CVE-2025-29780
17h26 +00:00
CVE 설명
Post-Quantum Secure Feldman's Verifiable Secret Sharing has Timing Side-Channels in Matrix Operations
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.CVE 정보
관련 약점
| 약점 이름 | 출처 | |
|---|---|---|
| Observable Discrepancy The product behaves differently or sends different responses under different circumstances in a way that is observable to an unauthorized actor. |
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| Observable Timing Discrepancy Two separate operations in a product require different amounts of time to complete, in a way that is observable to an actor and reveals security-relevant information about the state of the product, such as whether a particular operation was successful or not. |
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| Covert Timing Channel Covert timing channels convey information by modulating some aspect of system behavior over time, so that the program receiving the information can observe system behavior and infer protected information. |
메트릭
| 메트릭 | 점수 | 심각도 | CVSS 벡터 | 출처 |
|---|---|---|---|---|
| V4.0 | 5.8 | MEDIUM |
CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N
추가 정보
Base: Exploitabilty MetricsThe Exploitability metrics reflect the characteristics of the “thing that is vulnerable”, which we refer to formally as the vulnerable system. Attack Vector This metric reflects the context by which vulnerability exploitation is possible. Local The vulnerable system is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or through terminal emulation (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., using social engineering techniques to trick a legitimate user into opening a malicious document). Attack Complexity This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. High The successful attack depends on the evasion or circumvention of security-enhancing techniques in place that would otherwise hinder the attack. These include: Evasion of exploit mitigation techniques. The attacker must have additional methods available to bypass security measures in place. For example, circumvention of address space randomization (ASLR) or data execution prevention (DEP) must be performed for the attack to be successful. Obtaining target-specific secrets. The attacker must gather some target-specific secret before the attack can be successful. A secret is any piece of information that cannot be obtained through any amount of reconnaissance. To obtain the secret the attacker must perform additional attacks or break otherwise secure measures (e.g. knowledge of a secret key may be needed to break a crypto channel). This operation must be performed for each attacked target. Attack Requirements This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. Present The successful attack depends on the presence of specific deployment and execution conditions of the vulnerable system that enable the attack. These include: A race condition must be won to successfully exploit the vulnerability. The successfulness of the attack is conditioned on execution conditions that are not under full control of the attacker. The attack may need to be launched multiple times against a single target before being successful. Network injection. The attacker must inject themselves into the logical network path between the target and the resource requested by the victim (e.g. vulnerabilities requiring an on-path attacker). Privileges Required This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. Low The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources. User Interaction This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. None The vulnerable system can be exploited without interaction from any human user, other than the attacker. Examples include: a remote attacker is able to send packets to a target system a locally authenticated attacker executes code to elevate privileges Base: Impact MetricsThe Impact metrics capture the effects of a successfully exploited vulnerability. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve. Confidentiality Impact This metric measures the impact to the confidentiality of the information managed by the system due to a successfully exploited vulnerability. High There is a total loss of confidentiality, resulting in all information within the Vulnerable System being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server. Integrity Impact This metric measures the impact to integrity of a successfully exploited vulnerability. Low Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Vulnerable System. Availability Impact This metric measures the impact to the availability of the impacted system resulting from a successfully exploited vulnerability. None There is no impact to availability within the Vulnerable System. Sub Confidentiality Impact Negligible There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System. Sub Integrity Impact None There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System. Sub Availability Impact None There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System. Threat MetricsThe Threat metrics measure the current state of exploit techniques or code availability for a vulnerability. Environmental MetricsThese metrics enable the consumer analyst to customize the resulting score depending on the importance of the affected IT asset to a user’s organization, measured in terms of complementary/alternative security controls in place, Confidentiality, Integrity, and Availability. The metrics are the modified equivalent of Base metrics and are assigned values based on the system placement within organizational infrastructure. Supplemental MetricsSupplemental metric group provides new metrics that describe and measure additional extrinsic attributes of a vulnerability. While the assessment of Supplemental metrics is provisioned by the provider, the usage and response plan of each metric within the Supplemental metric group is determined by the consumer. |
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참고 자료
Tags : x_refsource_CONFIRM
