Post-Quantum Secure Feldmans Verifiable Secret Sharing provides a Python implementation of Feldmans 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 Pythons 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 Feldmans Verifiable Secret Sharing exist, but other mitigations are available. As acknowledged in the librarys 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.
The product behaves differently or sends different responses under different circumstances in a way that is observable to an unauthorized actor, which exposes security-relevant information about the state of the product, such as whether a particular operation was successful or not.