Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous DNS query patterns originating from AI agent hosts that are characteristic of DNS tunneling, such as the use of TXT or NULL records and excessively long subdomain labels. These techniques are often used by attackers to establish covert Command and Control (C2) channels and exfiltrate data by bypassing traditional HTTP/HTTPS egress filtering.
Detects instances where the system DNS process (dns.exe) on a domain controller performs recursive DNS resolution towards a set of external IP addresses associated with suspicious infrastructure (AS202412). The rule correlates this activity with recent network connections from common web browsers or system utilities (msedge.exe, svchost.exe) on the same host to identify potential proxying of malicious DNS queries.
This rule detects instances where common system processes (svchost.exe, explorer.exe, dllhost.exe) perform process injection activities, followed within a 5-minute window by a network connection to known SaaS and collaborative platforms (Slack, Discord, Dropbox, Trello). This combination is often indicative of malicious code executing within a trusted process to facilitate command and control or data exfiltration.
This rule detects potential command and control or malicious file staging activity by correlating DNS TXT record queries (often used for data exfiltration or staging configuration) performed by common system utilities (nslookup, PowerShell) with the subsequent execution of files from suspicious directories (Downloads, Temp) within a 30-minute window on the same device.
Detects network indicators associated with the ORAX Phishing-as-a-Service (PhaaS) platform. This includes patterns for emoji-matching CAPTCHAs, spoofed Cloudflare security pages, specific wildcard subdomain DNS queries, and the use of anti-analysis gate sequences to prevent sandbox inspection.
Detects DNS queries for domains containing specific brand-related strings (such as government agencies or courier services) coupled with high-risk top-level domains (TLDs). This pattern is frequently used by adversaries to register infrastructure for phishing and social engineering campaigns by mimicking legitimate organizational presence.
Sweeps Defender Advanced Hunting telemetry for known Sauron Loader indicators: 5 malicious SHA256 hashes (MSI installer, rnp.dll loader, tdwp.dll decrypter, embedded RSA private/public key blobs) across file/process/image-load events, plus 4 C2 domains and their full URLs across network and DNS telemetry. No IP indicators were published in the source reporting (C2 is domain-based over HTTPS) — the IP bucket is intentionally omitted rather than filled with placeholder data.
Sweeps Defender Advanced Hunting telemetry for known Sauron Loader indicators: 5 malicious SHA256 hashes (MSI installer, rnp.dll loader, tdwp.dll decrypter, embedded RSA private/public key blobs) across file/process/image-load events, plus 4 C2 domains and their full URLs across network and DNS telemetry. No IP indicators were published in the source reporting (C2 is domain-based over HTTPS) — the IP bucket is intentionally omitted rather than filled with placeholder data.
Detection of network traffic patterns associated with the NovaCookies Adversary-in-the-Middle (AiTM) phishing kit. The rules monitor for DNS queries for .vu domains, HTTP requests to lookalike Microsoft 365 login pages hosted on .vu domains, POST requests containing credential data, and the receipt of specific session cookies (ESTSAUTH) indicative of successful AiTM session interception.
Detects network activity associated with the OnyxC2 malware, including DNS queries to .top TLDs for beaconing, subsequent HTTP check-ins to .top domains, and known TLS SNI matches for OnyxC2 C2 infrastructure.
Detects a correlation between a DNS query for a potential typosquatting or brand-lookalike domain (newly observed within the last 30 days) and a subsequent sign-in authentication event originating from the same client IP within a 30-minute window. This behavior is indicative of an attacker, such as ShinyHunters vishing operators, directing victims to a lookalike SSO phishing portal to harvest credentials and MFA tokens before attempting access to the legitimate environment.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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 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 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 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 network activity (DNS queries, TLS SNI, and HTTP requests) associated with identified 'ShipmentsFree' scam domains. These domains are typically used in phishing or credential harvesting campaigns to trick users into visiting fake account or tracking pages.
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