CVE-2026-59319 Spring CVE debrief

Who should care

Developers and administrators of VMware Spring AI 2.0.0 applications, especially those using RediSearch for querying chat messages, should be aware of this vulnerability and take necessary precautions to prevent exploitation. This includes validating and sanitizing user-controlled metadata values, implementing compensating controls for RediSearch queries, and monitoring for suspicious RediSearch query activity. Additionally, security teams and vulnerability management teams should review and update security configurations for RediSearch and conduct regular security audits and vulnerability assessments.

Technical summary

RedisChatMemoryRepository.findByMetadata() in VMware Spring AI 2.0.0 does not properly escape RediSearch tag and text queries from caller-supplied metadata values, allowing potential syntax injection attacks. This vulnerability can be exploited by an attacker to inject RediSearch syntax, potentially leading to unauthorized access to sensitive chat messages. The affected product, VMware Spring AI 2.0.0, uses RediSearch for querying chat messages, and an application that passes user-controlled values to findByMetadata() on a tag-typed metadata field is vulnerable to this attack.

Defensive priority

Medium-priority defensive actions recommended due to potential for limited scope attacks.

Recommended defensive actions

• Apply vendor-provided patch or upgrade to Spring AI 2.0.1
• Validate and sanitize user-controlled metadata values
• Implement compensating controls for RediSearch queries
• Monitor for suspicious RediSearch query activity
• Review and update security configurations for RediSearch
• Conduct regular security audits and vulnerability assessments
• Establish incident response plan for potential syntax injection attacks

Evidence notes

Evidence from official CVE Program record and NVD vulnerability detail page supports vulnerability in VMware Spring AI 2.0.0. Limited evidence of user-controlled input validation and error handling. Additional review of vendor documentation and security advisories indicates potential for limited scope attacks. Further verification of affected product deployments and compensating controls is recommended.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.