CVE-2017-7602 in LibTIFF
Summary
by MITRE
LibTIFF 4.0.7 has a signed integer overflow, which might allow remote attackers to cause a denial of service (application crash) or possibly have unspecified other impact via a crafted image.
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Analysis
by VulDB Data Team • 11/28/2022
The vulnerability identified as CVE-2017-7602 represents a critical signed integer overflow flaw within LibTIFF version 4.0.7, a widely deployed library for handling tagged image file format files across numerous operating systems and applications. This vulnerability resides in the library's image parsing mechanisms where it fails to properly validate integer values during memory allocation calculations, creating a scenario where maliciously crafted image files can trigger unexpected behavior in the processing applications. The flaw specifically manifests when the library attempts to calculate memory requirements for image data structures, where signed integer arithmetic overflow occurs, potentially leading to memory corruption or application instability.
The technical nature of this vulnerability places it squarely within the CWE-190 category of Integer Overflow or Wraparound, which is classified as a fundamental weakness in software systems that can lead to severe security implications. When a malicious actor crafts an image file with carefully manipulated dimensions or metadata fields, the library's internal calculations can produce negative or excessively large values that exceed the bounds of normal integer representation. This overflow condition can cause the application to allocate insufficient memory or attempt to access invalid memory regions, resulting in segmentation faults, application crashes, or potentially more severe consequences depending on the specific context in which the library is used. The vulnerability is particularly dangerous because it can be triggered remotely through image processing operations in web browsers, image viewers, or any application that relies on LibTIFF for image handling.
The operational impact of CVE-2017-7602 extends beyond simple denial of service scenarios, as it can potentially enable more sophisticated attacks depending on the execution environment. In web-based contexts, this vulnerability allows remote attackers to execute denial of service attacks against web applications that process user-uploaded images, effectively creating a vector for service disruption attacks. The potential for unspecified other impacts suggests that under certain conditions, this vulnerability could be exploited to achieve arbitrary code execution or privilege escalation, particularly in environments where the vulnerable library is used in security-critical applications or where memory corruption could be leveraged for further exploitation. The vulnerability affects a broad ecosystem since LibTIFF is integrated into numerous applications including web browsers, image processing software, and server applications, making the potential attack surface extensive.
Mitigation strategies for CVE-2017-7602 should focus on immediate library updates to versions that contain patched integer overflow protections and input validation mechanisms. System administrators should prioritize patching affected applications that utilize LibTIFF, particularly those handling untrusted image data from external sources. Network defenders should implement content filtering mechanisms to block suspicious image files and establish monitoring for unusual application crash patterns that might indicate exploitation attempts. The vulnerability aligns with ATT&CK technique T1203, which involves the use of malicious files to gain initial access or cause system instability, making it particularly relevant for defensive strategies focused on file validation and application sandboxing. Organizations should also consider implementing application whitelisting policies and restricting image processing capabilities in public-facing applications to minimize exposure. Regular vulnerability assessments and security audits of third-party libraries should be conducted to identify and remediate similar integer overflow conditions that may exist in other components of the software stack.