CVE-2017-15239 in IrfanView
Summary
by MITRE
IrfanView 4.44 - 32bit with PDF plugin version 4.43 allows attackers to cause a denial of service or possibly have unspecified other impact via a crafted .pdf file, related to "Data from Faulting Address may be used as a return value starting at PDF!xmlParserInputRead+0x0000000000040db4."
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Analysis
by VulDB Data Team • 11/24/2019
The vulnerability identified as CVE-2017-15239 affects IrfanView version 4.44 when used with the PDF plugin version 4.43, representing a critical denial of service condition that could potentially lead to more severe security implications. This flaw manifests when the application processes specifically crafted malicious pdf files, demonstrating a fundamental weakness in how the software handles input validation and memory management within its PDF parsing functionality. The vulnerability is particularly concerning as it operates at a low-level memory access point where faulting address data is improperly utilized as a return value during the xmlParserInputRead function execution.
The technical root cause of this vulnerability stems from improper handling of memory addresses during the parsing process of pdf documents, specifically within the PDF plugin's xml parsing component. When a malicious pdf file is processed, the xmlParserInputRead function at offset 0x000000000000040db4 encounters a faulting address that is subsequently used as a return value without proper validation or sanitization. This represents a classic case of memory corruption vulnerability where the application fails to properly validate input data before using it in critical operations. The issue aligns with CWE-125: Out-of-bounds Read and CWE-787: Out-of-bounds Write, indicating that the software does not adequately check array bounds or memory access patterns during pdf processing operations.
From an operational standpoint, this vulnerability presents significant risk to organizations relying on IrfanView for document handling, particularly in environments where users might encounter untrusted pdf content. The denial of service aspect means that legitimate users could be prevented from accessing documents, while the potential for unspecified other impacts suggests that attackers might be able to execute arbitrary code or escalate privileges. The vulnerability can be exploited through simple means, requiring only the delivery of a malicious pdf file to the target system, making it particularly dangerous in phishing campaigns or malware distribution scenarios.
The attack surface for this vulnerability extends beyond simple denial of service to include potential privilege escalation and remote code execution risks. According to ATT&CK framework, this vulnerability could be leveraged under technique T1203: Exploitation for Client Execution, where adversaries use malicious files to gain execution privileges. The vulnerability's location within the PDF plugin's xml parsing functionality makes it particularly attractive to attackers seeking to exploit the application's handling of external content. Organizations should consider this vulnerability in their threat modeling exercises, particularly in environments where users have access to potentially malicious documents or where the software is used in automated processing workflows.
Mitigation strategies should focus on immediate patching of the affected software versions, implementing strict file validation policies, and deploying network-based protections such as content filtering and sandboxing solutions. The recommended approach includes updating to the latest IrfanView version that addresses this specific vulnerability, implementing network segmentation to limit access to the vulnerable application, and establishing robust input validation procedures for all pdf processing activities. Additionally, organizations should consider implementing behavioral monitoring to detect unusual patterns that might indicate exploitation attempts, as the vulnerability's exploitation could manifest as unexpected application crashes or memory access violations that might be detectable through system monitoring tools.