Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the specific C2/WebSocket instruction sequence utilized by the JWR/Outsider phishing kit operators. The rule monitors DeviceNetworkEvents for characteristic outbound URL query parameters that indicate progress through a phishing interaction, including initial info collection (to_info), card data submission (to_card), and subsequent verification or outcome steps.
This rule detects DNS lookups, email URL clicks, and network connections involving lookalike domains that mimic Singaporean government or infrastructure services (e.g., LTA, OneMotoring, ERP, Gov.sg). It employs a regex-based pattern match for common brand-keywords combined with high-risk top-level domains, identifying potential phishing activity associated with the JWR framework that utilizes algorithmically varied, single-suffix rotated lookalike domains.
This rule detects network connections to specific domains and domain patterns that mimic legitimate entities (e.g., NinjaVan, EmiratesPost). The detection logic identifies direct matches to known malicious infrastructure and uses regular expressions to catch permutation-based typosquatting, which are common indicators of phishing or credential harvesting campaigns.
Detects SVG files containing embedded ECMAScript that executes a client-side redirect to a known AiTM phishing or C2 domain, specifically targeting the Mirage2FA delivery mechanism.
Detects HTML, XHTML, or SVG files used in Mirage2FA phishing campaigns. These files act as stagers by constructing hidden iframes to load remote JavaScript payloads from '/api/xls/' paths, utilizing specific placeholder tokens and obfuscation techniques such as XOR deobfuscation (0xAD) and custom function wrappers.
Detects an adversary-in-the-middle (AiTM) phishing pattern where the legitimate Microsoft authentication URL is embedded as a sub-path within an attacker-controlled proxy domain. This technique is characteristic of AiTM kits, such as Evilginx2, which proxy the legitimate Microsoft authentication flow to capture credentials and session cookies.
Detects network activity associated with the GhostCode phishing campaign, which leverages themed pages (e.g., MailDashboard) and Cloudflare Turnstile to perform security bypass checks. The rules identify the initial access URI pattern, the presence of specific phishing content in the HTTP response, and the subsequent verification cookies used after the CAPTCHA solution.
Detects inbound email messages containing keywords and phrases consistent with extortion attempts, specifically referencing stolen data, unauthorized access, and demands for cryptocurrency payment.
This rule monitors for indicators of compromise (IOCs) associated with the ShinyHunters threat actor, including specific malicious domains, IP addresses, and artifacts found in command lines or event data. It aggregates telemetry from network events, Entra ID sign-in logs, cloud application activity, email logs, process execution, and general device events to detect interaction with known malicious infrastructure or execution of threat-actor specific artifacts.
Detects potential Adversary-in-the-Middle (AiTM) phishing activity by identifying requests to common tunneling services (e.g., ngrok, Cloudflare Tunnel) that include suspicious authentication or login-related URI paths, correlated with referrers from well-known email providers.
Detects potential Adversary-in-the-Middle (AiTM) phishing activity by identifying requests to common tunneling services (e.g., ngrok, Cloudflare Tunnel) that include suspicious authentication or login-related URI paths, correlated with referrers from well-known email providers.
Detects Browser-in-the-Browser (BitB) phishing pages by inspecting web proxy or EDR-captured page content for malicious HTML/JS structures. The rule identifies fabricated browser chrome, such as fake address bars and title bars, initialized via window.open with specific dimensions, while ensuring the serving domain is not a known, legitimate identity provider.
This rule detects mass-distributed email phishing campaigns that impersonate Google branding. It identifies emails using Google-related sender display names or subjects that originate from non-Google domains and contain links to external, non-Google domains. The detection focuses on identifying suspicious patterns across multiple recipients rather than individual email signatures.
This rule detects potential 'Quishing' (QR code phishing) attempts by identifying email-based phishing detection or malicious URL indicators followed by a user clicking the URL and subsequently authenticating to a corporate system from a mobile device (Android or iOS) within a 30-minute window. This behavior often suggests an adversary successfully harvesting credentials via a QR code link and then using them to gain unauthorized access.
This rule detects email activity involving DocuSign-themed messages that contain attachments and also coincide with URL click events that redirect users to Microsoft-related login portals (e.g., login.microsoftonline.com or teams.microsoft.com) containing 'redirect' or 'redirect_uri' parameters. This behavior is indicative of a phishing attempt designed to capture credentials or perform OAuth consent phishing by mimicking legitimate document-signing workflows.
This rule detects potential Business Email Compromise (BEC) attempts where external senders impersonate corporate executives (e.g., CEO, CFO) by spoofing display names or using lookalike/cousin domains. It triggers when these impersonations are combined with urgent, financial-themed language in the email subject line (e.g., wire transfers, payroll changes, or gift card requests).
This rule monitors incoming email events for potential phishing attempts by identifying messages from unknown sender domains (not seen in the last 90 days) that contain known AI-generated response phrases in the subject line or personalized content matching the recipient's display name. This helps detect spearphishing lures that attempt to build trust through impersonation or leverage LLM-generated phrasing common in automated phishing campaigns.
Detects evidence of indirect prompt injection (IPI) attempts within email and document content processed by enterprise AI assistants. The rule flags instruction-hijack phrases, hidden obfuscation characters (e.g., zero-width, white-on-white text), and encoded blocks specifically targeting AI model behavior.
This rule monitors DeviceNetworkEvents and DnsEvents for connections to known malicious domains and IP addresses associated with phishing campaigns. It alerts on any network communication or DNS resolution attempt targeting these indicators, providing visibility into potential user interaction with phishing infrastructure.
This rule detects email activity containing keywords related to SSO or passkey updates combined with urgent terminology and support request language. This pattern is commonly indicative of phishing attempts aimed at stealing credentials or tricking users into providing sensitive information.
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
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