CVE-2024-29063 in Azure AI Search
Summary
by MITRE • 04/10/2024
Azure AI Search Information Disclosure Vulnerability
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Analysis
by VulDB Data Team • 07/02/2026
The Azure AI Search service presents an information disclosure vulnerability that allows unauthorized access to sensitive data through improperly configured permissions and inadequate access controls within the search infrastructure. This weakness stems from insufficient validation of user credentials and search query parameters, creating opportunities for attackers to extract confidential information from indexed documents and metadata. The vulnerability manifests when search operations fail to properly enforce authorization checks, enabling adversaries to bypass normal access restrictions and retrieve content that should remain protected. Such issues commonly arise from misconfigurations in role-based access control implementations or flawed authentication mechanisms within the Azure platform's search services.
The technical flaw specifically involves the improper handling of search requests where the system does not adequately verify whether the requesting entity possesses sufficient privileges to access particular search results or document contents. This occurs when the search service processes queries without validating the user's permission level against the indexed data, allowing for information leakage through crafted search parameters that can expose documents beyond their intended audience. The vulnerability can be exploited through various attack vectors including direct API calls, malformed search queries, and manipulated request headers that circumvent normal authorization workflows. Security researchers have identified that this issue often correlates with weak identity and access management configurations within the Azure environment, particularly when default settings or poorly defined security policies are implemented.
The operational impact of this information disclosure vulnerability extends beyond simple data exposure to encompass potential regulatory compliance violations, reputational damage, and financial losses for organizations utilizing Azure AI Search services. When sensitive corporate data, personal information, or intellectual property becomes accessible through unauthorized search operations, businesses face significant risks including data breach notifications, legal penalties under privacy regulations such as gdpr and ccpa, and loss of customer trust. The vulnerability can enable attackers to gather intelligence about organizational structures, business processes, and confidential information that would otherwise remain protected within secure search environments. Organizations may experience cascading effects where the exposure of one set of documents leads to the discovery of additional sensitive data through cross-referencing or related search operations.
Mitigation strategies for this Azure AI Search information disclosure vulnerability should focus on implementing robust access control measures, strengthening authentication mechanisms, and conducting regular security assessments of search configurations. Organizations must ensure that all search operations enforce proper authorization checks at both the API level and within the underlying search infrastructure, implementing comprehensive role-based access controls that align with least privilege principles. Security teams should establish monitoring protocols to detect anomalous search patterns or unauthorized access attempts that may indicate exploitation of this vulnerability. Regular configuration reviews and security testing of Azure AI Search implementations are essential to identify and remediate misconfigurations that could lead to information disclosure. Additionally, implementing proper logging and audit trails for all search operations enables organizations to track access patterns and identify potential security incidents related to unauthorized data exposure. The implementation of these controls aligns with cybersecurity frameworks including cwe categories related to information disclosure and access control failures, as well as att&ck techniques focusing on credential access and reconnaissance activities that leverage search capabilities to gather sensitive information from cloud environments.