Unauthenticated SQL Injection in Listing Hub CMS

Listing Hub CMS 1.0 contains a SQL injection vulnerability that allows unauthenticated attackers to execute arbitrary SQL queries by injecting malicious code through the id parameter. Attackers can send GET requests to pages.php with crafted id values using error-based SQL injection techniques to extract database credentials, usernames, and version information.

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

Listing Hub CMS version 1.0 contains a critical SQL injection vulnerability in the pages.php file that allows unauthenticated attackers to execute arbitrary database queries. By manipulating the id parameter with specially crafted SQL payloads, attackers can bypass authentication controls and extract sensitive information including database credentials, usernames, and system version details. This vulnerability has a CVSS score of 8.2 (high severity) and affects any organization running this CMS version without patches. The lack of input validation on user-supplied parameters creates a direct pathway for attackers to interact with the underlying database, making this a severe risk for data confidentiality and potential lateral movement within affected systems.

Casky's 301 mapped skills use Claude AI with extended reasoning to detect the reconnaissance and exploitation patterns associated with this vulnerability across MITRE ATT&CK techniques TA0001 (Reconnaissance) and TA0043 (Reconnaissance). Practitioners using Casky would observe detection findings focused on anomalous GET requests to pages.php containing SQL syntax patterns in the id parameter, error-based responses revealing database structure information, and sequential queries indicating data exfiltration attempts. The platform's skill set would flag suspicious parameter encoding, unusual SQL keywords in HTTP requests, and database error messages returned to unauthenticated users—all behavioral indicators that precede successful SQL injection attacks. This approach enables teams to identify exploitation attempts before attackers achieve data extraction or establish persistence.

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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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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

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-2019-25730.

analyzing-apt-group-with-mitre-navigator

threat intelligence · low

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analyzing-campaign-attribution-evidence

threat intelligence · low

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analyzing-certificate-transparency-for-phishing

threat intelligence · low

Run

MITRE ATT&CK Techniques

TA0001 TA0043

Investigate the attack patterns behind CVE-2019-25730

Casky has 301 skills that investigate the attack patterns behind CVE-2019-25730. Run one and get CVSS-scored findings in 3 minutes.

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