Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a specific adversary pattern termed 'Phantom Deal' where a user is socially engineered into disabling their VPN (by claiming a link won't open), followed immediately by a rapid succession of accesses to the same tracking or canary link from that user account. The rule correlates sign-in events indicating a shift in VPN or MFA context with subsequent bursts of URL clicks.
Detects a specific adversary pattern termed 'Phantom Deal' where a user is socially engineered into disabling their VPN (by claiming a link won't open), followed immediately by a rapid succession of accesses to the same tracking or canary link from that user account. The rule correlates sign-in events indicating a shift in VPN or MFA context with subsequent bursts of URL clicks.
This rule detects TLS handshakes where the Server Name Indication (SNI) field contains an IP address literal instead of a domain name. Legitimate web services and applications typically use FQDNs for TLS SNI to support virtual hosting. Using an IP literal in the SNI field is a technique often used by malware, C2 infrastructure, and malicious scripts to establish encrypted connections while avoiding standard DNS lookups, which may be logged or monitored.
This rule detects the use of raw sockets by 'ERAAgent.exe' by monitoring for socket I/O control (Ioctl) operations involving 'SIO_RCVALL'. This configuration, often associated with promiscuous mode, allows an application to capture all network traffic received by the network interface, a behavior commonly used by network sniffing tools or malicious implants to intercept sensitive data.
This rule detects OAuth authorization requests (targeting Microsoft or Google identity providers) that use 'prompt=none' (silent authentication) and redirect the user to an unexpected or untrusted domain. This pattern is commonly used in OAuth consent phishing or token theft attacks, where an attacker attempts to silently acquire an authorization code by redirecting it to a malicious application server instead of the legitimate service provider's domain.
KQL Query from file: grafana-mcp-server-mediated-probing-of-internal-ip-ranges-lateral-movement.kql
This rule detects potential automated web scraping activity by identifying high-volume, repetitive network requests directed towards domains identified as government (.gov) or military (.mil). It correlates these network patterns with the execution of common browser automation frameworks (e.g., Puppeteer, Playwright) or headless browsers, indicating a likely coordinated scraping operation or bot activity.
Detects high-frequency requests to the RubyGems legacy API key endpoint, which may indicate attempts to harvest or bruteforce developer API keys. The rule specifically monitors for request patterns involving variations like .yaml, .json, or parameter-based variants often observed in scanning activities.
This rule detects browser activity where a page rendered via a data blob loads a sandboxed iframe containing cross-origin content originating from cdn.bloom.io. This pattern is consistent with known phishing delivery mechanisms often used in DocuSign or Teams-themed phishing campaigns to facilitate credential theft or secondary payloads.
Detects anomalous TCP stream reassembly where overlapping segments contain different data. This technique is often used to bypass Network Intrusion Detection Systems (IDS) by presenting different data to the target system than what the IDS inspects.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
Detects a multi-stage authentication bypass attempt against LiteLLM MCP endpoints. The rule tracks an initial malformed Authorization Bearer token request to the /mcp/ endpoint, followed by a server response returning a 200 OK status code accompanied by an 'mcp-session-id' header, confirming the exploitation of CVE-2026-59822.
Detects a multi-stage authentication bypass attempt against LiteLLM MCP endpoints. The rule tracks an initial malformed Authorization Bearer token request to the /mcp/ endpoint, followed by a server response returning a 200 OK status code accompanied by an 'mcp-session-id' header, confirming the exploitation of CVE-2026-59822.
This rule identifies potential command-and-control (C2) beaconing behavior by detecting repetitive, consistent connections (low jitter) to public IP addresses over common TLS ports (443, 8443, 4443, 9443) from processes that do not have a known history of connecting to those destinations. It establishes a baseline of historical connections to filter out legitimate traffic and uses a statistical analysis of connection intervals to highlight suspicious, non-human-like automated communication patterns.
This rule monitors for various types of events (user logons, network connections, API audits, cloud app events, and email traffic) originating from a specific CIDR block (160.79.104.0/21), which is flagged as suspicious or unauthorized.
This rule detects various event types (email, identity authentication, network connections, and cloud audit logs) originating from or interacting with the specific IP address range 160.79.104.0/22 to 160.79.111.0/22, which is associated with known malicious activity.
This rule detects potential Command and Control (C2) beaconing activity by identifying periodic outbound network connections from suspicious or non-browser processes. It analyzes the time deltas between successful network connections; if the standard deviation of these intervals is low (indicating consistent timing) and a sufficient number of connections occur, it flags the behavior as a potential C2 heartbeat.
Detects network connections from Windows hosts to known IP addresses and domain names associated with the exploitation infrastructure used in CVE-2026-18577, targeting N-able N-central servers.
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