CVE-2026-22730 is a critical SQL injection vulnerability affecting VMware's Spring AI component, specifically within the MariaDBFilterExpressionConverter. This vulnerability allows attackers to bypass metadata-based access controls and execute arbitrary SQL commands, which can lead to unauthorized data access and potential data breaches. Given its CVSS score of 8.8, it falls into the high-severity category, indicating a serious risk to affected systems.
The vulnerability arises from inadequate input sanitization, making it susceptible to exploitation over a network with low attack complexity and requiring only low privileges. Attackers may leverage this vulnerability to manipulate the database directly, resulting in significant confidentiality, integrity, and availability impacts.
Organizations using affected versions of Spring AI should prioritize patching immediately to mitigate risks. The exploitability score of 2.8 indicates that while no public exploit is confirmed yet, the potential for exploitation remains high.
Given the severity of this vulnerability and its implications, security teams must act swiftly. The lack of interaction needed for an attack makes this vulnerability particularly dangerous, emphasizing the urgency of remediation efforts.
Vulnerability Details
The official description of CVE-2026-22730 is as follows: 'A critical SQL injection vulnerability in Spring AI's MariaDBFilterExpressionConverter allows attackers to bypass metadata-based access controls and execute arbitrary SQL commands. The vulnerability exists due to missing input sanitization.'
This vulnerability has been classified under CWE-89, indicating its nature as a SQL injection flaw. The CVSS score of 8.8 reflects its high severity, and the vulnerability affects all versions of the Spring AI component between 1.0.0 and 1.0.4, as well as 1.1.0 and 1.1.3.
Technical Analysis
The root cause of CVE-2026-22730 is the absence of proper input sanitization within the MariaDBFilterExpressionConverter. This oversight enables attackers to craft malicious SQL queries that can manipulate the underlying database. The attack vector is network-based, allowing remote exploitation of vulnerable systems.
The attack complexity is classified as low, which means that an attacker does not need advanced skills to exploit this vulnerability. Privileges required for exploitation are low, as users with minimal privileges can trigger the vulnerability without any user interaction.
If successfully exploited, the attacker can achieve high impacts on confidentiality, integrity, and availability, undermining the overall security posture of the affected systems.
Risk & Impact Analysis
Risk to organizations includes unauthorized access to sensitive data, potential data loss, and significant operational disruptions. Given that the vulnerability affects widely used components in web applications, the blast radius could be substantial, impacting multiple applications leveraging the Spring AI framework.
Organizations should assess their exposure and prioritize patching as part of their immediate risk management strategy. The fact that this vulnerability is not included in the KEV catalog does not diminish its potential impact; on the contrary, it emphasizes the need for proactive defenses.
The EPSS score indicates a very low likelihood of exploitation in the wild at this moment. However, organizations should not become complacent, as the nature of SQL injection vulnerabilities often leads to rapid adoption by attackers once discovered.
Exploitation Status
Signal | Status |
|---|---|
Known Exploit | Yes |
Public PoC | Yes |
Actively Exploited | No |
Ransomware Use | No |
Affected Versions
The affected versions of the Spring AI component include all versions from 1.0.0 to 1.0.4, and from 1.1.0 to 1.1.3. Organizations using these versions should apply the necessary patches as soon as they are available.
Mitigation & Remediation
Organizations must ensure that they update to the latest patched versions of Spring AI to protect against this SQL injection vulnerability. If patches are unavailable, implement input validation checks and employ network security measures to limit exposure.
For a thorough security assessment, organizations can consider engaging in penetration testing to identify similar vulnerabilities.
Detection Guidance
Organizations should monitor logs for unusual database queries that may indicate exploitation attempts. Behavioral anomalies, such as unexpected changes to database content or unauthorized access attempts, should also be investigated.
Network signatures that detect SQL injection patterns can help in identifying potential attacks before they escalate.
AppSecure Threat Intelligence Insight
This vulnerability highlights the ongoing need for stringent input validation within application development. As SQL injection remains one of the most common attack vectors, organizations must remain vigilant and proactive in their security efforts.
For organizations utilizing Spring AI, comprehensive security assessments can provide insights into potential weaknesses, allowing for better risk management. Security teams should stay informed about emerging threats and vulnerabilities in their technology stack.
For further reading on application security practices, consider exploring our resource on penetration testing methodology and how it can enhance your security posture.
Security teams may also benefit from reviewing the latest trends in vulnerability management programs to better prepare for future threats.
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
.webp)