CVE-2026-43980 in Malla
Summary
by MITRE • 08/21/2026
Malla is a web analyzer for Meshtastic networks based on MQTT data. Prior to commit 4086e2b5f61615a813b70b25bc76095083552135, code names (long_name, short_name) received via MQTT are stored in SQLite without sanitization and rendered into the DOM without escaping. Any participant on a public Meshtastic MQTT broker can set a malicious node name that executes JavaScript in the browser of every Malla dashboard visitor. Commit 4086e2b5f61615a813b70b25bc76095083552135 fixes the issue.
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Analysis
by VulDB Data Team • 08/21/2026
The vulnerability identified in the Malla web application, a tool designed for analyzing Meshtastic networks via MQTT data streams, represents a critical cross-site scripting flaw rooted in improper input validation and output encoding practices. Prior to the corrective commit 4086e2b5f61615a813b70b25bc76095083552135, the application failed to sanitize or escape data received from external sources before processing it for display. Specifically, node identifiers such as long_name and short_name were ingested directly into an SQLite database without any form of sanitization. This lack of input validation allowed untrusted actors to inject malicious payloads disguised as legitimate network metadata. The severity of this flaw is compounded by the fact that these unsanitized values are subsequently rendered directly into the Document Object Model using innerHTML or similar methods, which execute embedded JavaScript code rather than treating it as plain text data.
From a technical perspective, this vulnerability aligns with CWE-79, known as Improper Neutralization of Input During Web Page Generation, commonly referred to as Cross-Site Scripting (XSS). The attack vector is particularly potent because the Meshtastic network utilizes public MQTT brokers that are accessible to any participant on the internet. An attacker can simply connect to these open brokers and publish a message containing a malicious node name with embedded JavaScript payloads. When other users access the Malla dashboard, their browsers retrieve this data from the backend server, which stores it in SQLite without filtering. Upon rendering the page for visualization purposes, the browser interprets the stored script as executable code, leading to immediate client-side execution within the context of the victim's session.
The operational impact of this vulnerability is significant, potentially allowing attackers to perform a variety of malicious actions against users viewing the dashboard. These actions include stealing sensitive session cookies or authentication tokens, which could lead to account takeover if such credentials are stored in accessible local storage or cookies. Furthermore, an attacker could redirect victims to phishing sites designed to mimic legitimate Meshtastic management interfaces, thereby harvesting user credentials under false pretenses. In more advanced scenarios, the injected script could be used to deface the application interface, log keystrokes entered by administrators, or even exfiltrate network topology data and other sensitive information displayed on the dashboard to an external server controlled by the attacker. This compromises not only individual privacy but also the integrity of the mesh network analysis provided by Malla.
Mitigation strategies for this vulnerability focus primarily on implementing robust input validation and output encoding mechanisms. The fix implemented in commit 4086e2b5f61615a813b70b25bc76095083552135 addresses the root cause by ensuring that data is properly sanitized before storage and escaped during rendering. Developers should adhere to strict whitelisting practices for input fields, rejecting any characters or patterns that do not conform to expected formats for node names. Additionally, employing context-aware output encoding libraries when injecting data into HTML elements prevents browsers from interpreting special characters as code. It is also advisable to implement Content Security Policy headers to restrict the sources from which scripts can be loaded and executed, adding an additional layer of defense against XSS attacks even if input validation fails.
This incident highlights the importance of secure coding practices in applications that aggregate data from open or semi-open networks like Meshtastic. By treating all external inputs as untrusted until proven otherwise, developers can prevent similar vulnerabilities across their software stack. The integration of automated static analysis tools and regular security audits can further help identify such flaws early in the development lifecycle. For users relying on Malla for network monitoring, ensuring that they are running a version patched with commit 4086e2b5f61615a813b70b25bc76095083552135 or later is essential to maintain the security and integrity of their operational environment.