CVE-2013-4245 in Orca
Summary
by MITRE
Orca has arbitrary code execution due to insecure Python module load
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Analysis
by VulDB Data Team • 12/25/2024
The vulnerability identified as CVE-2013-4245 affects the Orca screen reader application, which is widely used by visually impaired users to access desktop environments on linux systems. This security flaw resides in the application's handling of Python modules, specifically in how it loads and executes code from potentially untrusted sources. The issue stems from the application's failure to properly validate or sanitize module names and paths during the loading process, creating a pathway for malicious actors to inject and execute arbitrary code on affected systems.
The technical root cause of this vulnerability aligns with CWE-472 Unprotected Primary Resource and CWE-94 Improper Control of Generation of Code, as Orca demonstrates inadequate input validation and code execution controls when processing Python modules. The flaw allows attackers to manipulate the module loading mechanism through specially crafted input that bypasses normal security checks. When Orca processes a malicious module, it executes the code with the privileges of the user running the screen reader, potentially enabling full system compromise. This vulnerability operates at the intersection of privilege escalation and code injection attack vectors, making it particularly dangerous in multi-user environments.
The operational impact of CVE-2013-4245 extends beyond simple code execution, as it can be leveraged to establish persistent access, escalate privileges, or exfiltrate sensitive data from systems where Orca is installed. Given that Orca is typically run with elevated privileges to access system resources and provide accessibility services, successful exploitation can result in complete system compromise. The vulnerability affects users who may unknowingly load malicious modules through legitimate application workflows, such as when accessing remote desktop environments or when system administrators configure accessibility tools. This makes the attack surface particularly broad, as the vulnerability can be exploited through various vectors including network-based attacks or local privilege escalation scenarios.
Mitigation strategies for CVE-2013-4245 should focus on immediate patching of affected Orca versions, along with enhanced input validation and module loading restrictions. Organizations should implement strict module whitelisting policies and ensure that all Python modules loaded by Orca are properly verified and authenticated. The implementation of principle of least privilege should be enforced, limiting the execution permissions of accessibility tools to prevent privilege escalation. Additionally, system administrators should monitor for unauthorized module installations and consider using application control solutions that can prevent execution of untrusted Python code. This vulnerability demonstrates the critical importance of secure coding practices in accessibility applications, as these tools often run with elevated privileges and must be protected against code injection attacks that could compromise entire computing environments. The ATT&CK framework categorizes this vulnerability under T1059 Command and Scripting Interpreter and T1068 Exploitation for Privilege Escalation, highlighting the need for comprehensive defensive measures.