CVE-2017-14540 in IrfanView
Summary
by MITRE
IrfanView 4.44 - 32bit allows attackers to cause a denial of service or possibly have unspecified other impact via a crafted .svg file, related to "Data from Faulting Address controls Branch Selection starting at CADIMAGE+0x000000000001f23e."
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Analysis
by VulDB Data Team • 11/17/2019
The vulnerability identified as CVE-2017-14540 affects IrfanView version 4.44 32-bit installations and represents a critical denial of service condition that could potentially lead to more severe security implications. This flaw manifests when the image viewer processes specially crafted malicious svg files, demonstrating a classic buffer overflow or memory corruption vulnerability that stems from improper input validation mechanisms within the software's image parsing routines. The vulnerability specifically relates to how the application handles data from faulting addresses during branch selection processes, indicating a sophisticated memory management issue that could be exploited to disrupt normal application operation.
The technical exploitation of this vulnerability occurs through manipulation of the CADIMAGE+0x00000000000001f23e memory address during the image processing workflow, which suggests that attackers can control the execution flow of the application by injecting malformed data into the svg parsing pipeline. This type of vulnerability aligns with CWE-125 Out-of-bounds Read and CWE-787 Out-of-bounds Write classifications, as the application fails to properly validate memory boundaries during image rendering operations. The faulting address mechanism indicates that the vulnerability involves conditional branch prediction and execution control flow manipulation, where the attacker can influence the program's decision-making process through crafted input data.
From an operational impact perspective, this vulnerability presents significant risks to end-user systems and enterprise environments that rely on IrfanView for image viewing operations. The denial of service condition can be triggered simply by opening a malicious svg file, potentially affecting users across various operating systems and applications that integrate with IrfanView for image handling. The unspecified other impacts mentioned in the vulnerability description suggest that beyond simple service disruption, attackers may be able to execute arbitrary code or escalate privileges, particularly given the nature of memory corruption vulnerabilities that affect branch selection mechanisms. This vulnerability could be particularly dangerous in environments where automated image processing or batch operations are common, as a single malicious file could compromise entire systems or networks.
Security mitigations for this vulnerability should include immediate patching of IrfanView installations to version 4.45 or later, which contains the necessary fixes for the memory handling routines. Organizations should implement strict file validation protocols for all svg files entering their systems, including sandboxed processing environments and content inspection tools that can detect malformed svg structures before they reach the vulnerable application. Network administrators should consider implementing file type restrictions and content filtering mechanisms to prevent malicious svg files from being processed by vulnerable applications. Additionally, system hardening measures such as address space layout randomization and data execution prevention should be enabled to reduce the effectiveness of potential exploitation attempts. The vulnerability also highlights the importance of maintaining up-to-date software versions and implementing comprehensive vulnerability management programs that can quickly respond to emerging threats. This case demonstrates the critical need for proper input validation and memory safety practices in image processing applications, as these components often handle untrusted data from external sources and require robust defensive mechanisms against various attack vectors including those targeting execution flow control and memory management systems.