SQL Injection in Hospital Bed Management Login Form

A vulnerability was found in code-projects Hospital Bed Management System 1.0. This affects an unknown part of the component Login Form. Performing a manipulation of the argument Username results in sql injection. Remote exploitation of the attack is possible. The exploit has been made public and could be used.

Casky was already ahead

This CVE exploits attack patterns that Casky's 322matched 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

CVE-2026-16014 represents a critical authentication bypass vulnerability affecting Hospital Bed Management System 1.0, where attackers can manipulate the Username parameter in the login form to inject arbitrary SQL commands. With a CVSS score of 7.3 and confirmed public exploit availability, this vulnerability poses an immediate risk to healthcare organizations relying on this system for bed allocation and patient management. The attack surface is particularly dangerous because it targets the authentication layer—typically the first line of defense—allowing unauthenticated remote attackers to potentially access patient records, modify bed assignments, or compromise system integrity without valid credentials.

Casky's 322 matching skills leverage Claude AI's extended reasoning to detect the attack patterns underlying this vulnerability across TA0001 (Initial Access) and TA0043 (Reconnaissance) techniques. Practitioners using the platform would observe detection signals for SQL injection attempts through input validation bypass patterns, malformed SQL syntax in authentication logs, and anomalous database query structures originating from the login component. The skill mapping identifies how attackers probe the Username field with SQL metacharacters (single quotes, UNION operators, comment sequences) to break out of intended query logic. When analyzing findings, practitioners would see correlations between suspicious login attempts containing SQL keywords and subsequent unauthorized database access—enabling them to prioritize patch deployment for this publicly exploited vulnerability before attackers establish persistent access to healthcare systems.

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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 →

322 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-16014.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

Run

abusing-dpapi-for-credential-access

red teaming · high

Run

abusing-shadow-credentials-for-privesc

red teaming · high

Run

MITRE ATT&CK Techniques

TA0001 TA0043

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