CVE-2026-22743
Cypher Injection in Spring AI Neo4j Store Enables Data Manipulation
Publication date: 2026-03-27
Last updated on: 2026-04-16
Assigner: VMware
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| vmware | spring_ai | From 1.0.0 (inc) to 1.0.5 (exc) |
| vmware | spring_ai | From 1.1.0 (inc) to 1.1.4 (exc) |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-89 | The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
CVE-2026-22743 is a Cypher injection vulnerability in the spring-ai-neo4j-store component of Spring AI, specifically in the Neo4jVectorFilterExpressionConverter class.
When a user-controlled string is passed as a filter expression key, the method doKey() embeds this key into a backtick-delimited Cypher property accessor (like node.`metadata.`) after removing only double quotes, but it does not escape embedded backticks.
This improper sanitization allows an attacker to perform Cypher injection, which can lead to Server-Side Request Forgery (SSRF) attacks.
How can this vulnerability impact me? :
This vulnerability can allow an attacker to perform Cypher injection attacks, potentially leading to Server-Side Request Forgery (SSRF).
An SSRF attack can enable an attacker to make unauthorized requests from the server, potentially accessing internal systems or sensitive data.
The CVSS base score of 7.5 indicates a high severity with network attack vector, low attack complexity, no privileges required, and no user interaction needed, with high confidentiality impact.
What immediate steps should I take to mitigate this vulnerability?
The primary mitigation step is to upgrade the affected spring-ai-neo4j-store component to a fixed version.
- For Spring AI 1.0.x series, upgrade to version 1.0.5.
- For Spring AI 1.1.x series, upgrade to version 1.1.4.
No additional mitigation steps are required beyond upgrading.