Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
565 detections
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Detects network activity associated with Mirage2FA Adversary-in-the-Middle (AiTM) phishing infrastructure. The rules monitor for HTTP responses containing specific spoofed Microsoft 365 sign-in page content, DNS resolutions for known proxy-associated domain suffixes, and client requests fetching malicious loader scripts from suspected AiTM hosting infrastructure.
Detects network activity associated with Adversary-in-the-Middle (AiTM) phishing kits. This includes detection of kit-specific fingerprinting scripts (class_identifier.php), use of specific server banners (openresty), unauthenticated geolocation lookups (api.country.is), setting of geolocation cookies, and proxying of requests to Microsoft OAuth endpoints.
Detects communication patterns associated with the OnyxC2 malware, including host-fingerprint synchronization over HTTP, potential reverse SOCKS5 proxy tunnel initialization, and inbound HTTP responses containing command tasking such as cmd.exe.
Detects network indicators associated with the ClearFake campaign, including connections to known dead-drop resolvers (bsc-testnet-rpc.publicnode.com), use of Cloudflare Workers as C2 infrastructure, and the delivery of malicious fake browser-update/CAPTCHA JavaScript payloads.
Detects HTTP responses containing a file named 'ClaudeDesktop.exe' served from paths containing '/artifacts/' on the 'claude.ai' host where the request referrer is not 'claude.ai' or 'anthropic.com', suggesting a malvertising or supply chain delivery attempt of a malicious installer.
Detects HTTP responses containing a file named 'ClaudeDesktop.exe' served from paths containing '/artifacts/' on the 'claude.ai' host where the request referrer is not 'claude.ai' or 'anthropic.com', suggesting a malvertising or supply chain delivery attempt of a malicious installer.
Detects high-frequency, sustained queries to an ML inference endpoint from a single identity, indicative of gradient-free training data reconstruction or model inversion attacks. The rule triggers when a specific user or API key performs over 100 successful requests within a 15-minute window, where the responses include granular confidence, probability, or logit values, which are typical targets for reconstructing training data.
Detects high-frequency, sustained queries to an ML inference endpoint from a single identity, indicative of gradient-free training data reconstruction or model inversion attacks. The rule triggers when a specific user or API key performs over 100 successful requests within a 15-minute window, where the responses include granular confidence, probability, or logit values, which are typical targets for reconstructing training data.
Detects network activity associated with the 'ClickFix' campaign, specifically targeting the cdnsuicaches[.]com domain. The rules identify the initial DNS query, the subsequent TLS SNI connection, and the retrieval of malicious JavaScript containing the 'cookie-captcha-complete' overlay signature. This behavior is indicative of a browser-based social engineering attack.
Detects network traffic associated with the SloppyRAT backdoor, which utilizes a reverse SOCKS proxy mechanism. The rule identifies specific HTTP GET/POST heartbeats and command responses to the '/api/poll' and '/api/proxy/ack' endpoints commonly used for C2 operations.
This rule set detects web traffic associated with 'GhostCode' phishing campaigns. These campaigns utilize Cloudflare Turnstile verification gates on non-Cloudflare domains, specific phishing page titles, and session cookies ('turnstile_verified', 'cf_clearance') to facilitate device code phishing or credential harvesting activities.
Detects anomalous C2 traffic associated with SectopRAT that leverages JSON-RPC 'eth_call' methods on 'binance.org'. The detection monitors for a specific POST request pattern followed by a response containing 'START' and 'FINISH' markers within the result field, indicating command-and-control communication disguised as blockchain interactions.
Detects HTTP connections between internal hosts and suspected C2 infrastructure associated with the Operation SilkParasite campaign. The rule specifically monitors for connections to known malicious IPs and identifies the retrieval of a cloned RTX Corporation homepage content, which acts as a decoy for the SpiceRAT malware.
This rule detects network activity associated with the SilverFox malware, specifically targeting communication patterns between the compromised host and identified relay infrastructure. The detection focuses on unique URL query patterns for relay discovery and dispatcher requests, as well as the identification of staging/download links within server responses.
This rule detects attempts to exploit a path traversal vulnerability (CVE-2024-21762) in FortiOS SSL-VPN by monitoring for malformed GET requests targeting the /remote/fgt_lang endpoint. The rule also tracks successful exploitation by identifying HTTP 200 responses containing Linux password file patterns (root:x:0:0:), indicating potential remote file disclosure.
Detects HTTP responses containing JavaScript-based anti-bot challenge pages consistent with the GhostCode toolkit, and subsequent HTTP requests containing tracking tokens used for victim verification after passing the challenge.
Detects network activity associated with the 'ClickFix' campaign, specifically targeting the cdnsuicaches[.]com domain. The rules identify the initial DNS query, the subsequent TLS SNI connection, and the retrieval of malicious JavaScript containing the 'cookie-captcha-complete' overlay signature. This behavior is indicative of a browser-based social engineering attack.
Detects network activity associated with the 'ClickFix' campaign, specifically targeting the cdnsuicaches[.]com domain. The rules identify the initial DNS query, the subsequent TLS SNI connection, and the retrieval of malicious JavaScript containing the 'cookie-captcha-complete' overlay signature. This behavior is indicative of a browser-based social engineering attack.
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
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