated attacker can forge state-changing cross-origin requests against any Worker API endpoint by injecting a public route pattern into the query string, causing the CSRF middleware to skip token validation entirely. This allows actions such as sending admin invites, modifying global configuration, and managing users without a valid CSRF token. This vulnerability is fixed in 3.35.4.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.3.2V3.5.1V10.2.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover regex that fails to match or compare data as intended.
Access enforcement requires verifying that state-changing requests originate from the authenticated user rather than a forged cross-site source.
Requiring documented development standards and tools reduces the chance that incorrect regular expressions are written into validation or filtering logic.
An SDLC that incorporates security can embed reviews or tooling that catch malformed regular expressions before deployment.
Protecting session authenticity prevents attackers from replaying or forging authenticated requests via the victim's browser.
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 require correct regex design, testing, and review to avoid improper matching.
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.
Security testing in development can detect regex-related flaws before release.
By denying access to phishing or malicious sites, the control lowers the likelihood that a user will be tricked into submitting a forged request that performs an unintended action on another site.
Secure development lifecycle includes validation of input-handling constructs such as regex.
Application security requirements can mandate correct regex design and testing.
Secure coding standards directly address proper construction and review of regular expressions.
Contextual intelligence about emerging CSRF toolkits can be translated into updated anti-CSRF token or same-site policy configurations across applications.