CVE-2017-18342 in PyYAML
Summary
by MITRE
In PyYAML before 4.1, the yaml.load() API could execute arbitrary code. In other words, yaml.safe_load is not used.
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Analysis
by VulDB Data Team • 03/29/2023
The vulnerability identified as CVE-2017-18342 represents a critical security flaw in the PyYAML library version 4.1 and earlier, where the default yaml.load() function lacks proper input validation and sanitization mechanisms. This vulnerability falls under the category of code injection attacks and is classified as CWE-94, which describes the execution of arbitrary code or commands. The issue stems from the library's default behavior of allowing deserialization of arbitrary Python objects, which creates an opportunity for malicious actors to execute unintended code when processing untrusted YAML input. When developers use yaml.load() instead of the safer yaml.safe_load() function, they inadvertently expose their applications to remote code execution risks.
The technical exploitation of this vulnerability occurs through the manipulation of YAML input data that contains serialized Python objects. Attackers can craft malicious YAML payloads that, when processed by yaml.load(), will execute arbitrary Python code on the target system. This typically involves creating YAML structures that reference Python classes or functions that can be executed during the deserialization process. The vulnerability is particularly dangerous because it allows attackers to leverage the full power of the Python interpreter, potentially enabling them to read files, execute system commands, access network resources, or perform other malicious activities. The flaw exists at the core of how the library handles untrusted input, making it a fundamental security issue that affects any application using the vulnerable version of PyYAML.
The operational impact of CVE-2017-18342 extends beyond simple code execution, as it can lead to complete system compromise and data breaches. Applications that rely on PyYAML for configuration management, data processing, or user input handling become vulnerable to remote code execution attacks. This vulnerability has been classified under the MITRE ATT&CK framework as part of the T1059 technique, which involves executing malicious code through command and scripting interpreters. The risk is particularly high in web applications where user input is processed through YAML parsers, as attackers can exploit this vulnerability to gain unauthorized access to backend systems. Organizations using vulnerable versions of PyYAML may face significant security implications, including potential data loss, system compromise, and regulatory compliance violations.
Mitigation strategies for CVE-2017-18342 focus on immediate remediation and architectural improvements to prevent future occurrences. The primary recommendation is to upgrade to PyYAML version 4.1 or later, where the library has been patched to properly handle untrusted input and prevent arbitrary code execution. Additionally, developers should implement the principle of least privilege by using yaml.safe_load() instead of yaml.load() when processing untrusted data. Organizations should conduct comprehensive code reviews to identify all instances of yaml.load() usage and replace them with safer alternatives. Security monitoring should be implemented to detect potential exploitation attempts, and application firewalls or intrusion detection systems should be configured to block suspicious YAML parsing activities. The vulnerability also highlights the importance of proper input validation and the need for security awareness training to prevent developers from inadvertently using insecure functions in their applications.