CVE-2025-29780

Post-Quantum Secure Feldman's Verifiable Secret Sharing provides a Python implementation of Feldman's Verifiable Secret Sharing (VSS) scheme. In versions 0.8.0b2 and prior, the `feldman_vss` library contains timing side-channel vulnerabilities in its matrix operations, specifically within the `_find_secure_pivot` function and potentially other parts of `_secure_matrix_solve`. These vulnerabilities are due to Python's execution model, which does not guarantee constant-time execution. An attacker with the ability to measure the execution time of these functions (e.g., through repeated calls with carefully crafted inputs) could potentially recover secret information used in the Verifiable Secret Sharing (VSS) scheme. The `_find_secure_pivot` function, used during Gaussian elimination in `_secure_matrix_solve`, attempts to find a non-zero pivot element. However, the conditional statement `if matrix[row][col] != 0 and row_random < min_value:` has execution time that depends on the value of `matrix[row][col]`. This timing difference can be exploited by an attacker. The `constant_time_compare` function in this file also does not provide a constant-time guarantee. The Python implementation of matrix operations in the _find_secure_pivot and _secure_matrix_solve functions cannot guarantee constant-time execution, potentially leaking information about secret polynomial coefficients. An attacker with the ability to make precise timing measurements of these operations could potentially extract secret information through statistical analysis of execution times, though practical exploitation would require significant expertise and controlled execution environments. Successful exploitation of these timing side-channels could allow an attacker to recover secret keys or other sensitive information protected by the VSS scheme. This could lead to a complete compromise of the shared secret. As of time of publication, no patched versions of Post-Quantum Secure Feldman's Verifiable Secret Sharing exist, but other mitigations are available. As acknowledged in the library's documentation, these vulnerabilities cannot be adequately addressed in pure Python. In the short term, consider using this library only in environments where timing measurements by attackers are infeasible. In the medium term, implement your own wrappers around critical operations using constant-time libraries in languages like Rust, Go, or C. In the long term, wait for the planned Rust implementation mentioned in the library documentation that will properly address these issues.
CVSS

No CVSS.

Configurations

No configuration.

