CVE-2026-96297 in MongoDB
Summary
by MITRE • 10/13/2026
Use of freed memory in the aggregation feature of MongoDB Server can cause the server to read data from a memory area after it has been released. When an internal aggregation stage is combined with a batch size of 0, the server may read from memory that is no longer in use. Because that memory can be reused for other data before it is read, query results returned to the client may contain unrelated data from the server process. Depending on the state of memory at the time, the server process may also terminate unexpectedly. The behavior can occur when an authenticated user with read privileges runs an aggregate command that combines these two settings.
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Analysis
by VulDB Data Team • 10/13/2026
The vulnerability identified in MongoDB Server involves a critical use-of-freed-memory flaw within its aggregation framework, specifically triggered by specific combinations of internal stage configurations and batch size parameters. This issue stems from improper memory management where the server attempts to access data structures after they have been deallocated or released back to the system for reuse. The technical root cause lies in how the aggregation pipeline handles cursor states when a batch size is explicitly set to zero, which signals an intent to fetch all results without intermediate batching but interacts poorly with certain internal stage optimizations that may prematurely release memory buffers associated with previous stages of the pipeline.
From a security architecture perspective, this flaw represents a classic heap-based use-after-free condition where the pointer to the freed memory block is not nullified or properly validated before being dereferenced during query execution. When an authenticated user possessing read privileges executes an aggregate command under these specific conditions, the server process reads from a memory address that no longer belongs to the current operation context. Because operating systems frequently reuse recently freed heap memory for new allocations, the data retrieved by MongoDB may correspond to unrelated information currently being processed by other threads or connections within the same database instance. This leads directly to an Information Disclosure vulnerability where sensitive internal state, potentially including credentials, session tokens, or proprietary business logic stored in adjacent memory blocks, can be inadvertently returned as part of the query results to the client application.
The operational impact extends beyond mere data leakage, encompassing significant stability and availability risks for database administrators and end-users. Depending on the specific contents of the reused memory region at the moment of access, the invalid read operation may corrupt internal pointers or trigger segmentation faults within the server process. This can result in unexpected termination of the MongoDB instance, leading to service denial for all connected clients until the process is restarted. Such instability undermines the reliability guarantees expected from enterprise-grade database systems and creates opportunities for attackers to induce repeated crashes through targeted requests, effectively achieving a Denial of Service condition without requiring elevated privileges beyond standard read access.
This vulnerability aligns with Common Weakness Enumeration (CWE) category CWE-416, which defines Use After Free as a situation where software continues to use a pointer after it has been freed, often leading to crashes or arbitrary code execution in more severe cases. In the context of MITRE ATT&CK, this behavior maps to techniques involving Tainted Input Handling and potentially Data from Information Repositories if the leaked data is exfiltrated by an attacker leveraging the vulnerability for reconnaissance purposes. The attack vector requires authentication, classifying it as a lower-severity initial access path compared to unauthenticated exploits, but its potential for both information disclosure and service disruption makes it a critical concern for environments where MongoDB handles sensitive workloads or operates in multi-tenant architectures with strict isolation requirements.
Mitigation strategies must focus on immediate patching of the affected MongoDB Server versions to address the memory management logic within the aggregation pipeline engine. Administrators should verify their current version against vendor advisories and apply updates that enforce proper lifecycle management for internal stage buffers, ensuring that pointers are invalidated after deallocation or that access is guarded by validity checks before dereferencing. In environments where immediate patching is not feasible due to operational constraints, network-level controls such as firewalls can be configured to restrict aggregate command execution from untrusted sources, although this does not mitigate the risk posed by authenticated users with legitimate read privileges who may inadvertently trigger the flaw through complex query structures. Regular auditing of database logs for unexpected process restarts or anomalous data patterns in aggregation results can also serve as a detection mechanism for potential exploitation attempts while long-term architectural reviews ensure that memory safety is prioritized in custom application logic interacting with the database engine.