Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects HTTP POST requests to SharePoint ToolPane or WebPartPage endpoints containing serialized gadget chains (e.g., ysoserial ExpandedWrapper/ObjectDataProvider or XamlServices) indicative of deserialization exploitation attempts, specifically targeting CVE-2026-65660.
Detects DNS queries, HTTP requests, and TLS SNI traffic directed towards the domain 'cloudflare-check.net', which is associated with 'ClickFix' social engineering campaigns used to deceive users into executing malicious code.
Detects unauthenticated HTTP POST requests targeting SharePoint WebPartPage-derived endpoints using the 'webPartMarkup' parameter. This activity attempts to exploit a vulnerability (CVE-2026-65660) where anonymous access to specific pages bypasses authentication, allowing an attacker to invoke internal methods for malicious register-directive injection.
Detects malicious exploitation attempts against the SharePoint WebPartPages.asmx SOAP endpoint. Attackers use this endpoint to bypass security patches by invoking template-parsing functions like GetWebPartPageConnectionInfo, which facilitates Register-directive injection and XamlServices deserialization chains for remote code execution.
This rule detects DNS queries, TLS Server Name Indication (SNI) lookups, and HTTP Host header requests directed towards a list of known domains associated with 'Exvicy' malicious activities (lure domains).
This rule detects HTTP POST requests indicative of the RevStealer malware interacting with a Polygon blockchain smart contract via a public RPC endpoint. The rule specifically looks for 'eth_call' JSON-RPC methods targeting a known malicious contract address and a specific function selector ('0xd8b0d6ad') often used in RevStealer's command-and-control failover operations.
Detects outbound HTTP POST requests associated with the VelvetCake malware and Konni threat actor to the command-and-control (C2) domain 'medianewsonline.com'. The rule matches specific URI patterns ('/logout.php') and query parameters ('OKey=', 'Who=', 'Areyou=') commonly used for reconnaissance and data exfiltration.
Detects RevStealer malware attempting to use blockchain infrastructure for C2 communication or failover. The rules identify specific 'eth_call' JSON-RPC method calls to Polygon smart contracts containing hardcoded indicators, as well as TLS connections to known public RPC providers used as fallback C2 infrastructure.
The following analytic detects potential data exfiltration using plain HTTP POST requests. It leverages network traffic logs, specifically monitoring the `stream_http` data source for POST methods containing suspicious form data such as "wermgr.exe" or "svchost.exe". This activity is significant because it is commonly associated with malware like Trickbot, trojans, keyloggers, or APT adversaries, which use plain text HTTP POST requests to communicate with remote C2 servers. If confirmed malicious, this activity could lead to unauthorized data exfiltration, compromising sensitive information and potentially leading to further network infiltration.
Detects potential Denial of ML Service (DoMLs) attacks targeting inference endpoints. The rule identifies anomalous behavior characterized by large request payloads (oversized requests) correlated with increased latency or high GPU utilization, suggesting an attempt to exhaust compute resources and impact model availability.
This rule monitors for indicators of compromise (IOCs) associated with the TrustSink rogue MFA provider, specifically tracking the domain 'trident-sip-filter.ngrok-free.dev' and its associated OIDC discovery path. It aggregates signals from sign-in logs, audit logs, DNS queries, and network proxy traffic to identify attempts to interact with this malicious infrastructure.
This rule detects potential cost harvesting or unauthorized resource abuse by monitoring API endpoints (typically AI model gateways) for high-volume or resource-intensive queries associated with a specific identity. It correlates these patterns with billing or autoscaling trigger events (e.g., cost spikes, quota exhaustion) and identifies agentic sessions that exhibit abnormally long reasoning loops, which suggests an attempt to waste computational budget.
Detects network traffic (DNS queries, TLS SNI, and HTTP Host headers) associated with the known TukTuk C2 infrastructure domain 'borjumaniya.store'.
Detects network requests originating from mobile device user-agents to suspected phishing or OAuth-consent URLs. This rule identifies patterns common in 'quishing' (QR-code phishing) campaigns where a mobile device is used to interact with a malicious redirect chain or credential-harvesting page. It excludes known legitimate OAuth authorization flows to reduce noise.
Detects high-volume, systematic querying of LLM inference endpoints, which may indicate unauthorized model extraction, distillation attempts, or targeted data exfiltration from an LLM.
This rule correlates web clicks on Google Sites URLs containing keywords related to GlobalProtect with the subsequent creation or renaming of an unsigned or improperly signed GlobalProtect.msi file on the same endpoint within a 30-minute window. This behavior is indicative of a spearphishing attempt using a masqueraded landing page to deliver malicious or unauthorized software.
This rule detects potential prompt injection attacks against internal AI-powered assistants, agents, or LLM gateways. It monitors network HTTP requests for common patterns used to override system instructions, bypass safety filters, or force the model to adopt a privileged, unauthorized persona (e.g., administrator or debug mode). These techniques are often used in social engineering to manipulate the AI's output or security posture.
Hunts network, HTTP, and email-URL telemetry for known ARToken infrastructure (operator backend IPs and phishing/panel domains). Bounded to a 30-day lookback and tiers matches by confidence: domain hits are high-confidence (attacker-registered infrastructure), while IP hits are medium-confidence since the IPs sit on shared DigitalOcean hosting that can be reassigned to unrelated tenants once ARToken's infrastructure is taken down. Empty/unparsed indicator fields are excluded to avoid spurious matches in the HTTP event parsing branch. No known file hashes are associated with this intel.
This rule monitors for interactions with known malicious files (by SHA256 hash), connections to confirmed C2 infrastructure (specific IP address and domains), or requests to known malicious URLs. It aggregates indicators across file, process, network, and web browsing telemetry to identify potential threats or compromised systems communicating with known attacker infrastructure.
This rule detects malicious activity by monitoring for specific known indicators, including hashes of malicious files (ProcessRollup2), network connections to known C2 infrastructure (NetworkConnectIP4), and URL clicks (UrlClick) associated with malicious domains or paths. It acts as a multi-stage indicator correlation rule to identify execution or communication with known threats.
This rule detects potential malicious activity by monitoring for known indicators of compromise, including specific SHA256 file hashes, a known malicious IP address, and URLs associated with identified threats. The detection spans file creation/execution, network connections, and URL visits to block or alert on interactions with suspicious infrastructure.
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