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RSA weakness in tslite-ng

High severity GitHub Reviewed Published Dec 18, 2020 in tlsfuzzer/tlslite-ng • Updated Nov 13, 2024

Package

pip tlslite-ng (pip)

Affected versions

< 0.7.6

Patched versions

0.7.6

Description

Impact

The code that performs decryption and padding check in RSA PKCS#1 v1.5 decryption is data dependant.
In particular, code in current (as of 0.8.0-alpha38) master
https://github.com/tlsfuzzer/tlslite-ng/blob/0812ed60860fa61a6573b2c0e18771414958f46d/tlslite/utils/rsakey.py#L407-L441
and code in 0.7.5 branch
https://github.com/tlsfuzzer/tlslite-ng/blob/acdde3161124d6ae37c506b3476aea9996d12e97/tlslite/utils/rsakey.py#L394-L425
has multiple ways in which it leaks information (for one, it aborts as soon as the plaintext doesn't start with 0x00, 0x02) about the decrypted ciphertext (both the bit length of the decrypted message as well as where the first unexpected byte lays).

All TLS servers that enable RSA key exchange as well as applications that use the RSA decryption API directly are vulnerable.

All previous versions of tlslite-ng are vulnerable.

Patches

The patches to fix it are proposed in
tlsfuzzer/tlslite-ng#438
tlsfuzzer/tlslite-ng#439

Note: the patches depend on Python processing the individual bytes in side-channel free manner, this is known to not be the case: https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/
As such, users that require side-channel resistance are recommended to use different TLS implementations, as stated in the security policy of tlslite-ng.

Workarounds

There is no way to workaround this issue.

References

https://securitypitfalls.wordpress.com/2018/08/03/constant-time-compare-in-python/

For more information

If you have any questions or comments about this advisory please open an issue in tlslite-ng.

References

@tomato42 tomato42 published to tlsfuzzer/tlslite-ng Dec 18, 2020
Reviewed Dec 21, 2020
Published to the GitHub Advisory Database Dec 21, 2020
Last updated Nov 13, 2024

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
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. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
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. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

EPSS score

0.604%
(78th percentile)

Weaknesses

CVE ID

CVE-2020-26263

GHSA ID

GHSA-wvcv-832q-fjg7

Source code

Credits

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