Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAuthenticate to Spring AI application
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DeliverySubmit crafted filter expression to MariaDBFilterExpressionConverter
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ExploitInject malicious SQL via unsanitized input
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ExecutionBypass metadata access controls
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PersistExecute arbitrary SQL commands
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ImpactExtract or modify sensitive database records
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Parameterized queries, prepared statements
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Persistence The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Requires authenticated user access to Spring AI applications using MariaDBFilterExpressionConverter for metadata filtering. Attacker must have PR:L privileges to inject malicious SQL through filter expressions. No victim interaction needed. Affects default Spring AI deployments with MariaDB backend. |
| Impact | This vulnerability presents significant real-world risk due to multiple converging factors from the CVSS vector analysis. The attack vector is network-based (AV:N) with low complexity (AC:L), requiring only low privileges (PR:L) and no user interaction (UI:N), making it highly accessible to authenticated attackers. The impact is severe across all CIA triad dimensions (C:H/I:H/A:H), enabling complete database compromise. While EPSS probability data is not provided in the intelligence, the combination of low attack complexity, network accessibility, and critical impact typically correlates with elevated exploitation likelihood. No KEV listing is mentioned, suggesting no confirmed active exploitation in the wild yet, and no public POC is explicitly referenced. However, SQL injection vulnerabilities are well-understood and easily exploitable once discovered, making this automatable and likely to be weaponized rapidly. The SSVC framework would likely classify this as requiring urgent remediation due to the technical impact (total system compromise possible), low exploitation barrier, and broad attack surface in internet-facing Java applications using Spring AI with MariaDB backends. |
| Exploit ScenarioDerived | An authenticated attacker with low-level credentials to a Spring AI application crafts a malicious metadata filter expression containing SQL injection payloads when querying the MariaDB vector database. Because the MariaDBFilterExpressionConverter fails to sanitize this input, the attacker's injected SQL commands execute with the privileges of the application's database user, allowing them to bypass intended access controls, extract sensitive data from other users' records, modify or delete database contents, or potentially escalate to operating system command execution depending on database configuration. Given the network-accessible attack vector and low complexity, this can be performed remotely without user interaction once the attacker has obtained valid application credentials. |
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Alert meAnalysisAIv1 – Mar 18, 2026
A critical SQL injection vulnerability in Spring AI's MariaDBFilterExpressionConverter component allows authenticated attackers to bypass metadata-based access controls and execute arbitrary SQL commands due to missing input sanitization. VMware Spring AI versions 1.0.x prior to 1.0.4 and 1.1.x prior to 1.1.3 are affected. With a CVSS score of 8.8, this vulnerability enables attackers with low-level privileges to compromise confidentiality, integrity, and availability of the database system through network-based attacks with low complexity.
RemediationAI
Immediately upgrade VMware Spring AI to version 1.0.4 or later for the 1.0.x branch, or to version 1.1.3 or later for the 1.1.x branch as detailed in the official VMware Spring security advisory at https://spring.io/security/cve-2026-22730. Review all application code utilizing MariaDBFilterExpressionConverter to identify potential attack surfaces where user-controlled input influences filter expressions. Until patching is completed, implement defense-in-depth measures including strict input validation at the application layer using allowlists for filter expression parameters, enforce principle of least privilege for database accounts used by Spring AI applications to limit blast radius of SQL injection attacks, deploy web application firewall (WAF) rules to detect and block SQL injection patterns, and monitor database query logs for suspicious activity or anomalous SQL commands that might indicate exploitation attempts. Consult the EUVD advisory at https://nvd.nist.gov/vuln/detail/CVE-2026-22730 for additional technical details and the VulDB entry at https://vuldb.com/?id.351507 for community-contributed indicators of compromise.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 2 packages in maven, euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
Spring AI is VMware's framework for building AI applications in Java, and this vulnerability affects its MariaDB integration component specifically within the MariaDBFilterExpressionConverter class (CPE: cpe:2.3:a:vmware:spring_ai:*:*:*:*:*:*:*:*). The vulnerability stems from improper neutralization of special elements used in SQL commands, a classic SQL injection flaw. The MariaDBFilterExpressionConverter is responsible for converting filter expressions into SQL queries when working with vector databases and metadata filtering, but fails to properly sanitize user-supplied input before incorporating it into SQL statements. This allows specially crafted filter expressions to break out of their intended context and inject arbitrary SQL code, bypassing the metadata-based access control mechanisms that rely on these filters to enforce data isolation and security policies.
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
Lifecycle Timeline
2DescriptionCVE.org
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.
Executive ViewAI
A high-severity SQL injection vulnerability in Spring AI's MariaDB component allows attackers to bypass access controls and execute unauthorized database commands, potentially compromising sensitive data and system integrity. Organizations using Spring AI with MariaDB databases face immediate risk of data breach and unauthorized access if exploited.
Disable Spring AI's MariaDB filter expression converter functionality until patch availability; implement Web Application Firewall (WAF) rules to block SQL injection payloads; restrict database network access through network segmentation and firewall rules; enable database query auditing and real-time alerting for anomalous SQL patterns; apply principle of least privilege to database service accounts; implement API rate limiting on Spring AI endpoints; monitor vendor security advisories for patch release.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
SQL injection exploits the way applications construct database queries by mixing user input directly into SQL statements.
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