History

19 Mar 2025, 16:15

Type Values Removed Values Added
Summary
  • (es) Post-Quantum Secure Feldman's Verifiable Secret Sharing proporciona una implementación en Python del esquema de Intercambio de Secretos Verificables (VSS) de Feldman. En las versiones 0.7.6b0 y anteriores, la librería `feldman_vss` contiene vulnerabilidades de canal lateral de temporización en sus operaciones matriciales, específicamente en la función `_find_secure_pivot` y posiblemente en otras partes de `_secure_matrix_solve`. Estas vulnerabilidades se deben al modelo de ejecución de Python, que no garantiza una ejecución en tiempo constante. Un atacante con la capacidad de medir el tiempo de ejecución de estas funciones (p. ej., mediante llamadas repetidas con entradas cuidadosamente diseñadas) podría recuperar información secreta utilizada en el esquema de Intercambio de Secretos Verificables (VSS). La función `_find_secure_pivot`, utilizada durante la eliminación gaussiana en `_secure_matrix_solve`, intenta encontrar un elemento pivote distinto de cero. Sin embargo, la sentencia condicional `if matrix[row][col] != 0 and row_random &lt; min_value:` tiene un tiempo de ejecución que depende del valor de `matrix[row][col]`. Esta diferencia de tiempo puede ser explotada por un atacante. La función `constant_time_compare` en este archivo tampoco proporciona una garantía de tiempo constante. La implementación de Python de las operaciones matriciales en las funciones _find_secure_pivot y _secure_matrix_solve no puede garantizar la ejecución en tiempo constante, lo que podría filtrar información sobre los coeficientes polinómicos secretos. Un atacante con la capacidad de realizar mediciones precisas de tiempo de estas operaciones podría extraer información secreta a través del análisis estadístico de los tiempos de ejecución, aunque la explotación práctica requeriría una experiencia significativa y entornos de ejecución controlados. La explotación exitosa de estos canales laterales de tiempo podría permitir a un atacante recuperar claves secretas u otra información confidencial protegida por el esquema VSS. Esto podría llevar a un compromiso completo del secreto compartido. Al momento de la publicación, no existían versiones parcheadas de la Intercambio de Secretos Verificables de Feldman con Seguridad Post-Cuántica, pero sí existen otras mitigaciones. Como se reconoce en la documentación de la librería, estas vulnerabilidades no se pueden abordar adecuadamente en Python puro. A corto plazo, considere usar esta librería solo en entornos donde las mediciones de tiempo por parte de los atacantes sean inviables. A mediano plazo, implemente sus propios envoltorios para operaciones críticas utilizando librerías de tiempo constante en lenguajes como Rust, Go o C. A largo plazo, espere la implementación planificada de Rust mencionada en la documentación de la librería, que abordará adecuadamente estos problemas.
Summary (en) Post-Quantum Secure Feldman's Verifiable Secret Sharing provides a Python implementation of Feldman's Verifiable Secret Sharing (VSS) scheme. In versions 0.7.6b0 and prior, the `feldman_vss` library contains timing side-channel vulnerabilities in its matrix operations, specifically within the `_find_secure_pivot` function and potentially other parts of `_secure_matrix_solve`. These vulnerabilities are due to Python's execution model, which does not guarantee constant-time execution. An attacker with the ability to measure the execution time of these functions (e.g., through repeated calls with carefully crafted inputs) could potentially recover secret information used in the Verifiable Secret Sharing (VSS) scheme. The `_find_secure_pivot` function, used during Gaussian elimination in `_secure_matrix_solve`, attempts to find a non-zero pivot element. However, the conditional statement `if matrix[row][col] != 0 and row_random < min_value:` has execution time that depends on the value of `matrix[row][col]`. This timing difference can be exploited by an attacker. The `constant_time_compare` function in this file also does not provide a constant-time guarantee. The Python implementation of matrix operations in the _find_secure_pivot and _secure_matrix_solve functions cannot guarantee constant-time execution, potentially leaking information about secret polynomial coefficients. An attacker with the ability to make precise timing measurements of these operations could potentially extract secret information through statistical analysis of execution times, though practical exploitation would require significant expertise and controlled execution environments. Successful exploitation of these timing side-channels could allow an attacker to recover secret keys or other sensitive information protected by the VSS scheme. This could lead to a complete compromise of the shared secret. As of time of publication, no patched versions of Post-Quantum Secure Feldman's Verifiable Secret Sharing exist, but other mitigations are available. As acknowledged in the library's documentation, these vulnerabilities cannot be adequately addressed in pure Python. In the short term, consider using this library only in environments where timing measurements by attackers are infeasible. In the medium term, implement your own wrappers around critical operations using constant-time libraries in languages like Rust, Go, or C. In the long term, wait for the planned Rust implementation mentioned in the library documentation that will properly address these issues. (en) Post-Quantum Secure Feldman's Verifiable Secret Sharing provides a Python implementation of Feldman's Verifiable Secret Sharing (VSS) scheme. In versions 0.8.0b2 and prior, the `feldman_vss` library contains timing side-channel vulnerabilities in its matrix operations, specifically within the `_find_secure_pivot` function and potentially other parts of `_secure_matrix_solve`. These vulnerabilities are due to Python's execution model, which does not guarantee constant-time execution. An attacker with the ability to measure the execution time of these functions (e.g., through repeated calls with carefully crafted inputs) could potentially recover secret information used in the Verifiable Secret Sharing (VSS) scheme. The `_find_secure_pivot` function, used during Gaussian elimination in `_secure_matrix_solve`, attempts to find a non-zero pivot element. However, the conditional statement `if matrix[row][col] != 0 and row_random < min_value:` has execution time that depends on the value of `matrix[row][col]`. This timing difference can be exploited by an attacker. The `constant_time_compare` function in this file also does not provide a constant-time guarantee. The Python implementation of matrix operations in the _find_secure_pivot and _secure_matrix_solve functions cannot guarantee constant-time execution, potentially leaking information about secret polynomial coefficients. An attacker with the ability to make precise timing measurements of these operations could potentially extract secret information through statistical analysis of execution times, though practical exploitation would require significant expertise and controlled execution environments. Successful exploitation of these timing side-channels could allow an attacker to recover secret keys or other sensitive information protected by the VSS scheme. This could lead to a complete compromise of the shared secret. As of time of publication, no patched versions of Post-Quantum Secure Feldman's Verifiable Secret Sharing exist, but other mitigations are available. As acknowledged in the library's documentation, these vulnerabilities cannot be adequately addressed in pure Python. In the short term, consider using this library only in environments where timing measurements by attackers are infeasible. In the medium term, implement your own wrappers around critical operations using constant-time libraries in languages like Rust, Go, or C. In the long term, wait for the planned Rust implementation mentioned in the library documentation that will properly address these issues.

14 Mar 2025, 18:15

Type Values Removed Values Added
New CVE

Information

Published : 2025-03-14 18:15

Updated : 2025-03-19 16:15


NVD link : CVE-2025-29780

Mitre link : CVE-2025-29780

CVE.ORG link : CVE-2025-29780


JSON object : View

Products Affected

No product.

CWE
CWE-203

Observable Discrepancy

CWE-208

Observable Timing Discrepancy

CWE-385

Covert Timing Channel