Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Mythic C2 over SMB Detection
Cortex XDR
This rule detects potential Mythic C2 activity communicating over SMB. It identifies network traffic using the SMB protocol with a total upload size greater than 360 bytes, originating from and destined for private IP address ranges. The rule then groups these connections by agent hostname, local IP, remote IP, and process image name, flagging instances where three or more such connections occur within a 7-day timeframe, indicating potential beaconing behavior.
This rule detects the use of bitsadmin to download specific Python scripts ('libsystemhealthcheck.py' or 'libcryptopydatasize.py') from the 'inspectguarantee.org' domain. This activity is associated with the COLDDRIVER (Star Blizzard) threat group, which uses BITSAdmin for ingress tool transfer.
Detects the DriverFixer0428 macOS credential stealer, attributed to the North Korean 'Contagious Interview' campaign. This rule identifies the malware based on unique internal strings, network IOCs related to Dropbox exfiltration, and social engineering text.
Detects a host initiating network connections to multiple unique domains within a short time frame using common tools and interpreters.
This can be indicative of C2 channel rotation, or network enumeration.
This rule is excluding certain cloud metadata services.
This rule requires a correlation engine to aggregate events over time.
This can be indicative of C2 channel rotation, or network enumeration.
This rule is excluding certain cloud metadata services.
This rule requires a correlation engine to aggregate events over time.
Detects the use of curl.exe to download content from a remote source and pipe it directly into PowerShell for execution. This is a fileless execution technique used by adversaries like Storm-0249 to bypass traditional file-based defenses.
This detection identifies network connections to known first-stage Microsoft 365 phishing domains associated with an active Adversary-in-the-Middle (AiTM) campaign.
This rule detects attempts to discover Group Policy settings on a Windows system. It identifies the execution of common command-line interpreters (cmd.exe, powershell.exe, wmic.exe, rundll32.exe) followed by specific commands or PowerShell cmdlets used for GPO enumeration. This includes native Windows commands like 'gpresult' and 'secedit', registry queries for policy settings, and PowerShell cmdlets such as 'Get-GPO' and 'Get-GPResultantSetOfPolicy'. Additionally, it looks for LDAP-related commands or patterns ('ldapsearch', 'groupPolicyContainer') that might indicate GPO discovery via directory services. The rule also correlates these process events with network connections to SYSVOL shares or LDAP ports (389, 636) to further confirm GPO-related activity.
Detects the legitimate Windows utility MSBuild.exe initiating any outbound network connections. MSBuild.exe is a software build tool and should not typically make network connections outside of development environments. This behavior is highly indicative of process hollowing, where malware injects itself into the MSBuild process to evade defenses, as seen in recent BlindEagle campaigns.
Detects outbound network connections to a list of IP addresses identified as high-confidence command and control (C2) infrastructure for the Clop ransomware group. This infrastructure has been observed across multiple campaigns, including the exploitation of vulnerabilities like CVE-2025-61882 (Oracle E-Business Suite), CVE-2023-34362 (MOVEit), and CVE-2023-0669 (GoAnywhere).
This rule query identifies likely post‑exploitation activity associated with React2Shell (CVE-2025-55182) in which Part 1 identifies web servers spawning unusual child processes (such as command shells or system utilities) combined with suspicious command-line patterns, which may indicate post-exploitation behavior following a compromise. and part 2 detects web servers making outbound network connections to known malicious IPs or hostnames, or to domains associated with tunneling services (e.g., trycloudflare.com), suggesting potential command-and-control activity or data exfiltration.
This rule detects suspicious network connections to known malicious URLs associated with a Docker Desktop malware campaign. It also identifies instances where 'DockerDesktop.exe' is executed or present in unusual file paths, suggesting potential masquerading or unauthorized deployment outside of its standard installation directory. The rule is broken into three parts: network events, file events, and process events. The network part looks for connections to specific malicious domains. The file and process parts look for 'DockerDesktop.exe' in folders other than the assumed legitimate installation path, indicating potential malicious activity.
This rule detects attempts to discover Group Policy settings on a system. It identifies the execution of common command-line interpreters (cmd.exe, powershell.exe, wmic.exe, rundll32.exe) followed by specific commands or PowerShell cmdlets used for GPO enumeration. This includes native Windows commands like 'gpresult' and 'secedit', registry queries for policy settings, PowerShell cmdlets such as 'Get-GPO' and 'Get-GPResultantSetOfPolicy', and LDAP-related queries for 'groupPolicyContainer'. Additionally, it correlates these process events with network connections to SYSVOL shares or LDAP ports (389, 636) that also contain 'groupPolicyContainer' in the URL, indicating potential GPO access. The rule filters out common system processes to reduce noise.
Detects potential exploitation of Oracle E-Business Suite vulnerability CVE-2025-61882, which allows for unauthenticated remote code execution. This rule looks for specific web request URIs, post-exploitation process activity, and known indicators of compromise (IOCs).
This rule detects applications, other than common web browsers, that are making network connections to Google Analytics domains and also contain 'microsoft' in the remote URL. This could indicate an application collecting device information or other telemetry and exfiltrating it via Google Analytics, potentially for malicious purposes or unauthorized data collection.
This rule detects WebSocket C2 authentication attempts by the Frogblight mobile banking malware. It specifically looks for the hardcoded login key '{"login_key":"fg_a1b2c3d4e5f6"}' within TCP traffic destined for external networks.
Detects Indicators of Compromise (IOCs) associated with React2Shell (CVE-2025-55182) exploitation attempts. This includes network connections to known malicious IP addresses, DNS queries for attacker-controlled domains, process creations involving suspicious command-line arguments (often related to downloading or executing scripts/binaries), and file hashes of known malicious artifacts. The exploit activity is linked to C2 communication, data exfiltration, and potentially cryptomining activities.
This rule detects instances where the calculator application (calc.exe) initiates a network connection. This behavior is highly unusual for a standard calculator application and could indicate malicious activity, such as an adversary using calc.exe as a proxy for network communication or injecting malicious code into it.
This rule detects Command and Control (C2) communication associated with the Mythic C2 framework utilizing Server Message Block (SMB) for peer-to-peer (P2P) beaconing. It specifically looks for SMB_COM_WRITE_ANDX commands with a data size greater than 360 bytes, containing a specific null byte pattern at offset 86, and a PCRE match for a GUID-like string, which are indicators of Mythic C2 SMB P2P beacon traffic.
This rule detects command and control (C2) beaconing activity associated with the SHADOW-VOID-042 malware family. Specifically, it looks for HTTP POST requests containing the string "get_module_hello" in the request body, which is indicative of a C2 communication pattern used by this malware.
Detects indicators of compromise (IOCs) associated with the GOLD BLADE threat group's July 2025 campaign, including file hashes and C2 domains.
Detects attempts to exploit CVE-2025-55182 (React) and CVE-2025-66478 (Next.js) utilizing data from the Imperva WAF leveraging vm#, child_process#, util_#, & fs_# indicators.
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