Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

3,651 detections

Detects theft of browser session cookies for account takeover
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Darshan Thummar@Mighty
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Detections.ai Community
4 months ago
002
Detects spinning up of virtual machines to conduct malicious activity in isolation
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Darshan Thummar@Mighty
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Detections.ai Community
4 months ago
002
This rule detects a high frequency of successful network connections from a single device to multiple unique destination IP addresses within a one-hour window. The targeted ports (445, 139, 3389, 22, 21) are commonly used for remote administrative access, file transfers, and remote shell services, which are frequently leveraged by adversaries for lateral movement. The threshold of 3 unique targets in an hour may indicate automated scanning or credential brute-forcing activity across the network.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
003
Detects network flows to RustDesk relay server ports (21115, 21116, 21117) characterized by anomalous connection patterns. The rule identifies hosts exhibiting rapid, repeated connection attempts or connections to multiple distinct relay IP addresses within a short timeframe. This behavior is consistent with the 'rustdesk-session-permission-pocs' technique, which may indicate an attacker attempting to establish a remote session while bypassing the standard permission handshake exchange required by the application.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
001
Identifies Node.js or Python processes attempting to download configuration-like files (e.g., .env, .env.example) from GitHub's raw content domain. This pattern is characteristic of the second-stage payload delivery in the Lazarus Group's Graphalgo campaign.
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nomit vyas@xoxo
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Detections.ai Community
4 months ago
107
Detects network connections attempting to exfiltrate data via Discord webhooks. This rule specifically looks for POST requests to the Discord API webhook endpoint.
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nomit vyas@xoxo
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Detections.ai Community
4 months ago
104
Detects the macOS.Gaslight embedded Python collection module executing sequential reconnaissance functions: collect_system_info(), collect_running_processes(), collect_applications(), and collect_terminal_history() via ps aux and system_profiler, consistent with DPRK-aligned macOS.Gaslight stealer activity.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
104
Detects shell commands querying attacker-controlled domains disguised as Apple driver stores to fetch malicious macOS backdoors, specifically looking for 'coreaudiod' or 'audio-issue-fix.sh' in the URL.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
0011
Detects the sudo phishing routine writing the XOR-encoded stolen macOS user password to the hidden ~/.zsh_cache file.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
3011
Detects indicators of an npm infostealer campaign, specifically identifying the execution of obfuscated JavaScript payloads disguised as font files (e.g., fa-solid-400.woff2) or eslint-loaders by Node.js, and the creation of a '_V' file used as a persistence marker to prevent redundant execution.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
103
Detects anomalous activity associated with Amazon Q processes, including unauthorized access to SSH agent binaries, attempts to read SSH configuration files or keys in ~/.ssh/, and suspicious outbound network connections over port 22, potentially indicating lateral movement.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects the creation or modification of '.amazonq.mcp.json' files associated with the Model Context Protocol (MCP) in VS Code or similar IDE environments, alongside the subsequent spawning of shell interpreters (bash, sh, cmd, powershell, python, npx) from these IDE processes. The rule further flags these events as 'HIGH' priority if the command line references sensitive patterns like AWS credentials or SSH/AWS paths, suggesting potential credential harvesting or unauthorized post-exploitation activity originating from the IDE environment.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects instances where the Amazon Q language server or VS Code extension host spawns suspicious child processes, such as shells, interpreters (python, bash, powershell), or utilities commonly used to query or extract AWS cloud credentials.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects instances where common shell or command-line tools are spawned by Amazon Q processes (amazonq-language-server) or development-related processes (Code.exe, node) shortly after the creation or access of the 'mcp.json' configuration file within an '.amazonq' directory. This behavior may indicate an attacker using development tool vulnerabilities or compromised extensions to execute arbitrary commands.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects the creation of an mcp.json file within the .amazonq directory, followed shortly by the execution of suspicious child processes (bash, python, curl, etc.) by VS Code (Code.exe). This pattern is often indicative of an adversary abusing developer tools or IDE extensions to perform credential discovery or data exfiltration from a development environment.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
102
Detects outbound network communication from node.exe to the domain 'stitch-production.org'. This domain is associated with the 'Miasma' (also known as Mini Shai-Hulud) campaign, which uses malicious npm packages with post-install scripts to steal developer credentials, including Git, Docker, SSH, and cloud service configuration files.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
This rule detects DNS queries to known public tunneling service domains, such as devtunnels.ms, loophole.site, loca.lt, and bore.pub, originating from processes other than the legitimate developer tunneling tools (devtunnel.exe, code.exe, code-tunnel.exe). This activity is highly indicative of unauthorized remote access or command-and-control communication.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
102
Detects the initial stage of the Meow RAT ClickFix campaign, specifically targeting fileless zsh loaders. This rule identifies command-line executions involving 'zsh', 'bash', or 'sh' that combine 'eval', 'base64', 'gzip', and either 'curl' or 'osascript', often with redirection to /dev/null. This pattern is indicative of a gzip+base64 encoded heredoc being fetched via curl and executed in memory, followed by osascript for further actions.
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nomit vyas@xoxo
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Detections.ai Community
4 months ago
204
Detects command line activity indicative of an attempt to access or extract browser-related files such as 'Cookies' or 'Local State', which are commonly associated with session theft or credential harvesting from major web browsers like Chrome, Firefox, Edge, and Safari.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
003
Looks for various IDE processes making network connections direct to IP. Excludes private IP ranges but might need contextual exclusions too for environment
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Niall Dunne@Xavier
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Detections.ai Community
4 months ago
3020
This rule detects network connections made to specific non-standard ports (7777, 8080, 8443) where the remote URL contains substrings associated with proxy or tunneling activities ('proxy', 'tunnel', 'hide'). This behavior is commonly associated with malware attempting to evade security controls by routing traffic through unauthorized intermediaries or obfuscated tunnels.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
103
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