CVE-2026-114197 in Capa
Summary
by MITRE • 10/21/2026
Deserialization of untrusted data in Mandiant FLARE capa releases before 10.0.0 allows arbitrary code execution when a crafted .viv or .exe.viv workspace is passed to the capa utility
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Analysis
by VulDB Data Team • 10/21/2026
The vulnerability identified as CVE-2024-36598 represents a critical security flaw within Mandiant FLARE capa, specifically affecting versions prior to 10.0.0. This issue stems from improper handling of untrusted data during the deserialization process, which is a common attack vector for achieving arbitrary code execution in software applications that rely on object serialization formats such as Python's pickle module or similar mechanisms. The vulnerability manifests when an attacker provides a maliciously crafted .viv file or an executable with a .exe.viv extension to the capa utility. These files are typically used by capa to store workspace data, including analysis results and metadata associated with specific binary samples. When the tool processes these files without adequate validation or sanitization of their contents, it inadvertently executes code embedded within the serialized objects, leading to remote code execution under the context of the user running the application.
From a technical perspective, this flaw aligns closely with CWE-502, which describes Deserialization of Untrusted Data. The core issue lies in the assumption that workspace files originate from trusted sources or have been properly validated before being loaded into memory. In reality, attackers can craft payloads that exploit specific deserialization routines to instantiate arbitrary objects and invoke dangerous methods during the unpickling process. This allows for full control over the application's execution flow, enabling the attacker to execute system commands, exfiltrate sensitive data, or pivot further within a network environment depending on the privileges of the compromised user account. The attack does not require complex exploitation techniques beyond crafting a malicious serialized object that triggers the vulnerable code path during file loading.
The operational impact of this vulnerability is severe due to its potential for remote code execution without authentication if users are tricked into opening malicious workspace files, or local privilege escalation if an attacker gains access to modify existing workspaces on a shared system. Security analysts and reverse engineers who frequently use capa may inadvertently load compromised artifacts during routine analysis workflows, especially when collaborating with external partners or processing samples from untrusted sources. This undermines the integrity of security assessments and could lead to broader compromise of development environments where such tools are commonly deployed for malware analysis and threat intelligence gathering.
Mitigation strategies primarily involve upgrading to Mandiant FLARE capa version 10.0.0 or later, which addresses this deserialization flaw by implementing stricter input validation and potentially switching to safer serialization formats that do not allow arbitrary code execution during loading. Until an upgrade is feasible, users should exercise extreme caution when handling workspace files from unknown origins, avoiding the use of such tools in untrusted environments. Additionally, employing application whitelisting or sandboxing techniques can limit the impact if a malicious file is processed inadvertently. Security teams should also monitor for any indicators of compromise related to unusual process creation patterns originating from capa executions, as this may signal active exploitation attempts against vulnerable instances within their infrastructure.
This incident highlights the broader industry challenge associated with deserialization vulnerabilities and reinforces the importance of adhering to secure coding practices that prioritize input validation and safe data handling protocols. Organizations relying on static analysis tools must ensure they maintain up-to-date software versions and enforce strict policies regarding the ingestion of external artifacts into security toolchains. Awareness training for analysts working with dynamic or semi-dynamic analysis platforms can further reduce risk by promoting cautious behavior when interacting with files from unverified sources, thereby minimizing exposure to such high-severity flaws in widely used cybersecurity utilities.