Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects PHP web shells dropped into wp-content/uploads or plugin directories following WordPress plugin exploitation, characterized by host detail reporting and a browser-based file upload form
Detects attempts to exploit a vulnerability in WSO2 API Manager and Traffic Manager that allows for authentication bypass by utilizing a malformed JWT with the 'alg=none' header. Attackers can leverage this to impersonate users or bypass security controls by providing a crafted Bearer token in the Authorization header.
Detects high-frequency outbound TCP connection attempts from a WSO2 API Gateway or Traffic Manager host to multiple sensitive internal management and administrative ports (22, 445, 3389, 5985, 5986). This behavior is indicative of a compromised gateway being used for lateral movement across the network.
Detects download or installation attempts of specific trojanized versions (2.35 and 2.36) of the Admin Menu Editor Pro plugin, which were distributed via a compromised update channel on adminmenueditor.com.
This rule identifies instances of the Acronis backup plugin for cPanel, WHM, or Plesk running on versions older than 1.9.3 HF3. This versioning threshold corresponds to the patch level required to mitigate the security vulnerability identified as CVE-2026-87886.
Detects instances where a development-oriented web server (such as Vite or Node.js) is configured to bind to all network interfaces ('0.0.0.0') and is simultaneously receiving inbound connections from non-private, external IP addresses on a common development port (5173). This rule filters out common CI/CD environments to focus on potentially insecure exposure of development tools to the public internet.
Detects an exploitation attempt against the Vite Development Server (CVE-2026-39364) where an attacker uses specific query parameters to bypass file access restrictions and disclose sensitive files. The rule triggers on GET requests containing suspicious import-related query parameters and checks the resulting response to ensure a successful 200/206 status code and non-HTML content type.
Detects an exploitation attempt against the Vite Development Server (CVE-2026-39364) where an attacker uses specific query parameters to bypass file access restrictions and disclose sensitive files. The rule triggers on GET requests containing suspicious import-related query parameters and checks the resulting response to ensure a successful 200/206 status code and non-HTML content type.
Detects high-volume bursts of HTTP GET requests against specific paths associated with a Vite development server (/@vite/client, /@fs/, /src/) on port 5173. This pattern is indicative of automated reconnaissance or vulnerability scanning targeting an exposed development environment.
BigBear 2.0 IOC HUNT (Cortex XDR)
Cortex XDR
CloudSEK researchers uncovered BigBear 2.0, a global Microsoft 365 phishing-as-a-service operation targeting hundreds of organizations across 40+ countries. The investigation exposed the attacker’s admin panel, affiliate network, phishing infrastructure, and thousands of stolen credentials and session cookies, revealing how modern AiTM attacks can hijack authenticated sessions even after MFA.
Detects incoming HTTP requests attempting to exploit a path traversal vulnerability in the GitLab Commits API (CVE-2026-85706). The rule looks for URI patterns containing directory traversal sequences (e.g., ../) targeting the repository commits endpoint.
Detects unauthenticated path traversal attempts targeting the GitLab repository commits API, specifically checking for URL-encoded and plain path traversal patterns (e.g., '../') in requests to the commits endpoint. This behavior is indicative of attempts to exploit vulnerabilities like CVE-2026-85706 to read arbitrary files outside the repository scope.
Detects process creation events containing command-line arguments indicative of an OAuth 2.0 device code flow, commonly used in consent phishing or device code phishing attacks to hijack account access via a malicious OAuth application registration.
Matches known HOOKEDGE malware samples attributed to BlueDelta (APT28) via SHA256 hash comparison
Matches known HOOKEDGE malware samples attributed to BlueDelta (APT28) via SHA256 hash comparison
This rule monitors network connections and DNS queries directed towards Microsoft's OAuth device code authorization endpoints ('/common/oauth2/deviceauth' or '/device'). This flow is frequently abused by adversaries to perform device code phishing, allowing them to gain access to a victim's account without requiring the user's password or bypassing traditional MFA.
Detects suspicious Python execution patterns commonly associated with web shells or remote code execution, originating from typical web server or application middleware processes (e.g., w3wp, nginx, httpd, tomcat). The detection triggers on specific patterns including base64-encoded command execution, Python evaluation of base64-encoded strings, or long alphanumeric command-line strings suggesting obfuscated code execution.
Detects the use of common command-line utilities to search for sensitive files, including credential files (.env, credentials.json, database.yml), wallet files (wallet.dat), and mnemonic/seed phrases. This activity is often associated with reconnaissance for credentials or sensitive data on compromised Linux systems.
The rule detects the deletion of specific log files ('Udydn.out', 'server.log', or 'derby.log') which are often associated with application operations or internal debugging. Adversaries may delete these logs to conceal their activities, remove indicators of compromise, or interfere with forensic analysis.
Detects potential command and control (C2) beaconing activity to GitHub repository API endpoints. The rule monitors for a high frequency of requests to specific file names commonly associated with C2 payloads (e.g., command.txt, results.txt, heartbeat.txt) and employs statistical analysis to identify consistent, non-random connection patterns that deviate from expected business usage.
Detects a Golang-based remote access trojan (RAT) attributed to the Transparent Tribe (APT36) threat group. The rule identifies the malware based on distinctive fitness-themed C2 API endpoints, specific function names, hardcoded authentication secrets, and embedded Go runtime markers, while also monitoring for associated persistence registry keys and file paths.
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