CVE-2012-6124 in CHICKEN
Summary
by MITRE
A casting error in Chicken before 4.8.0 on 64-bit platform caused the random number generator to return a constant value. NOTE: the vendor states "This function wasn't used for security purposes (and is advertised as being unsuitable)."
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Analysis
by VulDB Data Team • 02/01/2024
The vulnerability identified as CVE-2012-6124 represents a critical implementation flaw in the Chicken Scheme interpreter version 4.8.0 and earlier, specifically affecting 64-bit platforms. This casting error fundamentally compromised the integrity of the random number generation functionality within the interpreter. The issue stems from improper type handling during the generation process, where the random number generator consistently returned identical values rather than producing the expected sequence of pseudo-random numbers. The vulnerability is particularly concerning because it affects a core component that many applications rely upon for various computational tasks, including simulations, cryptographic operations, and general algorithmic randomness requirements.
The technical root cause of this vulnerability lies in the improper casting of data types within the random number generation algorithm implementation. On 64-bit systems, the casting error manifests when the interpreter attempts to convert between different numeric representations, causing the generator to produce deterministic outputs instead of stochastic sequences. This flaw maps directly to CWE-191, which addresses integer underflow and overflow conditions, and CWE-194, which covers unexpected truncation of data types. The implementation error specifically affects the way the interpreter handles the conversion of floating-point values to integer representations during the random number generation process, creating a predictable pattern that undermines the fundamental purpose of random number generation.
The operational impact of this vulnerability extends beyond simple inconvenience, as it fundamentally compromises the reliability of any application or system that depends on the Chicken interpreter's random number generation capabilities. While the vendor explicitly states that this function was not intended for security purposes and is advertised as unsuitable for such use, the implications remain significant for applications that rely on pseudo-random number generation for simulation, testing, or algorithmic purposes. The constant return values can lead to predictable behavior in applications that depend on randomness, potentially causing systematic failures in testing environments, simulation accuracy, and overall system reliability. This vulnerability affects the broader ecosystem of applications built on Chicken Scheme, particularly those that utilize the interpreter for computational tasks requiring stochastic inputs.
Security practitioners should recognize this vulnerability as a potential indicator of broader code quality issues within the interpreter, suggesting that other components may also suffer from similar type handling errors. The vulnerability demonstrates the importance of thorough testing on target platforms, particularly 64-bit systems where type size differences can create subtle but critical implementation flaws. Organizations using Chicken Scheme should implement immediate mitigation strategies including updating to version 4.8.0 or later, which contains the necessary fixes for the casting error, and conducting comprehensive code reviews to identify similar type handling issues in custom extensions or applications built on top of the interpreter. Additionally, system administrators should monitor for applications that might be relying on this functionality and ensure proper version control measures are in place to prevent deployment of vulnerable interpreter versions.
The ATT&CK framework categorizes this vulnerability under software integrity threats, specifically relating to the manipulation of computational outputs and the potential for predictable system behavior. This weakness could be exploited by adversaries to gain insights into system operations or to craft targeted attacks against applications that depend on the compromised random number generation. While not inherently a security vulnerability in the traditional sense, the predictable behavior creates opportunities for exploitation in contexts where randomness is expected and required for proper system function. The vulnerability also highlights the importance of adhering to secure coding practices and the need for comprehensive testing across different platform architectures to prevent similar issues from manifesting in production environments.