Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects DNS queries to chattypetty.com, associated with the ChatGPT Custom GPT ClickFix campaign (Huntress reporting).
This is one of three logsource-scoped rules split from a combined KQL IOC hunt because Sigma only supports one logsource per rule.
IP/URL matching is covered by a separate network_connection rule; file-hash matching is covered by a separate process_creation rule.
This is one of three logsource-scoped rules split from a combined KQL IOC hunt because Sigma only supports one logsource per rule.
IP/URL matching is covered by a separate network_connection rule; file-hash matching is covered by a separate process_creation rule.
Detects HTTP GET requests to external services 'trycloudflare.com' or 'workers.dev' that return a file content starting with the 'MZ' and 'PE' header signatures within the first 256 bytes, indicating a Windows executable payload download often associated with AvisLoader activity.
Detects execution of shell commands (cmd, powershell) by processes associated with AvisLoader (e.g., 78324.exe, VLCAssistant.exe, auto.exe), followed by the creation or modification of files in suspicious user-writable directories (e.g., appdata, temp) within a 10-minute window, suggesting potential C2 activity and secondary payload staging.
Detects a sequence of Tox P2P protocol packets consisting of a Cookie Request, Cookie Response, and Crypto Handshake within a single network flow. This pattern is indicative of the Tox P2P protocol, which is sometimes abused by malware (e.g., AvisLoader) for command-and-control (C2) communications to evade traditional network inspection.
This rule monitors for known malicious indicators, including a specific file hash, a C2 IP address, a remote URL associated with potential malicious activity (anydesk.exe), and a domain associated with C3Pool crypto-mining activity, across device processes, network events, and file operations.
Detects outbound HTTP requests to identified scam infrastructure (e.g., herokuapp domains) containing platform-specific query parameters (win or mac). This behavior is indicative of a user interacting with a malicious site that is delivering an OS-tailored locker or malware payload.
Detects outbound HTTP requests to identified scam infrastructure (e.g., herokuapp domains) containing platform-specific query parameters (win or mac). This behavior is indicative of a user interacting with a malicious site that is delivering an OS-tailored locker or malware payload.
Detects a sequence of events where a potential multimedia lure (PDF, image, or media file) is created or downloaded via a web browser or communication client, followed by an AI agent (e.g., ChatGPT, Claude) accessing the file, and subsequently initiating a shell execution process (PowerShell, CMD, etc.) involving suspicious command-line patterns or references to the original file. This behavior is indicative of an AI-assisted prompt injection attack where malicious content is processed and executed through agent tooling.
Detects a sequence of events where a potential multimedia lure (PDF, image, or media file) is created or downloaded via a web browser or communication client, followed by an AI agent (e.g., ChatGPT, Claude) accessing the file, and subsequently initiating a shell execution process (PowerShell, CMD, etc.) involving suspicious command-line patterns or references to the original file. This behavior is indicative of an AI-assisted prompt injection attack where malicious content is processed and executed through agent tooling.
Detects a sequence of events where a potential multimedia lure (PDF, image, or media file) is created or downloaded via a web browser or communication client, followed by an AI agent (e.g., ChatGPT, Claude) accessing the file, and subsequently initiating a shell execution process (PowerShell, CMD, etc.) involving suspicious command-line patterns or references to the original file. This behavior is indicative of an AI-assisted prompt injection attack where malicious content is processed and executed through agent tooling.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects AI agent tooling (e.g., Copilot, Cursor, Ollama) that makes outbound network calls to known AI model providers followed by the execution of suspicious shell commands within a short duration. The rule flags high-severity activities such as download-cradles, credential reconnaissance, LOLBin usage, and persistence mechanisms. Informational alerts are generated for standard CLI activity within the same timeframe.
Detects HTTP GET requests to '/api.php?t=' containing a 13-digit timestamp identifier, followed by a response body containing 'download_link'. This pattern is indicative of the SilverFox malware relaying instructions or stage-two payload delivery.
Detects a multi-stage infection chain associated with RedFlick, involving the delivery of VHDX files or PDF attachments. The rule correlates malicious activities such as SSH-based tool download (using PermitLocalCommand), PowerShell-based PDF decoding/extraction, PowerShell VHDX disk mounting, and silent MSI installation from remote URLs. It monitors for these activities within user-writable directories like Downloads or Temp.
Detects a multi-stage infection chain associated with RedFlick, involving the delivery of VHDX files or PDF attachments. The rule correlates malicious activities such as SSH-based tool download (using PermitLocalCommand), PowerShell-based PDF decoding/extraction, PowerShell VHDX disk mounting, and silent MSI installation from remote URLs. It monitors for these activities within user-writable directories like Downloads or Temp.
This rule detects potential persistence via scheduled tasks that masquerade as legitimate network components (e.g., 'System Health Monitor'), as well as abnormal use of WebDav via rundll32.exe or net.exe in the context of the Star Blizzard (COLDRIVER) campaign. It monitors for task creation/updates, schtasks command lines, registry artifacts related to task scheduling, and suspicious WebDav network utility usage, while excluding common security tool processes.
This rule detects potential persistence via scheduled tasks that masquerade as legitimate network components (e.g., 'System Health Monitor'), as well as abnormal use of WebDav via rundll32.exe or net.exe in the context of the Star Blizzard (COLDRIVER) campaign. It monitors for task creation/updates, schtasks command lines, registry artifacts related to task scheduling, and suspicious WebDav network utility usage, while excluding common security tool processes.
The following analytic identifies the `finger.exe` utility being spawned with a command line containing an `@` character, indicating a remote host/server was specified.
The Finger protocol utility is largely obsolete in modern environments and has been abused by adversaries as a living-off-the-land binary (LOLBIN) to retrieve encoded payloads or establish covert command-and-control communication with an attacker-controlled finger server.
This behavior is uncommon in legitimate enterprise usage and warrants investigation.
The Finger protocol utility is largely obsolete in modern environments and has been abused by adversaries as a living-off-the-land binary (LOLBIN) to retrieve encoded payloads or establish covert command-and-control communication with an attacker-controlled finger server.
This behavior is uncommon in legitimate enterprise usage and warrants investigation.
This rule monitors for indicators of compromise (IOCs) associated with the Lunex Malware-as-a-Service (MaaS) campaign. It aggregates telemetry from file creation, process execution, and network connections to identify the presence of known malicious hashes, C2 IP addresses, phishing-related domains, and specific payload URLs.
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