Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects JavaScript code within HTML pages designed to block browser developer tools (F12, Inspect, View Source) using keydown event listeners. This technique is commonly associated with ClickFix-style phishing campaigns to prevent users or security analysts from inspecting malicious page content or fake CAPTCHA overlays.
This rule detects specific JavaScript helper functions and state machine constants commonly used in 'ClickFix' phishing campaigns (e.g., Exvicy and ErrTraffic). These scripts typically prompt users to copy and paste malicious code snippets, often disguised as error fixes or CAPTCHA resolution, to facilitate initial access.
Detects instances where a non-browser process initiates connections to commercial LLM provider APIs (DeepSeek, OpenRouter, Mistral) followed by a connection to Discord CDN/Webhook endpoints within a 15-minute window. This behavior is indicative of a process acting as an autonomous C2 agent that exfiltrates data after receiving instructions or processing information via an LLM.
Detects malicious shell commands attempting to perform supply-chain persistence via environment variable manipulation in CI/CD environments. The rule identifies processes injecting BASH_ENV into GITHUB_ENV, a known technique used by the SCKIT supply-chain worm to perform credential harvesting during CI pipeline execution.
Detects the execution of the 'sckit' Go implant, a malicious binary associated with trojanized '@memtensor/memos-cloud-openclaw-plugin' or 'MemoryOS' packages. The rule identifies instances where this binary is spawned as a child process of a language runtime (Node.js or Python) when the execution originates from specific directory paths associated with these packages, or when the parent process command line indicates these packages are being initialized.
Detects the execution of the 'sckit' Go implant, a malicious binary associated with trojanized '@memtensor/memos-cloud-openclaw-plugin' or 'MemoryOS' packages. The rule identifies instances where this binary is spawned as a child process of a language runtime (Node.js or Python) when the execution originates from specific directory paths associated with these packages, or when the parent process command line indicates these packages are being initialized.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
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.
This rule detects malicious shell execution patterns associated with ClickFix-based social engineering campaigns, such as the Macfinger AMOS campaign. It monitors for the execution of common shell utilities (curl, wget, bash, sh) with suspicious command-line parameters ('force=1') interacting with known malicious IP addresses (45.150.33.128), as well as the execution of specific malicious files or network callbacks identified in these campaigns.
Detects the execution of bash commands containing base64 decoding instructions, often used by adversaries to decode and execute obfuscated scripts or payloads. The rule specifically looks for command lines invoking base64 along with keywords like 'echo' or 'reCAPTCHA', which are commonly associated with malicious droppers or phishing-related scripts.
Detects the installation of AI-related packages (e.g., mcp, tiktoken_mcp) via common package managers (pip, npm, docker) followed by an outbound network connection from the same host within 10 minutes. This behavior is consistent with supply chain attacks where trojanized AI/MCP components are used to initiate command-and-control communication shortly after deployment.
Detects malicious prompt injection payloads targeting AI agent frameworks, specifically designed to bypass Semantic Kernel's filter blocklist. The payload utilizes Python reflection mechanisms by crawling the type hierarchy (starting from a tuple) to locate and invoke 'BuiltinImporter.load_module()', effectively bypassing filters that look for direct references to forbidden modules or functions like '__import__', 'eval', or 'os'. This allows for indirect arbitrary command execution within the agent's application context.
Detects incoming HTTP POST requests to the Zimbra OnlyOffice document handler containing path traversal sequences (e.g., '..'). This pattern is indicative of an attempt to exploit CVE-2026-93643 by manipulating document save or callback paths to access unauthorized files on the server.
Detects the execution of known Python scripts (CES_Enroll.py, ntlm_ces_relay.py, ces_negotiate_ntlm.py) often associated with NTLM relay attacks or forced authentication techniques. These scripts leverage Python to interact with authentication protocols or relay requests.
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