CVE-2026-73652 in vantage6
Summary
by MITRE • 08/13/2026
vantage6 is an open-source infrastructure for privacy preserving analysis. In version 5.0.2 and earlier, the algorithm-store edit permission lacks an ownership check, allowing one algorithm developer to alter another developer's algorithm while it is pending or under review. The attacker can change metadata including the algorithm image or image tag, causing reviewers and nodes to trust a different image from the one originally submitted for approval. No fixed version is available as of this review.
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Analysis
by VulDB Data Team • 08/13/2026
The vantage6 platform represents a sophisticated open-source infrastructure designed for privacy-preserving analysis, facilitating secure collaborative data processing across distributed networks. This system enables multiple algorithm developers to submit their computational modules through an algorithm-store mechanism that manages the lifecycle of these algorithms from submission to deployment. The platform's architecture relies on a permission model that should ensure proper access controls and maintain the integrity of submitted algorithms throughout the review process. However, a critical vulnerability exists in versions 5.0.2 and earlier where the algorithm-store edit functionality suffers from a fundamental ownership verification flaw.
This vulnerability stems from an insufficient access control mechanism within the algorithm-store component that fails to properly validate whether the requesting user has legitimate ownership rights over the target algorithm. The flaw manifests specifically during the pending or review phases when algorithm developers submit their modules for approval by system administrators or designated reviewers. The missing ownership check creates a privilege escalation scenario where any authenticated algorithm developer can manipulate another developer's submitted algorithm, fundamentally undermining the platform's security model and trust mechanisms.
The operational impact of this vulnerability extends beyond simple unauthorized access to encompass potential security breaches that could compromise entire collaborative analysis workflows. An attacker exploiting this flaw could modify critical metadata including the algorithm image name or tag, effectively replacing the original submission with a malicious alternative without detection by reviewers or deployment nodes. This manipulation capability allows adversaries to introduce backdoors, malware, or other malicious code into the system while maintaining the appearance of legitimate software submissions. The vulnerability directly violates security principles outlined in cwe-284 access control mechanisms and aligns with attack patterns described in the mitre att&ck framework under privilege escalation and defense evasion techniques.
The absence of a fixed version creates an ongoing risk for organizations relying on vantage6 infrastructure, as no official patch exists to address this vulnerability. This situation represents a critical gap in the platform's security posture that could enable sophisticated attackers to compromise the integrity of privacy-preserving analysis workflows. Organizations using affected versions should implement immediate compensating controls including manual verification processes, enhanced monitoring of algorithm-store modifications, and restricted access permissions for algorithm developers. The vulnerability also highlights the importance of proper input validation and access control enforcement in distributed systems, particularly those handling sensitive data processing tasks where trust and integrity are paramount considerations.
This flaw demonstrates how seemingly minor implementation gaps in access control mechanisms can create substantial security risks in collaborative platforms. The vulnerability's persistence without a resolution underscores the need for continuous security assessment and remediation processes in open-source projects. Organizations should consider implementing additional verification layers beyond the platform's native controls, including cryptographic signatures for algorithm submissions, multi-factor authentication for administrative functions, and comprehensive audit logging of all algorithm-store modifications to maintain operational integrity and traceability.