CVE-2023-22491
Published: 13 January 2023
Summary
CVE-2023-22491 is a high-severity Improper Input Validation (CWE-20) vulnerability in Gatsbyjs Gatsby. Its CVSS base score is 8.1 (High).
Operationally, ranked in the top 45.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0381
Vulnerability details
Gatsby is a free and open source framework based on React that helps developers build websites and apps. The gatsby-transformer-remark plugin prior to versions 5.25.1 and 6.3.2 passes input through to the `gray-matter` npm package, which is vulnerable to JavaScript…
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injection in its default configuration, unless input is sanitized. The vulnerability is present in gatsby-transformer-remark when passing input in data mode (querying MarkdownRemark nodes via GraphQL). Injected JavaScript executes in the context of the build server. To exploit this vulnerability untrusted/unsanitized input would need to be sourced by or added into a file processed by gatsby-transformer-remark. A patch has been introduced in `gatsby-transformer-remark@5.25.1` and `gatsby-transformer-remark@6.3.2` which mitigates the issue by disabling the `gray-matter` JavaScript Frontmatter engine. As a workaround, if an older version of `gatsby-transformer-remark` must be used, input passed into the plugin should be sanitized ahead of processing. It is encouraged for projects to upgrade to the latest major release branch for all Gatsby plugins to ensure the latest security updates and bug fixes are received in a timely manner.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.