Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,310 detections
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Detects network traffic associated with the 'ClickFix' technique, where malicious websites masquerade as legitimate CAPTCHA or bot-protection services to exfiltrate visitor telemetry via POST requests or fetch malicious script overlays.
Detects HTTP POST requests to a /collect endpoint containing visitorId and stage parameters, which is characteristic of ClickFix-style fake bot-protection overlays used to trick users into executing malicious scripts under the guise of security verification.
This rule detects outgoing HTTP POST requests to the 'velvet-otter-glagceis.life' domain path '/collect'. The request body contains indicators of victim fingerprinting, specifically looking for 'visitorId' and 'events' fields, characteristic of the Macfinger/ClickFix campaign used for gathering visitor telemetry for malicious purposes.
Detects a sequence of events where a host connects to 'speedtest.net' followed by a burst of outbound SYN packets to TCP port 37777. This pattern may indicate an adversary using legitimate web traffic to calibrate their scanning rate or bypass network controls before performing a targeted scan.
Detects potential C2 activity associated with MQTTDoor or MatrixDoor malware by monitoring suspicious network traffic patterns. This includes unauthorized processes connecting to MQTT brokers (hivemq.com), non-chat applications interacting with a Matrix homeserver, and geo-location lookups (ip-api.com) occurring shortly after process execution.
Detects adversarial conversational reconnaissance patterns where a user queries an AI agent to enumerate its capabilities, such as available plugins, functions, or parameter schemas. The disclosure of this internal information by the agent facilitates the construction of targeted prompt-injection payloads, a known precursor to exploitation of AI agent vulnerabilities.
Detects accounts showing a spike in requests to public generative-AI services compared to their historical baseline, combined with anomalous indicators like multiple source IPs, regions, or off-hours activity.
Detects accounts showing a spike in requests to public generative-AI services compared to their historical baseline, combined with anomalous indicators like multiple source IPs, regions, or off-hours activity.
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 network activity associated with Adversary-in-the-Middle (AiTM) phishing kits. This includes detection of kit-specific fingerprinting scripts (class_identifier.php), use of specific server banners (openresty), unauthenticated geolocation lookups (api.country.is), setting of geolocation cookies, and proxying of requests to Microsoft OAuth endpoints.
Detects high-frequency, unauthenticated Redis PING/AUTH attempts indicative of a reconnaissance scan against the Redis service. This activity typically represents an adversary performing mass fingerprinting or attempting to identify unsecured Redis instances.
This rule detects potentially malicious messages within Microsoft Teams that use common social engineering keywords related to security configuration changes (e.g., passkey, MFA, SSO). The detection specifically filters for users who have successfully logged in within the last 30 days to identify potential compromised accounts acting as internal senders.
This rule detects a multi-stage phishing attack, often referred to as 'quishing'. It identifies incoming emails containing image (JPG, PNG) or PDF attachments that embed previously unseen URLs, correlated with a subsequent sign-in event from a mobile device by the same recipient, which is a common indicator of Adversary-in-the-Middle (AiTM) credential harvesting.
Detects high-risk identity modifications (password or MFA resets) following an IT helpdesk ticket that lacks mandatory security controls, such as callback verification, manager approval, or established ticket history. This behavior is indicative of vishing and social engineering attacks aimed at helpdesk personnel to compromise user accounts.
Detects potential C2 activity associated with MQTTDoor or MatrixDoor malware by monitoring suspicious network traffic patterns. This includes unauthorized processes connecting to MQTT brokers (hivemq.com), non-chat applications interacting with a Matrix homeserver, and geo-location lookups (ip-api.com) occurring shortly after process execution.
Detects high-risk identity modifications (password or MFA resets) following an IT helpdesk ticket that lacks mandatory security controls, such as callback verification, manager approval, or established ticket history. This behavior is indicative of vishing and social engineering attacks aimed at helpdesk personnel to compromise user accounts.
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.
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.
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 login attempts to internet-exposed FortiGate SSL VPN or firewall management interfaces using suspicious, generic, or potentially leaked administrative account patterns such as fgt-*, FortiManager-*, or tech-support-*. These accounts typically suggest attempts to exploit default, hardcoded, or publicly shared credentials on network infrastructure.
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