CVE-2026-24713 & CVE-2026-24015: Critical Input Validation Flaws in Apache IoTDB Expose Industrial IoT Data Platforms to Remote Exploitation

Product Overview

Apache IoTDB (Internet of Things Database) is an open-source time-series database designed specifically for IoT data ingestion, storage, and analytics. The platform is commonly deployed in environments that generate large amounts of telemetry data such as industrial monitoring systems, smart infrastructure platforms, energy management systems, manufacturing plants, and cloud-based IoT telemetry pipelines.

IoTDB supports SQL-like queries, distributed storage, and real-time data ingestion from sensors and edge devices. Due to its role as a telemetry backend, it is often integrated with monitoring dashboards, industrial control networks, and automated data pipelines.

Two critical vulnerabilities have been identified in multiple Apache IoTDB releases. These weaknesses originate from insufficient input validation and improper configuration handling, allowing maliciously crafted inputs or unauthorized interactions with the database engine.

If successfully exploited, attackers may gain the ability to manipulate stored telemetry data, execute unauthorized queries, trigger service disruption, or access sensitive time-series data stored within the database.


Affected Products

Apache IoTDB

Affected Versions:

  • 1.0.0 – 1.3.6
  • 2.0.0 – 2.0.6

Vulnerability Summary

CVE IDVulnerability TypeSeverityCVSS (Estimated)ExploitabilityExploit Availability
CVE-2026-24713Improper Input Validation / Expression InjectionCritical~9.0HighNo public exploit confirmed
CVE-2026-24015Improper Input Validation / Configuration WeaknessCritical~8.8HighNo public exploit confirmed

CVE-2026-24713

Description

A critical vulnerability exists in Apache IoTDB due to improper validation of user-supplied expressions within the query processing engine. The database supports complex expressions and functions that can be embedded inside queries for filtering, aggregation, or calculation.

Under certain circumstances, input supplied through query parameters or APIs may be interpreted directly by the expression evaluation component without sufficient sanitization. Because of this behavior, specially crafted expressions could be executed by the underlying evaluation engine.

When malicious expressions are accepted by the query parser, the database may attempt to evaluate them as executable logic. This condition could allow an attacker to inject commands or perform unexpected operations during query execution.

The vulnerability becomes especially dangerous in environments where the database interface is exposed to external clients, web dashboards, or automated ingestion pipelines.


Technical Details

The issue originates from the lack of strict validation on expressions passed to the evaluation subsystem used by IoTDB’s query engine.

Instead of treating user input strictly as data, the engine may treat certain components as executable expressions.

The following behaviors may occur:

  • Untrusted expressions are evaluated during query parsing
  • Runtime evaluation mechanisms may execute malicious logic
  • Expression parsing may access internal classes or functions
  • Resource-intensive expressions may be executed repeatedly

This may lead to:

  • Arbitrary command execution in some contexts
  • Manipulation of stored sensor data
  • Denial-of-service through computationally expensive expressions
  • Unauthorized access to internal objects

Exploitation Scenario

A realistic attack scenario could involve the following sequence:

  1. An exposed IoTDB query interface is discovered through network scanning.
  2. The attacker interacts with the query API or client interface.
  3. A crafted query containing malicious expressions is submitted.
  4. The expression engine evaluates the injected payload.
  5. The payload is executed within the database runtime environment.

This technique could allow an attacker to run unauthorized operations or crash the service.


Proof of Concept (Educational Use Only)

Example malicious query attempting expression execution:

SELECT * FROM root.device.sensor
WHERE temperature > eval("java.lang.Runtime.getRuntime().exec('id')")

Another example payload attempting command execution through expression parsing:

SELECT * FROM root.iot.data
WHERE value > ${T(java.lang.Runtime).getRuntime().exec("whoami")}

These examples demonstrate how malicious expressions could be embedded within queries.


