CVE-2026-18444 in LabVIEW
Summary
by MITRE • 08/25/2026
There is an integer conversion vulnerability resulting in an out-of-bounds read when loading images recently discovered in NI LabVIEW. This may result in information disclosure or arbitrary code execution. Successful exploitation requires an attacker to get a user to open a specially crafted VI file. This vulnerability affects NI LabVIEW 2026 Q3 and prior versions.
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Analysis
by VulDB Data Team • 08/25/2026
The National Instruments LabVIEW platform, widely utilized for engineering applications such as test automation, data acquisition, and industrial control systems, contains a critical integer conversion vulnerability that leads to an out-of-bounds read condition during the image loading process. This flaw is rooted in improper handling of numeric values when parsing metadata or resource headers within VI (Virtual Instrument) files. Specifically, the application fails to validate whether an integer value representing image dimensions or buffer sizes fits within the expected data type constraints before performing arithmetic operations or memory allocations. When a specially crafted file containing malformed numerical inputs is processed, this lack of validation causes an integer overflow or truncation error. The resulting miscalculation leads the software to allocate insufficient memory or access memory regions outside the bounds of the intended buffer structure. This behavior aligns with CWE-190 (Integer Overflow or Wraparound) and CWE-787 (Out-of-bounds Read), which are common precursors to more severe exploitation scenarios in complex application environments like LabVIEW where binary data parsing is frequent.
The operational impact of this vulnerability extends beyond simple memory corruption, posing significant risks to system integrity and confidentiality. An out-of-bounds read allows an attacker to leak sensitive information from the process memory space that should not be accessible, potentially exposing cryptographic keys, user credentials, or proprietary engineering designs embedded within other open files or application states. This aligns with ATT&CK technique T1005 (Data from Local System), where adversaries seek to gather data for further exploitation or espionage. Furthermore, while the primary manifestation is a read-based flaw, such memory corruption issues often serve as stepping stones for arbitrary code execution if combined with other vulnerabilities or specific heap manipulation techniques. The attacker could potentially overwrite adjacent memory structures or control flow pointers, leading to remote code execution on the target machine. This risk is particularly acute in industrial and scientific settings where LabVIEW runs continuously and handles sensitive operational data, making any compromise a direct threat to critical infrastructure stability.
Successful exploitation of this vulnerability requires social engineering elements, as it necessitates that a user with appropriate privileges opens a maliciously crafted VI file within the LabVIEW environment. The attacker must distribute the payload through phishing campaigns, compromised shared drives, or trusted software update channels disguised as legitimate project files. Once opened, the application automatically attempts to parse embedded resources, triggering the integer conversion error without requiring additional user interaction beyond opening the document. This passive execution model increases the likelihood of successful compromise compared to vulnerabilities that require complex multi-step interactions. The vulnerability affects NI LabVIEW versions 2026 Q3 and prior releases, indicating a long-standing issue in the codebase related to input validation for image resources. Organizations relying on these older versions are at heightened risk until they can migrate to patched iterations or implement compensating controls such as strict file type filtering and sandboxing of untrusted inputs.
Mitigation strategies must focus on both immediate remediation and long-term architectural improvements. The primary defense is the prompt application of vendor-provided patches that address the integer validation logic in the image loading module. Until updates are available, administrators should enforce strict policies regarding the opening of VI files from unknown or unverified sources. Implementing network segmentation to isolate LabVIEW workstations from general internet access can reduce the attack surface by limiting exposure to phishing vectors. Additionally, deploying application whitelisting solutions that prevent unauthorized binaries or scripts from executing within the LabVIEW environment adds a layer of defense-in-depth. Security teams should also monitor for anomalous memory access patterns using endpoint detection and response tools configured to flag out-of-bounds read attempts. Regular audits of file intake processes and employee training on recognizing suspicious attachments are essential human-layer defenses against this type of social engineering-driven exploitation.