CVE-2026-41705
Filter Expression Injection in Spring AI MilvusVectorStore
Publication date: 2026-05-09
Last updated on: 2026-05-09
Assigner: VMware
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| spring_ai | spring_ai | From 1.0.0 (inc) to 1.0.x (inc) |
| spring_ai | spring_ai | From 1.1.0 (inc) to 1.1.x (inc) |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-917 | The product constructs all or part of an expression language (EL) statement in a framework such as a Java Server Page (JSP) using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended EL statement before it is executed. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
Spring AI's MilvusVectorStore#doDelete(List) implementation is vulnerable to filter-expression injection due to unsanitized document IDs.
This means that the method does not properly sanitize input document IDs, allowing an attacker to inject malicious filter expressions.
How can this vulnerability impact me? :
This vulnerability could allow an attacker to perform data destruction by exploiting the filter-expression injection.
What immediate steps should I take to mitigate this vulnerability?
The immediate step to mitigate this vulnerability is to upgrade Spring AI to a fixed version.
- Upgrade Spring AI 1.0.x versions to 1.0.7 or greater.
- Upgrade Spring AI 1.1.x versions to 1.1.6 or greater.
No additional mitigation steps are required beyond upgrading.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The vulnerability in Spring AI's MilvusVectorStore#doDelete(List) allows filter-expression injection via unsanitized document IDs, potentially leading to data destruction.
Such unauthorized data destruction could impact compliance with data protection regulations like GDPR and HIPAA, which require the integrity and availability of personal and sensitive data to be maintained.
Failure to protect data against such vulnerabilities may result in violations of these standards, leading to legal and regulatory consequences.
Mitigation involves upgrading to fixed versions 1.0.7 or 1.1.6 or greater.