Indicators of Compromise

The following abnormal behaviors may indicate exploitation attempts:

  • Queries containing scripting patterns
  • Java runtime references appearing in query strings
  • Unexpected query errors or expression evaluation failures
  • High CPU usage during query processing
  • Repeated malformed queries sent to the database
  • Unusual class references within query logs

Detection

Log Sources

The following log sources should be monitored:

  • IoTDB server logs
  • IoTDB query execution logs
  • REST API request logs
  • Database audit logs
  • Reverse proxy access logs
  • Network IDS / IPS logs
  • Firewall connection logs

Detection Rules

Splunk Query

index=iotdb_logs
| search query="*Runtime.getRuntime*" OR query="*exec(*" OR query="*eval(*" OR query="*java.lang*"
| stats count by src_ip query

Elastic Query (KQL)

query : ("Runtime.getRuntime" OR "exec(" OR "eval(" OR "java.lang")

Microsoft Sentinel (KQL)

IoTDBLogs
| where Query contains "Runtime.getRuntime"
or Query contains "exec("
or Query contains "eval("
or Query contains "java.lang"
| summarize Attempts=count() by SourceIP, Query

Network IDS Pattern

(Runtime\.getRuntime|exec\(|eval\(|java\.lang)

MITRE ATT&CK Mapping

TechniqueDescription
T1190Exploit Public Facing Application
T1059Command and Scripting Interpreter
T1499Endpoint Denial of Service
T1565Data Manipulation

CVE-2026-24015

Description

Another critical vulnerability has been identified in Apache IoTDB that originates from insufficient validation and security checks in database interactions and configuration behavior.

In certain deployments, input supplied through database operations or interfaces may not be adequately verified before processing. As a result, malicious queries or unauthorized database interactions could be performed.

If the database service is exposed externally or if weak authentication configurations are used, attackers may gain the ability to connect to the database and execute arbitrary commands.

Because IoTDB often stores operational telemetry data, unauthorized access could result in data tampering, deletion, or leakage.


Technical Details

The vulnerability is related to weak validation and improper handling of database access conditions.

Possible contributing factors include:

  • Inadequate validation of incoming commands
  • Improper enforcement of access restrictions
  • Lack of strict verification for query parameters
  • Misconfigured authentication or authorization mechanisms

These weaknesses may allow attackers to interact directly with the database server.


Exploitation Scenario

A possible exploitation path may involve the following steps:

  1. The IoTDB service is discovered during network reconnaissance.
  2. The default database port is identified.
  3. A connection is established through a database client.
  4. Unauthorized queries are executed against the database.

Because time-series databases store historical telemetry data, attackers may retrieve large volumes of operational data or modify stored values.


Proof of Concept (Educational Use Only)

Example database interaction attempt:

iotdb-client -h target_server -p 6667

Example queries that may be executed once connected:

SHOW STORAGE GROUP
SELECT * FROM root.*
DELETE FROM root.factory.sensor

These queries demonstrate how data could potentially be accessed or modified.


Indicators of Compromise

Potential signs of exploitation include:

  • Unknown client connections to IoTDB service ports
  • Database sessions originating from external IP addresses
  • Unusual query patterns executed by unknown users
  • Large volumes of SELECT queries from new sources
  • Sudden deletion or modification of time-series data
  • Authentication attempts from unfamiliar networks

Detection

Log Sources

Recommended monitoring locations include:

  • IoTDB authentication logs
  • Database connection logs
  • Query audit logs
  • Network firewall logs
  • IDS / IPS network alerts
  • System process logs

Detection Rules

Splunk Query

index=iotdb_logs
| search action=login_success
| stats count by src_ip user
| where src_ip NOT IN ("trusted_internal_ranges")

Elastic Query (KQL)

event.dataset : "iotdb.auth"
and event.outcome : "success"
and not source.ip : (trusted_network_ranges)

Microsoft Sentinel Query

IoTDBAuthLogs
| where LoginStatus == "Success"
| where SourceIP !in ("trusted_network_ranges")
| summarize count() by SourceIP, Username

Network Monitoring Rule

alert tcp any any -> server 6667
msg:"Suspicious Apache IoTDB access attempt";

MITRE ATT&CK Mapping

TechniqueDescription
T1190Exploit Public Facing Application
T1046Network Service Discovery
T1078Valid Accounts
T1565Data Manipulation

Mitigation

The following mitigation steps are recommended:

  • Upgrade Apache IoTDB to a patched version immediately
  • Restrict database access to internal trusted networks
  • Implement authentication and strong credential policies
  • Disable unnecessary database interfaces
  • Monitor query activity and database connections
  • Deploy network filtering rules limiting access to IoTDB ports

Official Patch / Upgrade

The vulnerabilities have been addressed in newer Apache IoTDB releases.

Upgrade to:

  • Apache IoTDB 1.3.7
  • Apache IoTDB 2.0.7

Official project website for patches and releases:

https://iotdb.apache.org


Aegiron

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