CVE-2015-5607 in IPython
Summary
by MITRE
Cross-site request forgery in the REST API in IPython 2 and 3.
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Analysis
by VulDB Data Team • 11/22/2024
The vulnerability identified as CVE-2015-5607 represents a critical cross-site request forgery weakness discovered in the REST API implementation of IPython versions 2 and 3. This security flaw resides within the web-based interactive computing environment that is widely used for data science and scientific computing tasks. The vulnerability stems from insufficient validation of incoming requests to the REST API endpoints, which allows malicious actors to exploit the lack of proper authentication and authorization mechanisms. IPython's REST API serves as a critical interface for programmatic access to the notebook server, enabling users to perform operations such as creating, reading, updating, and deleting notebooks and other resources through HTTP requests. The absence of adequate CSRF protection mechanisms in these versions creates a significant attack surface where authenticated users can be tricked into executing unintended actions on the IPython server without their knowledge or consent.
The technical exploitation of this vulnerability occurs when an attacker crafts malicious web pages or links that, when visited by an authenticated IPython user, automatically submit requests to the REST API endpoints. This type of attack leverages the browser's automatic handling of cookies and authentication tokens that are automatically included with requests to the IPython server. The flaw specifically affects the API endpoints that handle state-changing operations within the IPython environment, including those related to notebook management, file operations, and kernel control. Attackers can leverage this vulnerability to perform unauthorized actions such as creating malicious notebooks, modifying existing files, executing arbitrary code through kernel operations, or even deleting important data. The vulnerability is particularly dangerous because IPython servers are often deployed in environments where users maintain elevated privileges and have access to sensitive data and computational resources.
The operational impact of CVE-2015-5607 extends beyond simple data theft or modification, as it can enable complete compromise of the IPython server environment. When exploited successfully, this vulnerability allows attackers to gain persistent access to the computational resources and data stored within the IPython environment, potentially leading to data exfiltration, system compromise, or lateral movement within networked environments where IPython servers are deployed. The vulnerability affects organizations that rely on IPython for data analysis, scientific computing, or educational purposes, particularly those in research institutions, financial services, or government agencies where sensitive information is processed. The risk is amplified when IPython servers are accessible from untrusted networks or when multiple users share the same server instance, as a single compromised user account can provide attackers with access to the entire computational environment. This vulnerability directly relates to CWE-352, which defines Cross-Site Request Forgery, and aligns with ATT&CK technique T1566, specifically the use of social engineering to execute code through web-based interfaces.
Organizations affected by this vulnerability should immediately implement mitigations including upgrading to IPython versions that address the CSRF protection issues, typically version 4.0 and later. The recommended approach involves ensuring that all REST API endpoints validate the presence of proper CSRF tokens in requests, implementing strict origin validation, and employing additional authentication mechanisms such as API keys or OAuth tokens. Network-level mitigations should include implementing proper access controls, restricting access to IPython servers to trusted networks, and deploying web application firewalls to detect and block suspicious API requests. Security teams should also conduct comprehensive vulnerability assessments to identify all instances of affected IPython versions within their environments and ensure that proper logging and monitoring are in place to detect potential exploitation attempts. The mitigation strategy should also include user education about the risks of visiting untrusted websites while authenticated to IPython servers, as well as implementing multi-factor authentication for administrative access to the IPython environment to reduce the overall risk surface.