CVE-2017-16417 in Acrobat Reader
Summary
by MITRE
An issue was discovered in Adobe Acrobat and Reader: 2017.012.20098 and earlier versions, 2017.011.30066 and earlier versions, 2015.006.30355 and earlier versions, and 11.0.22 and earlier versions. This vulnerability occurs as a result of a computation that reads data that is past the end of the target buffer; the computation is a part of the font parsing module. The use of an invalid (out-of-range) pointer offset during access of internal data structure fields causes the vulnerability. A successful attack can lead to sensitive data exposure.
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Analysis
by VulDB Data Team • 09/03/2024
This vulnerability exists in Adobe Acrobat and Reader software versions prior to specific patches, affecting multiple release lines including 2017.012.20098, 2017.011.30066, 2015.006.30355, and 11.0.22. The flaw resides within the font parsing module where a buffer over-read condition occurs during the processing of malformed font files. The technical implementation involves a computation that calculates an offset beyond the boundaries of the target buffer, specifically when accessing internal data structure fields through an invalid pointer offset. This type of vulnerability falls under the category of buffer over-read as classified by CWE-125, which represents an out-of-bounds read condition where a program reads data past the end of a buffer. The vulnerability manifests when the application attempts to parse font data that has been crafted to exploit this specific behavior, leading to memory access violations that can potentially expose sensitive information stored in adjacent memory regions.
The operational impact of this vulnerability extends beyond simple memory corruption as it creates a potential information disclosure vector that attackers can leverage to extract sensitive data from the application's memory space. When an attacker successfully triggers this condition through a maliciously crafted PDF file containing malformed font data, the application's font parsing routine executes an out-of-bounds memory read operation that can reveal contents of adjacent memory locations. This memory exposure could potentially contain cryptographic keys, user credentials, application state information, or other sensitive data depending on the memory layout at the time of the read operation. The vulnerability demonstrates characteristics consistent with the attack pattern described in the attack technique T1059.007 for Windows Command Shell, where the exploitation involves memory corruption to achieve unauthorized data access, though this specific case operates at the application layer rather than system level. The exposure of sensitive data through such mechanisms represents a significant security risk that could compromise user privacy and system integrity.
Mitigation strategies for this vulnerability should focus on immediate patch deployment as provided by Adobe through their security bulletins and updates. Organizations should prioritize updating all affected Adobe Acrobat and Reader installations to versions that contain the patched font parsing module that properly validates buffer boundaries before accessing memory locations. Additionally, network administrators should implement defensive measures including email filtering to prevent the delivery of malicious PDF attachments that contain the crafted font data designed to trigger this vulnerability. The implementation of sandboxing mechanisms around PDF processing applications can provide an additional layer of protection by isolating the vulnerable parsing code from the rest of the system. Security monitoring should include detection of anomalous PDF processing behavior that might indicate exploitation attempts, while also ensuring that the system maintains proper patch management procedures to prevent similar vulnerabilities from remaining unaddressed. Compliance with industry standards such as those outlined in the OWASP Top Ten and NIST cybersecurity frameworks should be maintained to ensure comprehensive protection against this and similar memory corruption vulnerabilities that could be exploited to gain unauthorized access to sensitive information.