Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects high-volume API call patterns targeting Google Gemini/Vertex AI services originating from a small, coordinated set of user accounts. This behavior may indicate an automated actor cluster, such as those leveraging generative AI to rapidly generate content for phishing kits or other malicious purposes.
Detects anomalous activity associated with AI and LLM service providers by identifying accounts that are either interacting with these services for the first time or exhibiting a significant spike in API call volume compared to their 14-day historical baseline. This pattern may indicate unauthorized use of enterprise AI resources, potential persistence mechanisms, or exfiltration activities abusing legitimate LLM orchestration APIs.
This rule detects network connections to known cryptomining pool IP addresses and domain names, as well as file or process executions matching specific hashes associated with known miner samples. It monitors for communication to command-and-control (C2) servers potentially used for cryptomining operations.
Detects activity associated with the 'MovieReaper' threat campaign by identifying known malicious file hashes, command and control (C2) IP addresses, and communication with identified malicious domains. This rule monitors process execution, file operations, and network connections within the campaign's active timeframe.
This rule monitors for outbound network connections to domains and IP addresses associated with known phishing, loader, and C2 infrastructure, including specific ClickFix patterns.
This rule detects network traffic patterns associated with the Sauron Loader malware family. It specifically identifies outbound HTTPS beaconing to known malicious C2 domains using the TLS SNI (Server Name Indication) field.
Detects instances where PowerShell scripts are executed via the Windows Task Scheduler from within potential staging directories (ProgramData with randomized folder names). The rule identifies execution that uses common PowerShell obfuscation flags (e.g., -EncodedCommand) and requires secondary hardening bypass flags (e.g., -WindowStyle hidden), followed by correlated network activity to a specific suspicious C2 domain.
Detects instances where PowerShell scripts are executed via the Windows Task Scheduler from within potential staging directories (ProgramData with randomized folder names). The rule identifies execution that uses common PowerShell obfuscation flags (e.g., -EncodedCommand) and requires secondary hardening bypass flags (e.g., -WindowStyle hidden), followed by correlated network activity to a specific suspicious C2 domain.
Detects instances where PowerShell scripts are executed via the Windows Task Scheduler from within potential staging directories (ProgramData with randomized folder names). The rule identifies execution that uses common PowerShell obfuscation flags (e.g., -EncodedCommand) and requires secondary hardening bypass flags (e.g., -WindowStyle hidden), followed by correlated network activity to a specific suspicious C2 domain.
Detects Python processes (python.exe, python3.exe, pythonw.exe) performing DNS resolution for Microsoft identity, device login, or Graph API endpoints. This activity is consistent with automated tooling, such as python-requests, performing device-code flow polling or API token authentication within an environment.
Detects anomalous HTTP POST requests to a suspected C2 endpoint ('/beacon/pre-register') on a typosquatted domain ('thecovnresation') characterized by an application/octet-stream content type, which is indicative of encrypted C2 beacon registration activity.
Detects anomalous HTTP POST requests to a suspected C2 endpoint ('/beacon/pre-register') on a typosquatted domain ('thecovnresation') characterized by an application/octet-stream content type, which is indicative of encrypted C2 beacon registration activity.
Detects anomalous HTTP POST requests to a suspected C2 endpoint ('/beacon/pre-register') on a typosquatted domain ('thecovnresation') characterized by an application/octet-stream content type, which is indicative of encrypted C2 beacon registration activity.
This rule detects potentially malicious activity where a Python-based process or a PyInstaller-compiled executable invokes a command shell (cmd.exe, powershell.exe) or command execution via 'os.popen', followed by a network connection to 'api.telegram.org' within a 60-second window. This behavior is often characteristic of malware or tools using Telegram's API as a command-and-control (C2) channel or for data exfiltration.
Detects network activity associated with the AMOS (Atomic macOS Stealer) malware, specifically identifying C2 communication patterns such as heartbeat beacons and agent tasking requests occurring over non-standard port 8133.
Detects network activity associated with the AMOS (Atomic macOS Stealer) malware, specifically identifying C2 communication patterns such as heartbeat beacons and agent tasking requests occurring over non-standard port 8133.
Detects network activity associated with the AMOS (Atomic macOS Stealer) malware, specifically identifying C2 communication patterns such as heartbeat beacons and agent tasking requests occurring over non-standard port 8133.
Detects architecture-specific Mach-O 64-bit AMOS Stealer binaries dropped by the Macfinger ClickFix first-stage shell script, requiring multiple distinctive C2 endpoint strings alongside Mach-O magic and size constraints to reduce false positives
Detects architecture-specific Mach-O 64-bit AMOS Stealer binaries dropped by the Macfinger ClickFix first-stage shell script, requiring multiple distinctive C2 endpoint strings alongside Mach-O magic and size constraints to reduce false positives
Detects architecture-specific Mach-O 64-bit AMOS Stealer binaries dropped by the Macfinger ClickFix first-stage shell script, requiring multiple distinctive C2 endpoint strings alongside Mach-O magic and size constraints to reduce false positives
This rule detects network traffic originating from the RatHat Android malware, specifically identifying the 'SCROLL_DOWN' command in HTTP response bodies. This suggests the malware is receiving instructions from a C2 server to perform UI automation or interaction tasks.
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