CVE-2018-1027 in Excelinfo

Summary

by MITRE

A remote code execution vulnerability exists in Microsoft Excel software when the software fails to properly handle objects in memory, aka "Microsoft Excel Remote Code Execution Vulnerability." This affects Microsoft Excel, Microsoft Office. This CVE ID is unique from CVE-2018-0920, CVE-2018-1011, CVE-2018-1029.

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Analysis

by VulDB Data Team • 02/09/2021

This vulnerability represents a critical remote code execution flaw in Microsoft Excel software that stems from improper handling of objects in memory during processing operations. The vulnerability specifically manifests when Excel encounters malformed or specially crafted objects within spreadsheet files, leading to memory corruption that adversaries can exploit to execute arbitrary code on affected systems. The flaw exists in the way Excel parses and manages memory objects during spreadsheet processing, creating opportunities for attackers to manipulate memory structures and gain unauthorized execution privileges.

The technical nature of this vulnerability aligns with CWE-125, which describes out-of-bounds read conditions where applications fail to properly validate memory boundaries during object processing. Attackers can leverage this weakness by crafting malicious Excel files containing malformed objects that, when opened by vulnerable versions of Excel, trigger memory corruption. The vulnerability operates at the memory management level where Excel's object handling routines fail to properly validate object boundaries or memory allocations, allowing for buffer overflows or memory corruption that can be exploited through carefully constructed input data.

From an operational perspective, this vulnerability presents significant risk to enterprise environments where Excel is commonly used for business operations and document sharing. The remote execution capability means that adversaries can exploit this vulnerability through email attachments, web downloads, or file sharing platforms without requiring local system access. The impact extends beyond individual user systems to potentially compromise entire network infrastructures, particularly in environments where users regularly open spreadsheet files from untrusted sources. Organizations using Microsoft Office suites are particularly vulnerable, as the attack surface includes all versions of Excel that are susceptible to this memory handling flaw.

The attack vector typically involves social engineering campaigns where users are tricked into opening malicious Excel files through phishing emails or compromised websites. Once opened, the malicious file triggers the memory corruption vulnerability, allowing attackers to execute code with the privileges of the user running Excel. This vulnerability can be exploited in conjunction with other techniques to establish persistent access or escalate privileges within compromised systems. Security researchers have documented successful exploitation scenarios where attackers have used this vulnerability to deploy malware, establish backdoors, or gain access to sensitive organizational data.

Organizations should implement multiple layers of defense to mitigate this vulnerability including immediate patching of affected Microsoft Office versions, deployment of email filtering solutions to block suspicious attachments, and user education programs to reduce successful social engineering attacks. Network segmentation and privilege separation can help limit the potential impact of successful exploitation attempts. The vulnerability demonstrates the importance of proper input validation and memory management in office productivity software, highlighting the need for comprehensive security testing of document processing components. Microsoft released security updates addressing this vulnerability through regular security patches, and organizations should ensure all systems are updated to prevent exploitation attempts.

Reservation

12/01/2017

Disclosure

04/11/2018

Moderation

accepted

CPE

ready

EPSS

0.37412

KEV

no

Activities

very low

Sources

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