CVE-2016-0938 in Acrobat Reader
Summary
by MITRE
The AcroForm plugin in Adobe Reader and Acrobat before 11.0.14, Acrobat and Acrobat Reader DC Classic before 15.006.30119, and Acrobat and Acrobat Reader DC Continuous before 15.010.20056 on Windows and OS X allows attackers to execute arbitrary code or cause a denial of service (memory corruption) via unspecified vectors, a different vulnerability than CVE-2016-0931, CVE-2016-0933, CVE-2016-0936, CVE-2016-0939, CVE-2016-0942, CVE-2016-0944, CVE-2016-0945, and CVE-2016-0946.
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Analysis
by VulDB Data Team • 07/03/2022
The vulnerability described in CVE-2016-0938 represents a critical memory corruption flaw within the AcroForm plugin component of Adobe Reader and Acrobat software across multiple versions. This vulnerability affects Windows and macOS platforms and specifically targets the handling of unspecified input vectors within the plugin architecture. The flaw allows attackers to potentially execute arbitrary code or induce denial of service conditions through memory corruption techniques that exploit improper input validation mechanisms within the software's form processing capabilities.
The technical nature of this vulnerability stems from inadequate memory management and input validation within the AcroForm plugin's processing routines. When the plugin encounters malformed or specially crafted input data, it fails to properly validate the input before processing, leading to memory corruption that can be exploited by malicious actors. This type of vulnerability falls under the category of memory safety issues commonly associated with buffer overflows, heap corruption, or other memory manipulation attacks that have been extensively documented in cybersecurity literature. The vulnerability's classification aligns with CWE-121, which addresses stack-based buffer overflow conditions, and CWE-122, which covers heap-based buffer overflow scenarios, though the specific implementation details remain unspecified in the CVE description.
From an operational perspective, the impact of this vulnerability extends beyond simple denial of service to potentially enable full system compromise. Attackers could leverage this flaw to execute arbitrary code with the privileges of the affected application, potentially leading to complete system takeover. The vulnerability affects a broad range of Adobe products including both legacy versions and newer DC (Dynamic Content) releases, indicating that the underlying memory corruption issue has persisted across multiple software iterations. This widespread impact suggests that the vulnerability may be rooted in fundamental architectural design flaws within the plugin architecture rather than isolated implementation errors. The vulnerability's relationship to other CVEs in the same year indicates a pattern of security weaknesses within Adobe's PDF processing components, which aligns with common attack patterns documented in the MITRE ATT&CK framework under the T1059.007 technique for command and scripting interpreter.
The exploitation of this vulnerability typically requires social engineering to deliver malicious PDF files containing specially crafted AcroForm elements that trigger the memory corruption when the document is opened or interacted with. The attack surface is particularly concerning because PDF files are commonly used in business environments and can be easily distributed through email attachments, web downloads, or other common attack vectors. Organizations running affected versions of Adobe Reader or Acrobat should implement immediate mitigations including disabling the AcroForm plugin functionality, updating to patched versions, and implementing network-based protections such as web application firewalls and email filtering solutions. The vulnerability also highlights the importance of maintaining up-to-date software patches and implementing robust security monitoring to detect potential exploitation attempts. Given the nature of memory corruption vulnerabilities, traditional antivirus solutions may not detect exploitation attempts, making behavioral monitoring and network-based detection more critical for identifying potential compromise.