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CVE-2026-3733: Server-Side Request Forgery in xuxueli xxl-job

0
Medium
VulnerabilityCVE-2026-3733cvecve-2026-3733
Published: Sun Mar 08 2026 (03/08/2026, 11:02:14 UTC)
Source: CVE Database V5
Vendor/Project: xuxueli
Product: xxl-job

Description

A vulnerability was detected in xuxueli xxl-job up to 3.3.2. This impacts an unknown function of the file source-code/src/main/java/com/xxl/job/admin/controller/JobInfoController.java. The manipulation results in server-side request forgery. It is possible to launch the attack remotely. The exploit is now public and may be used. The project maintainer closed the issue report with the following statement: "Access token security verification is required." (translated from Chinese)

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 03/16/2026, 09:05:47 UTC

Technical Analysis

CVE-2026-3733 is a server-side request forgery vulnerability identified in the xuxueli xxl-job open-source distributed task scheduling platform, affecting versions 3.3.0 through 3.3.2. The vulnerability resides in the JobInfoController.java source file, where an attacker can manipulate server-side requests by exploiting insufficient validation or filtering of user-supplied input that controls outbound HTTP requests. This SSRF flaw enables remote attackers to coerce the vulnerable server into sending crafted requests to internal or external systems, potentially bypassing network access controls or firewall rules. The vulnerability can be triggered remotely without user interaction but requires low privileges, indicating that an attacker with limited access could exploit it. The project maintainer has indicated that access token security verification is necessary to prevent exploitation, implying that the vulnerability is mitigated if proper authentication tokens are enforced. The CVSS 4.0 base score of 5.3 reflects a medium severity level, with network attack vector, low attack complexity, no user interaction, and partial impact on confidentiality, integrity, and availability. No public patches or exploits are currently documented, but the exploit code is publicly available, increasing the risk of future attacks. The vulnerability's impact is primarily on the confidentiality and integrity of internal network resources and the availability of services that rely on the xxl-job scheduler.

Potential Impact

The SSRF vulnerability in xxl-job could allow attackers to perform unauthorized internal network scans, access sensitive internal services, or cause denial of service by triggering unexpected requests. This can lead to exposure of internal infrastructure details, unauthorized data access, or disruption of scheduled job execution. Organizations relying on xxl-job for critical task scheduling may experience operational interruptions or data leakage. The medium CVSS score indicates moderate risk, but the presence of publicly available exploit code increases the likelihood of exploitation attempts. Since the vulnerability requires low privileges but no user interaction, attackers who gain limited access to the system or network could leverage this flaw to escalate their reach internally. The lack of authentication token enforcement significantly raises the risk. Industries with complex internal networks and sensitive data, such as finance, healthcare, and manufacturing, are particularly vulnerable. Additionally, cloud environments using xxl-job could see lateral movement or data exfiltration attempts via SSRF.

Mitigation Recommendations

To mitigate CVE-2026-3733, organizations should immediately enforce strict access token verification for all API endpoints exposed by xxl-job, ensuring that only authenticated and authorized requests are processed. Network segmentation should be applied to limit the server's ability to reach sensitive internal services or external untrusted networks. Implement outbound request filtering and egress controls to restrict the destinations that the xxl-job server can contact. Regularly update to the latest version of xxl-job once patches become available. Conduct thorough input validation and sanitization on parameters that influence outbound requests to prevent injection of malicious URLs. Monitor logs for unusual outbound request patterns indicative of SSRF exploitation attempts. Employ Web Application Firewalls (WAFs) with SSRF detection rules to block suspicious traffic. Finally, perform security audits and penetration testing focused on SSRF vectors in the deployment environment.

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Technical Details

Data Version
5.2
Assigner Short Name
VulDB
Date Reserved
2026-03-07T18:00:25.805Z
Cvss Version
4.0
State
PUBLISHED

Threat ID: 69ad58832904315ca3977d20

Added to database: 3/8/2026, 11:07:47 AM

Last enriched: 3/16/2026, 9:05:47 AM

Last updated: 4/28/2026, 7:23:50 AM

Views: 104

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