Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors endpoint network events, file events, and process executions for indicators associated with the Kamasers malware. It specifically looks for connections to known malicious C2 IP addresses and domains, as well as the presence or execution of files matching known malicious SHA256 hashes.
Detects the creation of email mailbox or transport rules that perform actions like hiding, deleting, marking as read, forwarding, or redirecting emails with finance or payment-related keywords. This behavior is indicative of a Business Email Compromise (BEC) post-exploitation workflow where adversaries attempt to conceal malicious activity or divert financial communications.
Detects outbound network traffic and HTTP requests originating from the internal network destined for a known malicious infrastructure associated with 'Corp MDM'. The traffic includes C2 communication patterns, specific API URI paths, and potential login interactions on non-standard ports, consistent with phishing, malware delivery, or unauthorized administrative access.
Detects outbound network traffic and HTTP requests originating from the internal network destined for a known malicious infrastructure associated with 'Corp MDM'. The traffic includes C2 communication patterns, specific API URI paths, and potential login interactions on non-standard ports, consistent with phishing, malware delivery, or unauthorized administrative access.
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.
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 instances where PowerShell or mshta.exe are launched by a web browser or Windows Explorer, often indicative of the 'ClickFix' social-engineering campaign. In this scenario, users are tricked into copying and pasting malicious commands from a fake CAPTCHA or update prompt directly into a Windows terminal or the Run dialog, leading to code execution.
This rule detects network and email activity associated with a list of known suspicious or 'ghost' domains. It monitors email sender and recipient addresses, email URL links, and DNS query logs for matches against the predefined domain list, identifying potential spearphishing or command-and-control communication.
Detects incoming emails processed by Rspamd that exhibit suspicious authentication header signatures. The rule identifies emails lacking DKIM, ARC, or user agent information while simultaneously showing a zero receive count, potentially indicating spoofed, unauthenticated, or malformed phishing attempts.
This rule detects inbound phishing emails that leverage urgent security themes (e.g., passkey, SSO, or MFA updates) to lure users into clicking links. It correlates these emails with subsequent URL clicks and suspicious sign-in activity, such as MFA failures, which are indicative of an attempt to compromise credentials or bypass MFA.
This rule detects activity associated with the 'Ghostcode' threat campaign by monitoring multiple telemetry sources. It identifies connections to known malicious IP addresses and domains, patterns consistent with phishing kit hosting, and specific URL structures used in credential harvesting or payload delivery. The rule correlates sign-in logs, device network events, DNS queries, and email telemetry to identify potential compromise.
Detects the use of the device code authentication protocol in Azure Sign-in logs, which is a common vector used in Adversary-in-the-Middle (AiTM) phishing attacks to hijack OAuth tokens.
Detects network communication with domains and IP addresses known to be associated with 'ClickFix' social engineering campaigns (specifically those masquerading as legitimate HBO Max or macOS related updates). The rule applies a strict correlation between observed malicious IP traffic and specific DNS requests to reduce noise from IP address reuse or threat intelligence feed probes, while also excluding known security-related processes.
Detects incoming emails from specific suspicious domains that pass authentication checks (SPF, DKIM, DMARC) but contain subject lines commonly associated with phishing campaigns, such as invoices, payment requests, or urgent notifications. The rule includes associated URL and attachment information for further analysis.
This rule detects potential malicious activity by matching endpoint file events against a known list of malicious file hashes (SHA256, SHA1, MD5) and monitoring for connections to known malicious domains or URLs.
This rule detects potential malicious activity by matching endpoint file events against a known list of malicious file hashes (SHA256, SHA1, MD5) and monitoring for connections to known malicious domains or URLs.
This rule detects potential malicious activity by matching endpoint file events against a known list of malicious file hashes (SHA256, SHA1, MD5) and monitoring for connections to known malicious domains or URLs.
This rule monitors endpoint network events, file operations, and process executions for known malicious indicators (domains and file hashes) associated with Kremlin activity. It detects connections to suspicious remote domains and the existence or execution of specific malicious file hashes.
This rule detects internal network activity (DNS queries, network connections, and security logs) communicating with domains associated with the GhostCode phishing kit. These domains are typically used to host credential harvesting pages or phishing infrastructure.
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