Security readout for executives and security teams
Plain-English summary
Spring AI can build unsafe Redis search filters when an application places user-controlled text into a TAG filter. An attacker may be able to change the intended search filter and read data they should not see. The published CVSS impact is confidentiality-only, rated high.
Executive priority
Treat this as a high-priority confidentiality issue for affected Spring AI search features, especially customer-facing systems. Patch during the next urgent maintenance window if untrusted search filters are used.
Technical view
CVE-2026-22744 affects spring-ai-redis-store. RedisFilterExpressionConverter.stringValue() places TAG filter values directly into @field:{VALUE} RediSearch syntax without escaping. Affected Spring AI ranges are 1.0.0 before 1.0.5 and 1.1.0 before 1.1.4. CWE-74 and CVSS 7.5 indicate network-reachable injection with high confidentiality impact.
Likely exposure
Exposure is most likely in Spring AI applications using spring-ai-redis-store where user-controlled strings become TAG field filter values for Redis-backed searches.
Exploitation context
The source bundle marks KEV as false and provides no cited evidence of active exploitation. The risk depends on application data flow: the vulnerable path requires untrusted input reaching TAG filter construction.
Researcher notes
Focus review on RedisFilterExpressionConverter TAG handling and application paths that pass untrusted values into filter expressions. Do not assume impact where TAG filters are not user-influenced. Public sources do not establish exploitation in the wild.
Mitigation direction
- Upgrade Spring AI 1.0.x deployments to 1.0.5 or later.
- Upgrade Spring AI 1.1.x deployments to 1.1.4 or later.
- Review Spring’s advisory for any environment-specific guidance.
- Restrict user-controlled TAG filter values until the upgrade is complete.
- Prioritize systems exposing Redis-backed search over public or partner-facing interfaces.
Validation and detection
- Inventory applications using spring-ai-redis-store.
- Check resolved Spring AI dependency versions in build outputs.
- Trace whether request parameters reach TAG filter values.
- Confirm upgraded deployments use Spring AI 1.0.5, 1.1.4, or later.
- Add regression tests for TAG filter escaping behavior after upgrade.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
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ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-74: Exact CWE lookup
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Open ATT&CK lookupCVE-2026-22744 mapping review
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Open ATT&CK lookup- Severity
- High
- CVSS
- 7.5 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
SSVC decision data
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N3.93.6vmwareVulnerability scoring details
Base CVSS 3.1 score
7.5HighVector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Vulnerability timeline
Timeline events are normalized from CVE metadata, CNA source timelines, ADP timelines, and KEV metadata when present.
- CVE reservedCVE Program
The CVE ID was reserved by the assigning CNA.
- CVE publishedCVE Program
The CVE record was published.
- CVE updatedCVE Program
The CVE record metadata indicates this as the latest update time.
ADP provider summaries
Source materials
- CVE List V5 sourceCVE List V5
- https://spring.io/security/cve-2026-22744CVE reference, vmware
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')
Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.