CVE-2026-63355 in Siemens
Summary
by MITRE • 10/13/2026
Affected devices do not properly sanitize signal names contained in imported CSV trace files before rendering them in selection menus on the Trace page.
This could allow an attacker to social engineer an authorized user who holds the function right “Read diagnostics” into importing a specially crafted trace file. Attacker-controlled JavaScript could be executed in the user’s browser session when the user subsequently interacts with an affected selection menu.
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Analysis
by VulDB Data Team • 10/14/2026
The vulnerability described constitutes a classic Cross-Site Scripting (XSS) flaw, specifically categorized under CWE-79: Improper Neutralization of Input During Web Page Generation. This security defect arises from insufficient input validation and sanitization mechanisms within the application's backend processing logic for imported CSV trace files. When users upload these diagnostic data files to be rendered in selection menus on the Trace page, the system fails to properly escape or neutralize special characters embedded within signal names. Consequently, if a malicious actor embeds executable JavaScript code within the signal name field of a crafted CSV file, that script is stored and subsequently reflected back into the user interface without adequate filtering. This lack of sanitization allows raw script content to persist in the DOM structure when the selection menu is rendered, creating an execution vector for client-side attacks.
The operational impact of this vulnerability relies heavily on social engineering tactics due to its classification as a Stored or Reflected XSS depending on whether the data persists server-side before retrieval. An attacker must first deceive an authorized user possessing the Read diagnostics function right into importing a specially crafted trace file. Once imported, the malicious payload remains dormant until the victim interacts with the affected selection menu. At that moment, the browser interprets the unsanitized signal name as executable code rather than plain text. This results in the execution of attacker-controlled JavaScript within the context of the user’s active session. The consequences can range from stealing sensitive diagnostic data and session cookies to performing actions on behalf of the victim or redirecting them to phishing sites, thereby compromising the confidentiality, integrity, and availability of the industrial control system's monitoring interface.
From a threat modeling perspective aligned with MITRE ATT&CK techniques, this vulnerability facilitates initial access through social engineering (T1566) followed by credential harvesting or session hijacking via browser-based attacks such as Cross-Site Scripting: Persistent (T1059.007). The attacker leverages the trusted relationship between the user and the diagnostic interface to bypass authentication controls indirectly, exploiting the trust that users place in imported data files. This is particularly dangerous in industrial environments where operational technology interfaces may have limited security awareness among operators who are primarily focused on monitoring system health rather than cybersecurity hygiene.
To mitigate this vulnerability, developers must implement strict input validation and output encoding strategies for all user-supplied data before it is rendered in the browser context. Specifically, signal names extracted from CSV files should be sanitized to remove or escape HTML special characters such as angle brackets, quotes, ampersands, and semicolons that could terminate existing attributes or inject new script tags. Implementing a Content Security Policy (CSP) header can also significantly reduce the impact by restricting the sources from which scripts are allowed to execute, thereby preventing inline script execution even if injection occurs. Additionally, enforcing role-based access control ensures that only authorized personnel with specific diagnostic privileges can upload trace files, reducing the attack surface. Regular security code reviews and automated static analysis tools configured to detect XSS patterns in data handling routines should be employed to prevent similar flaws from being introduced during future development cycles.