Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the use of MSBuild.exe to compile and execute inline code or tasks. The rule identifies suspicious command-line patterns (such as Task/CodeTaskFactory), execution from non-standard directories (Temp, AppData, Downloads, etc.), and subsequent network or child process activity originating from these MSBuild instances, indicating potential defense evasion or code execution.
Detects the use of MSBuild.exe to compile and execute inline code or tasks. The rule identifies suspicious command-line patterns (such as Task/CodeTaskFactory), execution from non-standard directories (Temp, AppData, Downloads, etc.), and subsequent network or child process activity originating from these MSBuild instances, indicating potential defense evasion or code execution.
Detects the use of MSBuild.exe to compile and execute inline code or tasks. The rule identifies suspicious command-line patterns (such as Task/CodeTaskFactory), execution from non-standard directories (Temp, AppData, Downloads, etc.), and subsequent network or child process activity originating from these MSBuild instances, indicating potential defense evasion or code execution.
Detects outbound network connections to known Tor SOCKS (9050, 9150) or OR (9001, 9051) ports initiated by processes other than standard, authorized Tor client binaries. This is indicative of potential C2 traffic obfuscation or unauthorized use of the Tor network within the environment.
Detects network connection attempts to known malicious infrastructure, specifically targeting suspicious domains and an IP address associated with command and control (C2) activity. The rule monitors endpoint network events for communication with specified malicious URLs or a hardcoded IP.
Detects the use of common scripting and command-line utilities (such as curl, python, or bash) to interact with known Polygon blockchain RPC endpoints or specific smart contract addresses/selectors, which may indicate unauthorized interaction with decentralized applications or crypto-assets.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
This rule detects DNS queries or network connections originating from endpoints to a list of known malicious domains associated with various malware families (ClearFake, IClickFix, AMOS, Vidar, etc.). This helps identify potential C2 communication, malicious payload delivery, or infrastructure interaction.
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
Detects anomalous network behavior consistent with the PolinRider malware, which uses public Ethereum JSON-RPC endpoints and blockchain explorers (e.g., Etherscan.io) as a dead-drop resolver for command-and-control (C2) communication. The rules monitor for specific RPC methods (eth_getTransactionByHash, eth_call, eth_getBalance) over HTTP/TLS and DNS resolution queries to known blockchain explorer infrastructure.
Detects network activity associated with NetSupport Manager remote access software, specifically monitoring for connections to known malicious domains and infrastructure, as well as recurring beaconing patterns indicative of command-and-control behavior.
Detects network communication to a known malicious IP address (45.32.253.166) associated with the PIVOTPIPE RAT using Cobalt Strike C2 beaconing patterns. The rule identifies TCP connections, HTTP GET requests for beacon check-ins, and HTTP POST requests for task responses.
Detects network connection events initiated by known beaconing-related process names. These processes are associated with command and control infrastructure or pivot nodes often used by adversaries for post-compromise activity.
This rule detects suspicious usage of certutil.exe for file downloading or the execution of the Chisel proxy tool, specifically targeting connections or authentication towards the suspicious IP address 69.48.228.86. This behavior is indicative of C2 communication or ingress tool transfer.
Detects file, process, and network activity associated with the TraderTraitor/KelpDAO malware campaign based on known hashes, filenames, paths, and C2 infrastructure.
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