CVE-2025-61622 in Fory
Summary
by MITRE • 10/01/2025
Deserialization of untrusted data in python in pyfory versions 0.12.0 through 0.12.2, or the legacy pyfury versions from 0.1.0 through 0.10.3: allows arbitrary code execution. An application is vulnerable if it reads pyfory serialized data from untrusted sources. An attacker can craft a data stream that selects pickle-fallback serializer during deserialization, leading to the execution of `pickle.loads`, which is vulnerable to remote code execution.
Users are recommended to upgrade to pyfory version 0.12.3 or later, which has removed pickle fallback serializer and thus fixes this issue.
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Analysis
by VulDB Data Team • 10/01/2025
The vulnerability identified as CVE-2025-61622 represents a critical deserialization flaw in the pyfory library that affects versions ranging from 0.12.0 through 0.12.2 and legacy versions from 0.1.0 through 0.10.3. This issue falls under the category of insecure deserialization as defined by CWE-502, where untrusted data is processed through deserialization mechanisms without proper validation or sanitization. The vulnerability specifically exploits the library's handling of serialized data streams that can trigger the selection of pickle fallback serialization during the deserialization process. This occurs when applications process pyfory serialized data from untrusted sources, creating a dangerous attack surface where malicious actors can manipulate data streams to execute arbitrary code on the target system.
The technical implementation of this vulnerability relies on the dangerous behavior of Python's pickle module, which is inherently unsafe when processing untrusted data. When pyfory encounters serialized data that cannot be handled by its primary serialization methods, it automatically falls back to using pickle for deserialization. This fallback mechanism creates a direct pathway for remote code execution attacks as demonstrated by the CVE-2025-61622 vulnerability. The attacker can craft a malicious data stream that, when processed by the vulnerable pyfory library, triggers the pickle.loads function call, which executes arbitrary Python code with the privileges of the running application. This type of vulnerability aligns with the ATT&CK technique T1203 - Exploitation for Execution, where adversaries leverage software vulnerabilities to execute malicious code.
The operational impact of CVE-2025-61622 extends beyond simple code execution, as it provides attackers with complete control over affected systems. Applications using vulnerable pyfory versions that process data from untrusted sources become potential entry points for attackers seeking to compromise entire infrastructure. The vulnerability is particularly concerning because it affects both newer and legacy versions of the library, meaning organizations with older systems or applications that have not been updated remain at risk. This widespread impact affects various deployment scenarios including web applications, data processing systems, and distributed computing environments where pyfory is used for serialization purposes. The risk is amplified when considering that pickle deserialization is commonly used in data exchange protocols and can be triggered through multiple attack vectors such as network communications, file processing, or API interactions.
Organizations affected by this vulnerability should immediately implement the recommended mitigation strategy of upgrading to pyfory version 0.12.3 or later, which addresses the issue by completely removing the pickle fallback serializer. This upgrade approach aligns with security best practices for vulnerability remediation as outlined in NIST SP 800-128 and other cybersecurity frameworks. Additionally, administrators should conduct comprehensive vulnerability assessments to identify all systems and applications that utilize affected pyfory versions, implementing network segmentation and access controls to limit exposure. The fix implemented in version 0.12.3 represents a fundamental architectural change that eliminates the dangerous fallback mechanism, thereby preventing the exploitation path that leads to remote code execution. Security teams should also consider implementing runtime monitoring and anomaly detection systems to identify potential exploitation attempts, as the vulnerability may be difficult to detect through traditional scanning methods due to its reliance on specific data stream manipulation techniques.