CVE-2026-24012 in IoTDB
Summary
by MITRE • 07/06/2026
Uncontrolled Resource Consumption vulnerability in Apache IoTDB.
Some interface fails to impose reasonable limits on the time span and aggregation interval of the query. An attacker can construct a request with extreme parameters (e.g., a very large time range combined with a minimal interval). This forces the DataNode to build an enormous result set in memory, which exhausts the Java heap and causes the DataNode process to crash.
This issue affects Apache IoTDB: from 1.3.3 before 2.0.8.
Users are recommended to upgrade to version 2.0.8, which fixes the issue.
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Analysis
by VulDB Data Team • 07/06/2026
The vulnerability under discussion represents a classic example of resource exhaustion attack targeting Apache IoTDB's query processing mechanisms. This uncontrolled resource consumption flaw specifically impacts the DataNode component where query operations are executed, creating a pathway for malicious actors to deliberately overwhelm system resources through carefully crafted requests. The vulnerability exists within the parameter validation logic that governs how time ranges and aggregation intervals are processed during query execution, allowing attackers to bypass normal operational constraints and submit extreme values that would otherwise be rejected by reasonable limits.
The technical implementation of this vulnerability stems from insufficient input validation within IoTDB's query interface components. When users submit queries with excessive time spans combined with minimal aggregation intervals, the system fails to enforce appropriate boundaries on these parameters. This lack of boundary checking enables the construction of queries that generate massive result sets in memory, where each data point corresponds to a specific timestamp within the expanded range. The DataNode processes these requests without adequate safeguards, leading to exponential memory consumption as the system attempts to construct comprehensive datasets for the attacker's malformed query parameters.
The operational impact of this vulnerability extends beyond simple service disruption, potentially causing complete system crashes and data loss scenarios. When the Java heap space becomes exhausted due to the massive in-memory result sets, the DataNode process terminates abruptly, resulting in cascading failures that can affect entire IoT deployments. This type of denial-of-service condition directly impacts the availability component of the CIA triad and can be particularly devastating in industrial IoT environments where continuous data collection and monitoring are critical for operational safety and business continuity. The vulnerability affects all versions from 1.3.3 through 2.0.7, representing a significant window of exposure for affected organizations.
From a cybersecurity framework perspective, this vulnerability aligns with CWE-400 which specifically addresses uncontrolled resource consumption and relates to ATT&CK technique T1499.1 which covers resource exhaustion attacks targeting availability. The flaw demonstrates poor input validation practices that should be addressed through proper parameter sanitization and boundary checking mechanisms. Organizations should implement rate limiting and query complexity controls as immediate mitigations while upgrading to version 2.0.8 provides the definitive fix for this vulnerability. The recommended upgrade path ensures that appropriate limits are enforced on time range and aggregation interval parameters, preventing the construction of excessive result sets that could overwhelm system resources. System administrators should also consider implementing monitoring solutions to detect anomalous query patterns that might indicate exploitation attempts.