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CVE-2026-110306 is a URI scheme spoofing vulnerability in the fast-uri Node.js library that enables stored or reflected cross-site scripting (XSS) attacks. The flaw affects fast-uri versions before 2.4.8, 3.0.0 through 3.1.8, and 4.0.0 through 4.2.2. It was published on October 20, 2026, with the GitHub Security Advisory authored by maintainer mcollina. It carries a CVSS v3.1 base score of 6.1 (Medium) (GitHub Advisory, Red Hat CVE).
The root cause is an incorrect validation order (CWE-180) combined with an encoding error (CWE-172): fast-uri applies the legacy JavaScript unescape() function to percent-decode the URI scheme component before validating it, violating RFC 3986 §3.1 which explicitly prohibits percent-encoding in schemes. This means an input like %6Aavascript:alert(1) is decoded to javascript:alert(1) and emitted as a live, executable scheme. Additionally, the equal() comparison function treats percent-encoded and plain schemes as equivalent, allowing attackers to bypass equality-based scheme allowlists. Concrete examples include: normalize('%6Aavascript:alert(1)') returning javascript:alert(1), and equal('%68ttp://a/', 'http://a/') returning true (GitHub Advisory).
An unauthenticated attacker who can supply URI input to an application using fast-uri can craft a percent-encoded scheme (e.g., %6Aavascript:, %64ata:, or vbscript: variants) that passes raw-input scheme screening but is normalized into an executable URL. When the application stores or renders the normalized result in a browser, this produces stored or reflected XSS, enabling session hijacking, credential theft, or malicious script execution in the victim's browser context. Availability is not impacted, but both confidentiality and integrity are affected at a low-to-moderate level with a changed scope (GitHub Advisory, Red Hat CVE).
As of the disclosure date, there is no public proof-of-concept exploit code and no evidence of in-the-wild exploitation (Red Hat CVE). The EPSS score is reported at 0.0, indicating very low current exploitation probability. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. No threat actor attribution has been reported.
%6Aavascript:alert(document.cookie) (where %6A decodes to j) or using the %uXXXX form: %u006Aavascript:alert(1).javascript:.normalize() or resolve() function, which internally calls unescape() on the scheme before validation, converting the encoded scheme to javascript:alert(document.cookie) and emitting it as a live scheme.javascript: URL executes, delivering the XSS payload and potentially stealing session tokens or performing actions on behalf of the victim (GitHub Advisory).%6Aavascript:, %64ata:, %u006A) submitted to application endpoints that accept URL input.% characters in the scheme portion of submitted URIs (before the first :); repeated submissions with variations of encoded javascript, data, or vbscript strings.javascript:, data:, or vbscript: URIs that were not present in raw user input — indicating normalization has occurred on encoded input.javascript: scheme URLs on trusted domains.Upgrade fast-uri to one of the patched versions: 2.4.8, 3.1.9, or 4.2.3 (or any later release). If an immediate upgrade is not possible, apply one of two workarounds: (1) reject any URI input whose scheme component (the substring before the first :, /, ?, or #) contains a % character; or (2) validate parse(input).scheme against an allowlist after normalization and use the parsed result rather than the raw input string for all downstream operations (GitHub Advisory).
The advisory was published by fast-uri maintainer mcollina on GitHub, with UlisesGascon credited as a remediation reviewer (GitHub Advisory). Red Hat tracked the issue via Bugzilla (Bug #2556005) and published a CVE advisory page, indicating downstream awareness in enterprise Linux distributions (Red Hat CVE). No significant broader media coverage or notable social media commentary has been identified at this time.
Fix availability across major Linux distributions and their releases.
Source: This report was generated using AI
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