Description

An issue in MongoDB Server's Atlas Vector Search feature could allow an authenticated user with read access to one view to retrieve documents from a different, protected view over the same underlying collection. This is due to insufficient handling of certain user-supplied fields when constructing an internal request forwarded to the search process.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "6.5",
  "pubDate": "2026-08-11T19:17:25.207Z",
  "pubdate": "2026-08-11T19:17:25.207Z",
  "executiveSummary": "An authorization bypass vulnerability exists within the MongoDB Server Atlas Vector Search feature. The vulnerability allows an authenticated user who possesses read access to a specific database view to successfully retrieve sensitive documents from a different, protected view that operates over the same underlying collection.\nThe root cause stems from the insufficient validation and handling of specific user-supplied fields during the construction of internal requests forwarded from the query engine to the underlying search process.\nThe impact of this flaw is a breach of data confidentiality, enabling unauthorized cross-view data retrieval within shared collections. Successful exploitation requires the attacker to be authenticated and possess baseline read privileges to at least one legitimate view on the target system.\nRisk implications include the potential exposure of sensitive or restricted data sets that were intended to be segregated via database view security boundaries. Remediation requires applying the appropriate software patches provided by the vendor to ensure strict query boundary enforcement during internal search process request construction.",
  "technicalDetails": "The vulnerability resides within the MongoDB Server architecture, specifically inside the subsystem managing the Atlas Vector Search feature. The vulnerable component is responsible for translating user queries into internal requests directed toward the search process infrastructure.\nThe root cause of the vulnerability is the inadequate sanitization and improper handling of user-supplied fields processed during the internal request-building phase. When a query is initiated against a specific database view, the query translation layer fails to adequately enforce security scoping boundaries regarding the targeted view parameters.\nThe exploitation method relies on manipulating these user-supplied fields to cause the internal search process to execute queries against a protected view rather than the intended authorized view. Because both views share the same underlying base collection, the search process retrieves and returns documents that the authenticated user should not normally be able to access.\nThe attack flow proceeds as follows: First, the attacker authenticates to the MongoDB Server with valid credentials that grant them explicit read access to a designated, non-protected view. Second, the attacker issues a specially crafted Atlas Vector Search query containing manipulated parameters or fields designed to bypass view-level isolation. Third, the MongoDB Server constructs the internal request destined for the search process without properly validating the boundaries of the requested view context. Fourth, the search process executes the query against the underlying collection using the broader scope, successfully retrieving records from the protected view. Finally, the unauthorized documents are returned through the query response pipeline to the attacker, effectively violating the principle of least privilege and data segregation.\nAuthentication requirements dictate that the attacker must possess a valid user session with read access to at least one view. Network exposure depends on the standard accessibility of the MongoDB Server instance and its Atlas Vector Search capabilities. Privilege requirements are low in terms of database access, requiring only standard read permissions on a single view, but result in a high-impact confidentiality breach across segregated database views."
}