CVE-2019-8741 in iCloud
Summary
by MITRE
A denial of service issue was addressed with improved input validation.
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Analysis
by VulDB Data Team • 03/01/2020
The vulnerability identified as CVE-2019-8741 represents a denial of service weakness that emerged within a software system's input processing mechanisms. This issue specifically manifested when the application failed to adequately validate user-supplied data before processing it through internal functions. The root cause lies in insufficient sanitization of input parameters that could potentially contain malformed or malicious content designed to exploit the system's processing logic. Such vulnerabilities typically arise when developers assume that all input will conform to expected formats without implementing proper validation checks. The weakness creates an opportunity for attackers to disrupt normal system operations by submitting carefully crafted input that triggers unexpected behavior in the application's processing pipeline.
The technical flaw underlying CVE-2019-8741 operates through a lack of proper input validation controls that should have been implemented at multiple layers of the application architecture. When the system receives input that deviates from expected patterns or contains unexpected characters, the absence of robust validation mechanisms allows the data to proceed unchecked into processing functions where it can cause the application to crash, hang, or otherwise become unresponsive. This type of vulnerability falls under the broader category of improper input validation issues that are commonly categorized as CWE-20 - Improper Input Validation within the Common Weakness Enumeration framework. The vulnerability's impact is particularly concerning because denial of service attacks can effectively render systems unusable to legitimate users while remaining relatively simple to execute.
The operational impact of CVE-2019-8741 extends beyond immediate system unavailability to encompass broader business continuity concerns and potential reputational damage. When an attacker successfully exploits this vulnerability, they can cause sustained disruption to service availability, potentially affecting multiple users simultaneously depending on the system's architecture and the scope of the vulnerable component. The attack vector typically involves sending specially crafted input through application interfaces such as web forms, api endpoints, or network protocols that the vulnerable software component processes. Organizations may experience cascading effects where the denial of service impacts related systems or services that depend on the compromised application, creating wider operational disruptions. From an attacker's perspective, this vulnerability represents a low-effort, high-impact method for causing system disruption.
Mitigation strategies for CVE-2019-8741 should focus on implementing comprehensive input validation mechanisms across all application interfaces and processing points. The most effective approach involves deploying strict validation rules that filter out unexpected input patterns, implement proper data type checking, and enforce length limitations for all user-supplied parameters. Organizations should establish robust sanitization procedures that normalize input data before processing, ensuring that potentially harmful content is either removed or properly escaped. Security teams should implement automated testing procedures including fuzz testing to identify potential edge cases that could trigger similar vulnerabilities. Additionally, the remediation process should include thorough code reviews to identify all input handling points and ensure consistent application of validation controls throughout the software stack. This vulnerability aligns with attack patterns documented in the MITRE ATT&CK framework under the T1499 category for network denial of service attacks, emphasizing the importance of robust input validation as a foundational security control. The implementation of these mitigations should be complemented by monitoring systems that can detect anomalous input patterns and alert security teams to potential exploitation attempts.