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CVE-2026-67926 – Unauthenticated SSRF via AI Chat Module – JeecgBoot v3.9.2

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Summary

CVE-2026-67926 is a critical code injection vulnerability (CWE-94) affecting JeecgBoot v3.9.2. The flaw resides in the files parameter of the AI Chat Module and allows a remote, unauthenticated attacker to achieve arbitrary code execution. The vulnerability carries a CVSS v3.1 base score of 9.8 (Critical).

Technical details

  • Root cause: improper validation/handling of the files parameter submitted to the JeecgBoot AI Chat Module (CWE-94, Improper Control of Generation of Code).
  • The vulnerable functionality is exposed via the AI chat/RAG feature, which accepts a files array in request input.
  • Attack vector: network, no authentication and no user interaction required (AV:N/AC:L/PR:N/UI:N).
  • Impact: full compromise of confidentiality, integrity, and availability (C:H/I:H/A:H), consistent with arbitrary code execution on the host.

Affected software

  • JeecgBoot v3.9.2

Severity

  • CVSS v3.1 Base Score: 9.8 (Critical)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Mitigation and recommended actions

  • Immediate: Upgrade JeecgBoot to a version beyond 3.9.2 that addresses this issue; consult the vendor’s GitHub repository and issue tracker for the fix corresponding to this report and apply it as soon as it is available.
  • If no patch can be applied immediately: restrict or disable the AI Chat Module/related endpoint from external network access, place it behind authentication and strict network egress controls, and monitor for anomalous requests containing unexpected values in the files parameter.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Page title: JeecgBoot 企业级低代码平台, Jeecg-Boot
  • Raw response body: a script or stylesheet path matching /jeecg-online-vendor-*.js or .css

References

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How IONIX’s External Exposure Management Platform Detects and Validates
Zero-Days to Shrink MTTR

1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

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3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

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By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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