GHSA-63C8-M9M2-CVR3
Vulnerability from github – Published: 2026-04-28 09:34 – Updated: 2026-05-06 19:54
VLAI
Summary
Spring AI has SQL Injection in CosmosDBVectorStore.doDelete()
Details
SQL injection vulnerability in Spring AI's CosmosDBVectorStore allows attackers to execute arbitrary SQL queries via crafted document IDs.
Affected versions: Spring AI: 1.0.0 - 1.0.5 (fixed in 1.0.6), 1.1.0 - 1.1.4 (fixed in 1.1.5).
Severity
8.8 (High)
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "org.springframework.ai:spring-ai-azure-cosmos-db-store"
},
"ranges": [
{
"events": [
{
"introduced": "1.0.0"
},
{
"fixed": "1.0.6"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.springframework.ai:spring-ai-azure-cosmos-db-store"
},
"ranges": [
{
"events": [
{
"introduced": "1.1.0"
},
{
"fixed": "1.1.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-40978"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-06T19:54:17Z",
"nvd_published_at": "2026-04-28T09:16:16Z",
"severity": "HIGH"
},
"details": "SQL injection vulnerability in Spring AI\u0027s `CosmosDBVectorStore` allows attackers to execute arbitrary SQL queries via crafted document IDs.\n\nAffected versions:\nSpring AI: 1.0.0 - 1.0.5 (fixed in 1.0.6), 1.1.0 - 1.1.4 (fixed in 1.1.5).",
"id": "GHSA-63c8-m9m2-cvr3",
"modified": "2026-05-06T19:54:17Z",
"published": "2026-04-28T09:34:13Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40978"
},
{
"type": "PACKAGE",
"url": "https://github.com/spring-projects/spring-ai"
},
{
"type": "WEB",
"url": "https://spring.io/security/cve-2026-40978"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "Spring AI has SQL Injection in CosmosDBVectorStore.doDelete()"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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