CVE-2021-42574 Detail

CVE-2021-42574

Score / Severity

8.3

High

CVE Descriptions

An issue was discovered in the Bidirectional Algorithm in the Unicode Specification through 14.0. It permits the visual reordering of characters via control sequences, which can be used to craft source code that renders different logic than the logical ordering of tokens ingested by compilers and interpreters. Adversaries can leverage this to encode source code for compilers accepting Unicode such that targeted vulnerabilities are introduced invisibly to human reviewers. NOTE: the Unicode Consortium offers the following alternative approach to presenting this concern. An issue is noted in the nature of international text that can affect applications that implement support for The Unicode Standard and the Unicode Bidirectional Algorithm (all versions). Due to text display behavior when text includes left-to-right and right-to-left characters, the visual order of tokens may be different from their logical order. Additionally, control characters needed to fully support the requirements of bidirectional text can further obfuscate the logical order of tokens. Unless mitigated, an adversary could craft source code such that the ordering of tokens perceived by human reviewers does not match what will be processed by a compiler/interpreter/etc. The Unicode Consortium has documented this class of vulnerability in its document, Unicode Technical Report #36, Unicode Security Considerations. The Unicode Consortium also provides guidance on mitigations for this class of issues in Unicode Technical Standard #39, Unicode Security Mechanisms, and in Unicode Standard Annex #31, Unicode Identifier and Pattern Syntax. Also, the BIDI specification allows applications to tailor the implementation in ways that can mitigate misleading visual reordering in program text; see HL4 in Unicode Standard Annex #9, Unicode Bidirectional Algorithm.

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-94	Improper Control of Generation of Code ('Code Injection') The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	8.3	HIGH	CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:H/A:H More informations Base: Exploitabilty Metrics The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component. Attack Vector This metric reflects the context by which vulnerability exploitation is possible. Network The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers). Attack Complexity This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. High successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected. Privileges Required This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability. None The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an 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 component. Required Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited. For example, a successful exploit may only be possible during the installation of an application by a system administrator. Base: Scope Metrics The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope. Scope Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs. Changed An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities. Base: Impact Metrics The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. 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 resources managed by a software component due to a successfully exploited vulnerability. High There is a total loss of confidentiality, resulting in all resources within the impacted component 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. Integrity refers to the trustworthiness and veracity of information. High There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component. Availability Impact This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. High There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable). Temporal Metrics The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability. Environmental Metrics These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.	[email protected]
V2	5.1		AV:N/AC:H/Au:N/C:P/I:P/A:P	[email protected]

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

EPSS First.org