Stored XSS in Grav via Unquoted HTML Event Attributes

Grav is a file-based Web platform. Prior to 2.0.0-beta.2, a stored Cross-Site Scripting (XSS) vulnerability in getgrav/grav allows publisher-level accounts to execute arbitrary JavaScript. The issue arises from a blacklist bypass in the detectXss() function when handling unquoted HTML event attributes. This vulnerability is fixed in 2.0.0-beta.2.

Casky was already ahead

This CVE exploits attack patterns that Casky's 301matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

Grav, a file-based web platform, contains a stored Cross-Site Scripting (XSS) vulnerability affecting versions prior to 2.0.0-beta.2. The flaw exists in the detectXss() function's blacklist-based filtering, which fails to block malicious scripts when injected through unquoted HTML event attributes. Publisher-level accounts can exploit this to inject arbitrary JavaScript that executes in the browsers of other users viewing the compromised content. This is particularly dangerous because stored XSS vulnerabilities persist in the application's database, affecting all subsequent visitors and enabling account takeover, credential theft, malware distribution, and defacement. Organizations running vulnerable Grav instances with untrusted publishers face significant risk.

Casky.ai's 301 matching security skills leverage Claude's extended reasoning to detect the attack patterns mapped to MITRE ATT&CK techniques TA0001 (Initial Access) and TA0043 (Reconnaissance). Practitioners using Casky would identify findings related to HTML sanitization bypass attempts, unquoted attribute injection patterns, and stored payload persistence. The platform's skills would flag suspicious content modifications by publisher accounts, detect JavaScript execution contexts in user-controllable fields, and correlate stored XSS indicators with account privilege levels. Security teams would see detailed reconnaissance patterns showing how attackers probe for blacklist weaknesses in input validation, combined with execution technique detections revealing the delivery and activation of malicious scripts through normal user interactions—enabling rapid mitigation before widespread compromise.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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301 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-42612.

analyzing-apt-group-with-mitre-navigator

threat intelligence · low

Run

analyzing-campaign-attribution-evidence

threat intelligence · low

Run

analyzing-certificate-transparency-for-phishing

threat intelligence · low

Run

MITRE ATT&CK Techniques

TA0001 TA0043

Investigate the attack patterns behind CVE-2026-42612

Casky has 301 skills that investigate the attack patterns behind CVE-2026-42612. Run one and get CVSS-scored findings in 3 minutes.

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