CVE-2018-18540 in TeaKKi
Summary
by MITRE
TeaKKi 2.7 allows XSS via a crafted onerror attribute for a picture's URL.
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Analysis
by VulDB Data Team • 05/30/2023
The vulnerability identified as CVE-2018-18540 affects TeaKKi version 2.7 and represents a cross-site scripting flaw that arises from improper handling of image error attributes. This issue manifests when a malicious user crafts a picture URL containing a crafted onerror attribute that executes arbitrary javascript code upon image loading failures. The vulnerability falls under the category of client-side injection attacks and demonstrates a critical weakness in input validation and output encoding mechanisms within the application's image handling functionality.
The technical implementation of this vulnerability stems from the application's failure to properly sanitize or escape user-supplied input when processing image URLs. When a picture element contains an onerror attribute, the web application does not adequately filter or encode the attribute value before rendering it in the browser context. This allows attackers to inject malicious javascript code that executes when the image fails to load, creating a persistent cross-site scripting vector. The flaw specifically exploits the onerror event handler in html img tags, which is commonly used to provide fallback content when images cannot be displayed. According to CWE-79, this vulnerability maps directly to Cross-Site Scripting flaws where improper validation of user input leads to execution of malicious scripts in the victim's browser context.
The operational impact of this vulnerability extends beyond simple script execution, as it can enable attackers to perform session hijacking, steal sensitive information, redirect users to malicious websites, or execute additional attacks through the compromised browser. An attacker could craft a malicious image URL that, when processed by TeaKKi 2.7, would execute code that steals cookies, captures keystrokes, or modifies the application's behavior. The vulnerability is particularly concerning because it operates through normal user interactions with image elements, making detection difficult and exploitation straightforward. From an ATT&CK framework perspective, this vulnerability aligns with T1059.007 for scripting languages and T1566 for social engineering techniques that leverage web-based attacks.
Mitigation strategies for this vulnerability should focus on comprehensive input validation and output encoding practices. The application must implement strict sanitization of all user-supplied input, particularly when processing image URLs and their associated attributes. Input validation should reject or escape any characters that could be used to inject javascript code, including angle brackets, quotes, and javascript protocol handlers. Output encoding should be applied when rendering image attributes to ensure that any potentially malicious content is rendered harmless in the browser context. Additionally, implementing content security policies and using the sandbox attribute for embedded content can provide additional defense-in-depth measures. Regular security testing including automated vulnerability scanning and manual penetration testing should be conducted to identify similar input validation flaws in other application components. The vulnerability also highlights the importance of keeping all third-party libraries and frameworks updated, as similar issues have been documented in various web application frameworks and content management systems that handle image processing and rendering functions.