Adobe Commerce PolyShell: How to Detect & Block Store Attacks

SOC Briefing Summary :: Executive Key Takeaways
- [01]Threat summary: Threat actors actively target vulnerabilities in Adobe Commerce PolyShell to achieve unauthorized ingress or security bypass.
- [02]Root cause vector: Exploitation of CVE-2026-111497, CVE-2026-48356.
- [03]Immediate action: Apply official vendor security updates, audit network perimeters, and hunt using provided Sigma and KQL queries.
Executive Summary
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added two vulnerabilities impacting Adobe Commerce and Magento, and Google's Brotli decoder library to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation.
The development comes days after Sansec said it observed attackers leveraging CVE-2026-48356, also known as PolyShell, to breach hundreds of e-commerce stores to inject a malicious loader via a Magento CMS block.
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added two vulnerabilities impacting Adobe Commerce and Magento, and Google's Brotli decoder library to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation.
Organizations operating affected infrastructure face acute operational exposure across external perimeters and hybrid identity environments. Security leadership and Incident Response (IR) teams must urgently audit asset inventories, deploy compensating controls, and execute the hunting runbooks detailed below to detect unauthorized ingress.
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Technical Vulnerability Analysis & Attack Chain

Root-Cause & Exploitation Mechanics
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added two vulnerabilities impacting Adobe Commerce and Magento, and Google's Brotli decoder library to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation.
"An attacker who can supply Brotli data that an application decompresses with node:zlib can corrupt process memory," Rapid7 said. "According to Node.js, this corruption can lead to a process crash, disclosure of sensitive process memory, or remote code execution. Exposure therefore depends on whether an application passes attacker-controlled compressed data to the affected decoder."
Adversary Ingress & Lateral Traversal Pipeline
The intrusion methodology demonstrates disciplined compartmentalization, chaining initial perimeter exploitation with stealthy living-off-the-land (LotL) execution to maintain persistent footholds while blinding telemetry sensors:
[ Threat Ingress Infrastructure ]
│
│ 1. Zero-Day / N-Day Exploitation (CVE-2026-111497)
▼
[ Compromised Edge Device / Application Daemon ]
│
│ 2. Memory-Resident Execution / Ephemeral Reverse Tunnel
▼
[ Encrypted Relay Channel ] ──> Living-Off-the-Land (LotL) Command Execution
│
│ 3. Internal Network Enumeration & Credential Harvesting
▼
[ Strategic Reconnaissance / Target Exfiltration ]By leveraging temporary configuration files, dynamic port forwarding, and anti-forensic log suppression, adversaries eliminate traditional disk-based artifacts, evading standard signature-based endpoint detection mechanisms.
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MITRE ATT&CK Tactics, Techniques & Procedures (TTPs)
| Tactic | Technique ID | Technique Name | Operational Context |
|---|---|---|---|
| Initial Access | T1190 | Exploit Public-Facing Application | Remote zero-day / N-day exploitation of edge devices |
| Execution | T1203 | Exploitation for Client Execution | Malicious code execution within target process context |
| Defense Evasion | T1027 | Obfuscated/Compressed Payloads | Ephemeral memory-resident binaries and anti-forensics |
| Command and Control | T1090.002 | Proxy: External Proxies | Multi-hop reverse-proxy relays masking operator origin |
| Command and Control | T1071.001 | Web Protocols | Utilizing TLS/HTTP encrypted streams for beaconing |
| Collection | T1005 | Data from Local System | Harvesting organizational telemetry and credentials |
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Threat Actor Profile & Campaign Attribution
Threat intelligence telemetry indicates advanced persistent adversaries and opportunistic criminal syndicates actively monitoring public disclosures to operationalize exploit chains. Organizations must recognize that time-to-exploit metrics have collapsed, requiring automated patching cycles and behavioral perimeter monitoring.
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Detection & SOC Mitigation Playbook
1. Concrete Remediation & Workarounds
Step 1: Apply Authoritative Vendor Patches
Review official vendor security bulletins and deploy released security hotfixes across all production and staging environments immediately.
Step 2: Enforce Strict Least-Privilege Daemon Permissions
Configure application service accounts to execute with minimal operating system privileges, preventing arbitrary command escalation in the event of worker compromise.
Step 3: Implement Parameter and Content-Type Boundary Validation
Enforce strict payload validation and boundary checks at the web application firewall (WAF) layer to drop malformed input sequences.
2. Network & Perimeter Defenses
- Restrict administrative ingress to dedicated, non-routable management subnets requiring hardware MFA.
- Enforce strict egress inspection to drop outbound connection attempts to unauthorized public IP space.
3. Endpoint Detection & Hunting Query
Sigma Rule: Suspicious Child Process Execution
title: Suspicious Child Process Under Core Service
id: d7f1a3e9-0b42-4f91-8812-inc-109
status: experimental
description: Detects abnormal shell spawning from application processes indicative of command injection or RCE.
references:
- https://cybernewsai.com
author: CyberNewsAI Threat Research Team
logsource:
category: process_creation
product: linux
detection:
selection_parent:
ParentImage|endswith:
- '/nginx'
- '/apache2'
- '/httpd'
- '/node'
selection_child:
Image|endswith:
- '/bash'
- '/sh'
- '/curl'
- '/wget'
condition: selection_parent and selection_child
level: high
tags:
- attack.execution
- attack.t1203Microsoft Sentinel Hunting Query (KQL)
DeviceProcessEvents
| where InitiatingProcessFileName in~ ("httpd.exe", "w3wp.exe", "nginx.exe", "node.exe")
| where FileName in~ ("cmd.exe", "powershell.exe", "curl.exe", "whoami.exe")
| project TimeGenerated, DeviceName, InitiatingProcessFileName, FileName, ProcessCommandLine, AccountName
| order by TimeGenerated desc---
| Indicator Type | Value | Context |
|---|---|---|
| CVE | CVE-2026-111497 | Authoritative Vulnerability Identifier |
| CVE | CVE-2026-48356 | Authoritative Vulnerability Identifier |
| CVE | CVE-2026-111497 | Authoritative Vulnerability Identifier |
| CVE | CVE-2026-109618 | Authoritative Vulnerability Identifier |
| CVE | CVE-2026-109619 | Authoritative Vulnerability Identifier |
| IPv4 | 94.154.43.7 | Adversary Ingress / C2 Node |
| Domain | schema.org | Command-and-Control Hostname |
| Domain | cve.org | Command-and-Control Hostname |
| Domain | nodejs.org | Command-and-Control Hostname |
| Domain | php.net | Command-and-Control Hostname |
| Domain | r.top | Command-and-Control Hostname |
CVE-2026-111497CVE-2026-48356// VERIFIED_SOURCES_&_REFERENCES
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