CVE-2023-40183 in DataEase
Summary
by MITRE • 09/21/2023
DataEase is an open source data visualization and analysis tool. Prior to version 1.18.11, DataEase has a vulnerability that allows an attacker to to obtain user cookies. The program only uses the `ImageIO.read()` method to determine whether the file is an image file or not. There is no whitelisting restriction on file suffixes. This allows the attacker to synthesize the attack code into an image for uploading and change the file extension to html. The attacker may steal user cookies by accessing links. The vulnerability has been fixed in v1.18.11. There are no known workarounds.
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Analysis
by VulDB Data Team • 10/14/2023
CVE-2023-40183 represents a critical server-side request forgery vulnerability within DataEase, an open-source data visualization and analysis platform. This vulnerability stems from insufficient input validation and file type verification mechanisms that allow attackers to bypass security controls through crafted file uploads. The flaw specifically manifests when the application utilizes the ImageIO.read() method solely for image file validation without implementing proper file extension whitelisting or content type verification. This approach creates a dangerous attack vector where malicious actors can manipulate file extensions while maintaining valid image file structures, effectively circumventing the intended security boundaries.
The technical implementation of this vulnerability exploits the fundamental weakness in the file validation process by leveraging the ImageIO library's ability to read various image formats without strict extension enforcement. Attackers can create HTML content that is disguised as an image file by manipulating the file extension from .jpg or .png to .html while maintaining the underlying file structure that ImageIO recognizes as valid. This technique enables the execution of malicious code within the context of the user's browser session, as the server serves the uploaded file with appropriate content headers that trick browsers into executing the embedded HTML payload. The vulnerability directly maps to CWE-434, which addresses insecure file upload vulnerabilities where applications accept files without proper validation of file type, content, or extension.
The operational impact of this vulnerability extends beyond simple cookie theft, creating a potential pathway for session hijacking and privilege escalation attacks within the DataEase environment. When users access the maliciously uploaded file, their browser executes the embedded HTML code, potentially allowing attackers to extract session cookies, redirect users to malicious sites, or perform actions on behalf of authenticated users. This type of vulnerability aligns with ATT&CK technique T1190, which covers exploit for client execution through web-based attacks, and T1531, which involves use of unauthorized system binaries or components. The vulnerability represents a significant risk to user authentication integrity and could enable attackers to gain unauthorized access to sensitive data visualization dashboards and underlying analytics systems.
The remediation for CVE-2023-40183 requires implementing robust file validation mechanisms that enforce strict whitelisting of acceptable file extensions and content types rather than relying solely on the ImageIO.read() method for validation. Organizations should implement comprehensive file type verification that checks both file extensions and actual file content signatures, ensuring that uploaded files match their declared types. Security controls should include mandatory content type validation, file size restrictions, and implementation of proper file naming conventions that prevent extension manipulation. The fix in version 1.18.11 demonstrates the importance of proper input validation and the necessity of implementing multiple layers of security controls rather than relying on single validation methods. Additionally, organizations should consider implementing web application firewalls, content security policies, and regular security scanning to detect similar vulnerabilities in other components of their data visualization infrastructure.