PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-97320 YunaiV/zhijiantianya CVE debrief

A server-side request forgery vulnerability has been identified in the AI Knowledge Module of the ruoyi-vue-pro application, specifically in the AiKnowledgeDocumentServiceImpl.readUrl function. This issue allows remote attackers to manipulate the URL argument, potentially leading to unauthorized requests. The exploit has been published, and although the vendor was notified, no response was received.

Vendor
YunaiV/zhijiantianya
Product
ruoyi-vue-pro
CVSS
LOW 2.1
CISA KEV
Not listed in stored evidence
Original CVE published
2026-09-24
Original CVE updated
2026-09-25
Advisory published
2026-09-24
Advisory updated
2026-09-25

Who should care

Defenders responsible for systems using the ruoyi-vue-pro application, especially those with publicly accessible AI Knowledge Module functionality, should assess their exposure and prioritize verification of affected systems.

Why it matters

CVE-2026-97320 is a server-side request forgery vulnerability in the AI Knowledge Module of ruoyi-vue-pro. Defenders should assess exposure, prioritize verification, and consider implementing additional security measures.

  • Potential unauthorized requests to internal resources
  • Possible data breaches or system compromise
  • Need for input validation and URL filtering
  • Verification of affected system inventory and exposure

Technical summary

The AiKnowledgeDocumentServiceImpl.readUrl function in the AI Knowledge Module of ruoyi-vue-pro is vulnerable to server-side request forgery (SSRF). This occurs because the function does not properly validate or restrict the URL argument, allowing remote attackers to manipulate it and potentially make unauthorized requests to internal resources. The vulnerability has a CVSS score of 2.1 and is considered LOW severity. The exploit has been published, and defenders should assess their exposure, prioritize verification of affected systems, and consider implementing additional security measures such as input validation and URL filtering.

Defensive priority

Assess exposure and prioritize verification of affected systems, especially those with publicly accessible AI Knowledge Module functionality.

Recommended defensive actions

  • Verify if the AI Knowledge Module is exposed to untrusted networks or users.
  • Review and restrict access to the AiKnowledgeDocumentServiceImpl.readUrl function.
  • Monitor for potential unauthorized requests to internal resources.
  • Consider implementing additional security measures, such as input validation and URL filtering.
  • Assess exposure and prioritize verification of affected systems, especially those with publicly accessible AI Knowledge Module functionality.
  • Review compensating controls for exposed systems while remediation is scheduled and verified.
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented.

Evidence notes

The CVE record and NVD entry provide details on the vulnerability, including its CVSS score of 2.1 and severity of LOW. The exploit has been published, but there is no information on in-the-wild exploitation.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-97320 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-97320

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-97320 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-97320

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental 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.