CVE-2026-21344
Adobe Substance 3D Stager vulnerability analysis and mitigation

Overview

CVE-2026-21344 is an out-of-bounds read vulnerability in Adobe Substance 3D Stager that can allow an attacker to execute arbitrary code in the context of the current user. It affects Substance 3D Stager versions 3.1.6 and earlier (all versions prior to 3.1.7). Adobe disclosed and patched this vulnerability on February 10, 2026. It carries a CVSS v3.1 base score of 7.8 (High) (Adobe Advisory).

Technical details

The vulnerability is classified as CWE-125 (Out-of-bounds Read) and is triggered during the parsing of a specially crafted file. When processing such a file, the application reads past the end of an allocated memory structure, which can be leveraged to achieve code execution. Exploitation requires local access and user interaction — specifically, a victim must be tricked into opening a malicious file — and no elevated privileges are required (Adobe Advisory).

Impact

Successful exploitation allows an unauthenticated attacker to execute arbitrary code in the context of the current user, potentially compromising confidentiality, integrity, and availability of the affected system. Since the attack vector is local and requires user interaction, the blast radius is limited to the victim's user session, but could enable further lateral movement if the compromised account has elevated privileges. No scope change beyond the affected application is expected based on the CVSS assessment (Adobe Advisory).

Exploitation steps

  1. Craft a malicious file: Prepare a specially crafted file (e.g., a Stager project file) that contains malformed data designed to trigger an out-of-bounds read during parsing.
  2. Deliver the file to the victim: Use social engineering techniques (phishing email, malicious download link, or shared file) to deliver the crafted file to a user running a vulnerable version of Adobe Substance 3D Stager (≤ 3.1.6).
  3. Victim opens the file: The victim opens the malicious file in Substance 3D Stager, triggering the vulnerable file parsing code path.
  4. Out-of-bounds read triggered: The parser reads past the end of an allocated memory buffer, potentially exposing sensitive memory contents or enabling memory corruption.
  5. Code execution achieved: The attacker leverages the memory disclosure or corruption to redirect execution flow and run arbitrary code in the context of the current user (Adobe Advisory).

Indicators of compromise

  • File System: Unexpected or unfamiliar Substance 3D Stager project files (e.g., .sbs, .sbsar, or proprietary Stager formats) received via email or downloaded from untrusted sources.
  • Process: Unusual child processes spawned by the Substance 3D Stager application process (e.g., cmd.exe, powershell.exe, bash, curl, or network-connecting processes).
  • Logs: Application crash logs or error reports from Substance 3D Stager referencing memory access violations or out-of-bounds read errors around file parsing operations.
  • Network: Unexpected outbound network connections originating from the Substance 3D Stager process to unknown external IP addresses shortly after opening a file.

Mitigation and workarounds

Adobe has released Substance 3D Stager version 3.1.7 to address this vulnerability; users should update immediately. As an interim workaround, users should avoid opening Stager files from untrusted or unknown sources. Organizations may also consider restricting file-opening permissions or applying application sandboxing where feasible (Adobe Advisory).

Community reactions

The Center for Internet Security (CIS) issued an advisory noting that multiple Adobe product vulnerabilities patched in February 2026, including this one, could allow for arbitrary code execution. Coverage has been limited to standard vulnerability tracking and aggregation platforms, with no notable independent researcher commentary or significant social media discussion observed, consistent with the low EPSS score and absence of active exploitation.

Additional resources


SourceThis report was generated using AI

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