Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects network communication with 10729e014d0e.skyleen.fr, associated with the SCKIT malware downloading binaries during CI/CD emitter activities. This rule flags potential ingress tool transfers as part of a supply chain compromise campaign identified as 'memos-semi-nuclear'.
Detects exfiltration of sensitive information, including Dahua camera credentials and internal identifiers, to the Telegram Bot API over HTTPS. These rules monitor for specific API endpoints (/sendPhoto) and common credential patterns (Login:, Password:, Model:) or indicators (Shodan links, VKontakte references) within HTTP POST requests directed toward api.telegram.org.
Detects attempts to exploit CVE-2021-33044, an authentication bypass vulnerability in Dahua NetKeyboard hardware. The rule triggers when a POST request containing 'global.login', 'clientType: NetKeyboard', and 'loginType: Direct' is observed, which allows unauthorized access by manipulating authentication parameters.
Detects malicious HTTP POST requests targeting SharePoint servers that attempt to inject 'Register' directives into pages or manipulate WebPartPage ToolPane markup, indicative of attempts to bypass SafeControls or exploit vulnerable SharePoint features for code execution.
Detects network traffic associated with the Exvicy malware delivery chain. The rule identifies two behaviors: first, HTTP GET requests to a '/embed/' endpoint with specific 'embed=1' and 'host=cloudflare-check.net' parameters, and second, established TCP connections to a known command and control (C2) IP address related to the ClickFix social engineering delivery method.
Detects DNS queries, HTTP requests, and TLS SNI traffic directed towards the domain 'cloudflare-check.net', which is associated with 'ClickFix' social engineering campaigns used to deceive users into executing malicious code.
Detects DNS queries for the domain 'phf-ubp.com', which is associated with fraudulent HTS infrastructure. This rule monitors network traffic for indicators of communication with known malicious infrastructure.
Detects anomalous outbound HTTP POST requests containing sensitive file extensions or keywords (e.g., .docx, password, credentials) triggered by Python-based clients, followed by a potential exfiltration beacon response containing JSON file path data.
Detects outbound HTTP POST requests associated with the Telepuz modular loader. The rule monitors for specific URI patterns, request body parameters, and suspicious User-Agent strings indicative of PowerShell or MSHTA command-and-control communication.
Detects outbound HTTP POST requests associated with Cicada3301 ransomware affiliate check-in behavior. The rule monitors for a specific 'X-Session-Id' HTTP header and a corresponding 'affiliate_id' parameter within the request body, which are indicative of malicious C2 communication.
Detects network activity related to the BEAST ransomware targeting VMware ESXi systems. The rule identifies attempts to stage encryption operations via SSH, including detecting references to known filenames ('encryptor.elf', 'beast_esxi') and the use of the 'vim-cmd' utility to power off virtual machines as part of the preparation for file encryption.
Detects anomalous large-scale data transfers to external endpoints that exhibit patterns characteristic of the ShinyHunters group's SaaS bulk export and data exfiltration methods. The rule identifies suspicious HTTP requests to Salesforce API endpoints (e.g., batch jobs, bulk queries) accompanied by unusually large content payloads, followed by subsequent encrypted communication to non-whitelisted external destinations.
Detects the presence of an injected script tag containing 'ganalytics-tracker-js' in HTTP server responses, a pattern commonly associated with 'ClickFix' social engineering attacks where users are tricked into copying and executing malicious commands.
Detects HTTP traffic related to the Macfinger/ClickFix campaign, where malicious injected scripts or dns-prefetch entries point to known attacker-controlled infrastructure (velvet-otter-glagceis.life) or assets utilized for social engineering and malicious copy-paste exploitation.
Detects outbound HTTP POST requests directed at the '/api/credentials' URI, a pattern associated with AMOS Stealer credential exfiltration. The rule includes a threshold to reduce noise by alerting only when multiple requests occur from a single source within a short timeframe.
This rule detects network activity associated with the Sauron Loader malware. It monitors for TLS connections to known hardcoded C2 domains and identifies HTTP requests following a specific pattern of randomized command and control (C2) paths combined with suspicious User-Agent headers (Windows NT with Edge/Edg).
This rule detects HTTP GET requests to a specific GitHub repository path (raw.githubusercontent.com/omskiwdcvoiuyfd0998/) identified as staging infrastructure associated with Konni/VelvetCake malware operations. This activity is indicative of a compromised host attempting to download malicious payloads or stage tools from actor-controlled infrastructure.
Detects DNS lookup queries and HTTP POST beaconing attempts directed at known Sauron Loader C2 fallback infrastructure. The rule tracks specific domains associated with the malware's encrypted registration and command-and-control behavior.
This rule detects outbound HTTP GET requests initiated by a process using a 'WebClient' user-agent to retrieve a file named 'shell.ps1'. This behavior is characteristic of adversaries downloading second-stage PowerShell payloads to a compromised host.
Detects suspicious HTTP POST requests to a URI path '/collect' containing specific telemetry parameters ('visitorId', 'timeOnPage', 'stage') characteristic of the 'ClickFix' social engineering campaign. This behavior is used by threat actors to simulate fake bot-protection challenges to trick users into executing malicious code.
Detects high-frequency requests directed at common model-serving API endpoints, which may indicate an attacker attempting to perform model extraction or model inversion attacks by repeatedly querying the model to infer its parameters or training data.
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