Ankit Mehta
@SecvynIndiaTrusted contributorCompletionist
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8,655 detections
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This rule detects potentially malicious activities on network devices by monitoring Syslog messages for account creation with high privileges, privilege abuse, configuration wiping, and anomalous SSH logins from unauthorized source IP addresses. The rule aggregates these events to identify multi-stage exploitation patterns on network infrastructure.
This rule monitors for suspicious activity originating from the DHCP Client service process (svchost.exe running with 'Dhcp' in the command line). It detects unauthorized child processes (such as cmd.exe or powershell.exe), unexpected child processes that deviate from established baselines, service crashes potentially indicative of exploitation, and anomalous network connections to non-standard DHCP ports or external IP addresses.
Detects potential persistence attempts on Windows systems where an unsigned executable, located in a user-writable directory (Temp, AppData, Downloads), is either configured for automatic startup via Registry run keys or registered as a scheduled task.
This rule monitors for successful external logins occurring on an endpoint that previously demonstrated patterns of suspected MFA fatigue (multiple failed push notifications) and subsequent internal reconnaissance activity (execution of commands used for domain or system discovery). The rule correlates these events to identify potential compromised credentials being actively used for lateral movement or persistence.
This rule detects potentially malicious lateral movement or persistence activities by monitoring the creation or modification of executable files in remote network shares and startup folders, as well as the use of administrative tools like sc.exe or schtasks.exe to create services or tasks. The rule specifically filters out processes signed by Microsoft, focusing on non-standard or unsigned binaries that perform these administrative actions across multiple instances, indicating potential automated lateral propagation.
This rule detects processes that load sensitive Windows multimedia and graphics modules (mmdevapi.dll, avrt.dll, magnification.dll, dxgi.dll) which are commonly utilized for audio recording and screen capturing. The rule filters out known legitimate applications (e.g., Teams, Zoom, Web browsers) and trusted software publishers. It further identifies potential suspicious activity by flagging processes originating from common staging paths like 'Temp', 'Downloads', or 'ProgramData' and instances where the process image is unsigned.
Detects Python or Node.js processes executing command-line interpreters (e.g., cmd.exe, bash) while simultaneously performing network connections. This behavior is indicative of a post-exploitation activity where an attacker leverages language-specific package paths to execute shell commands and establish command-and-control communication.
This rule detects potential ransomware activity by identifying a combination of three distinct behaviors occurring on a single endpoint within a short window: high-volume file modifications (indicative of file encryption), deletion of system recovery resources (e.g., volume shadow copies, backup catalogs), and high-frequency network activity (indicative of data exfiltration). The rule uses cross-event correlation to reduce false positives by requiring all three signals to be present.
This rule detects potentially suspicious outbound network connections or DNS queries to known Generative AI service domains (OpenAI, Anthropic, Google, Mistral, Cohere) from non-browser and non-developer processes. It also triggers on suspicious Windows binaries (e.g., PowerShell, bitsadmin, mshta) initiating external connections to these domains or other destinations over port 443, helping identify potential data exfiltration or automated abuse of LLM APIs.
Detects attempts to open the Local Security Authority Subsystem Service (LSASS) process with read permissions (specifically, PROCESS_VM_READ access) by non-system processes. This activity is often associated with credential dumping techniques.
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