Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of multiple distinct host reconnaissance commands (e.g., systeminfo, whoami, ipconfig, AV/EDR checks, and domain enumeration) within a short window (10 minutes) originating from the same parent process. This pattern is characteristic of automated reconnaissance collection, often performed during the initial phases of an attack or as part of a C2 workflow. The rule includes exclusions for common administrative, monitoring, and RMM tools to reduce false positives.
Detects the execution of multiple distinct host reconnaissance commands (e.g., systeminfo, whoami, ipconfig, AV/EDR checks, and domain enumeration) within a short window (10 minutes) originating from the same parent process. This pattern is characteristic of automated reconnaissance collection, often performed during the initial phases of an attack or as part of a C2 workflow. The rule includes exclusions for common administrative, monitoring, and RMM tools to reduce false positives.
Detects the execution of multiple distinct host reconnaissance commands (e.g., systeminfo, whoami, ipconfig, AV/EDR checks, and domain enumeration) within a short window (10 minutes) originating from the same parent process. This pattern is characteristic of automated reconnaissance collection, often performed during the initial phases of an attack or as part of a C2 workflow. The rule includes exclusions for common administrative, monitoring, and RMM tools to reduce false positives.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
This rule detects Salesforce Agentforce or similar AI-driven chat responses that contain external URLs with non-standard Top-Level Domains (TLDs). It identifies cases where the organization's redactor failed to strip a URL due to unexpected TLDs or unusual trailing termination characters (e.g., brackets) that are still rendered as clickable links in the interface. Such links may facilitate phishing, credential harvesting, or redirection to malicious sites.
Detects the use of reg.exe to query the MachineGuid value from the Windows Registry (HKLM\SOFTWARE\Microsoft\Cryptography). This behavior is often associated with adversary reconnaissance, specifically host fingerprinting, to uniquely identify compromised machines.
Detects anomalous, high-frequency interaction with AI model endpoints characterized by a high volume of requests with a near 1:1 ratio of distinct inputs. This pattern is indicative of automated knowledge-distillation or model extraction attacks against AI services.
Detects Node.js processes executing system-level reconnaissance (e.g., CPU, memory, hostname, uptime enumeration) followed by network connections to known exfiltration endpoints (Slack, Telegram API). This behavior aligns with identified npm malware campaigns using host fingerprinting for target selection and data exfiltration.
This rule detects anomalous, high-volume activity from a single user account interacting with known public generative AI platforms (e.g., ChatGPT, Copilot, Claude). It uses a threshold-based approach on CloudAppEvents logs to identify potential reconnaissance or bulk information gathering activities which could signify unauthorized use or automated data scraping via AI interfaces.
This rule detects anomalous, high-volume activity from a single user account interacting with known public generative AI platforms (e.g., ChatGPT, Copilot, Claude). It uses a threshold-based approach on CloudAppEvents logs to identify potential reconnaissance or bulk information gathering activities which could signify unauthorized use or automated data scraping via AI interfaces.
This rule detects anomalous, high-volume activity from a single user account interacting with known public generative AI platforms (e.g., ChatGPT, Copilot, Claude). It uses a threshold-based approach on CloudAppEvents logs to identify potential reconnaissance or bulk information gathering activities which could signify unauthorized use or automated data scraping via AI interfaces.
Detects instances where a single user account exhibits an anomalously high frequency of requests to public generative-AI platforms within a one-hour window, potentially indicating automated reconnaissance or data staging activities using AI tools.
Detects instances where a single user account exhibits an anomalously high frequency of requests to public generative-AI platforms within a one-hour window, potentially indicating automated reconnaissance or data staging activities using AI tools.
Detects web proxy requests that resemble phishing attempts targeting Apple Activation Lock. The rule identifies URLs containing specific Apple-related keywords in combination with common phishing URL paths, while filtering out legitimate Apple support documentation pages.
This rule detects interaction between an internal host and the Vapi.ai API, typically used for automating AI-based voice phishing (vishing) calls. It identifies the initiation of a call via POST requests to the Vapi.ai API and subsequent callbacks from Vapi.ai to an attacker-controlled webhook endpoint used for tracking call status.
Detects a suspicious pattern where a user browser visits a Google Document and subsequently initiates a connection to the Telegram Bot API within a short timeframe (10 minutes). This sequence is indicative of malicious Google Apps Scripts embedded in documents attempting to exfiltrate victim information (IP, geolocation, device details) as part of a reconnaissance phase before a ClickFix-style payload delivery.
Detects potential reconnaissance activities targeting Redis services on port 6379, specifically looking for unauthenticated 'PING' commands and subsequent responses indicating either authentication requirements or an open, unauthenticated instance.
Detects the AnonyMousKIT vishing activity pattern by monitoring Twilio API call creation events followed by specific status or gather webhook callbacks from the same host within a one-hour window, consistent with automated voice phishing to collect DTMF-entered passcodes.
Detects the specific C2/WebSocket instruction sequence utilized by the JWR/Outsider phishing kit operators. The rule monitors DeviceNetworkEvents for characteristic outbound URL query parameters that indicate progress through a phishing interaction, including initial info collection (to_info), card data submission (to_card), and subsequent verification or outcome steps.
Detects anomalous Microsoft Graph API activity characterized by user enumeration or querying for sensitive organizational groups (e.g., payroll, finance, HR) often associated with post-AiTM account-takeover reconnaissance. This detection specifically identifies multiple requests for sensitive URIs or high-count enumeration requests originating from suspicious User-Agent strings like 'axios/1.18.1', commonly observed in threat actor activity such as Storm-2755.
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