CVE-2024-5166 in Cloud Looker
Summary
by MITRE • 05/22/2024
An Insecure Direct Object Reference in Google Cloud's Looker allowed metadata exposure across authenticated Looker users sharing the same LookML model.
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Analysis
by VulDB Data Team • 07/23/2025
The vulnerability identified as CVE-2024-5166 represents a critical Insecure Direct Object Reference issue within Google Cloud's Looker platform that fundamentally undermines the security boundaries between authenticated users. This weakness exists in the way Looker handles access control when multiple users share the same LookML model, creating an unintended pathway for metadata exposure that violates core principles of least privilege and access separation. The vulnerability specifically affects scenarios where users authenticated within the same Looker instance share common model definitions, enabling malicious actors to potentially access data and metadata that should remain restricted to specific user groups or roles.
The technical flaw manifests through improper validation of object references within Looker's access control mechanisms, where direct object references are not adequately sanitized or validated before being processed. This allows attackers to manipulate object identifiers and gain unauthorized access to metadata that should be restricted to particular user contexts. The vulnerability is particularly concerning because LookML models serve as the foundational data modeling layer in Looker, containing sensitive information about data sources, relationships, and business logic that could be exploited for further attacks. The issue stems from insufficient input validation and access control checks that should normally prevent cross-user data leakage within shared model environments.
The operational impact of this vulnerability extends beyond simple information disclosure, as it creates potential pathways for privilege escalation and data exfiltration within organizations using Google Cloud Looker. When multiple users share the same LookML model, the insecure object reference allows unauthorized access to metadata that could reveal sensitive business intelligence, data relationships, and structural information about the underlying data architecture. This exposure could enable attackers to map out entire data ecosystems, identify critical data sources, and potentially exploit additional vulnerabilities in the broader data pipeline. The implications are particularly severe for organizations with strict data governance requirements, as this vulnerability undermines the fundamental security assumptions of user isolation within shared analytical platforms.
Organizations should immediately implement mitigations including enhanced access control validation, regular auditing of shared model configurations, and implementation of proper object reference sanitization mechanisms within their Looker deployments. The vulnerability aligns with CWE-639 which specifically addresses Insecure Direct Object Reference issues, and could potentially be leveraged as part of broader attack chains that align with ATT&CK techniques such as credential access and discovery of system information. Security teams should conduct comprehensive reviews of all shared LookML model configurations and implement additional access controls that enforce proper user isolation even within shared environments. Regular security assessments should verify that object references are properly validated and that metadata access controls function as intended, particularly in multi-tenant or shared model scenarios that are common in enterprise deployments.