Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
694 detections
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This rule detects the use of 'npm' or 'node' to install packages from a registry other than trusted, standard registries (e.g., npmjs.org, GitHub). It specifically monitors command lines involving 'claude-code' that utilize custom, non-standard registry URLs. This behavior is indicative of potential supply chain attacks or the installation of unauthorized/malicious dependencies.
Detects BeaverTail JavaScript-based loader malware hidden inside NPM packages, distributed via GitHub or Bitbucket during fake technical interviews
Detects BeaverTail JavaScript-based loader malware hidden inside NPM packages, distributed via GitHub or Bitbucket during fake technical interviews
This rule monitors for a multi-stage attack pattern involving two potential indicators: first, it identifies phishing emails containing a 'Google Docs' link combined with an attachment named 'API Logic Flaw'. Second, it detects browser activity involving the paste of JavaScript code or suspicious browser clipboard activity, which may indicate an attacker attempting to execute malicious scripts directly in the user's browser context.
This rule detects potentially malicious process execution chains where VBScript or unknown/suspicious binaries (such as ProfileQuickHost.exe) are used to launch Node.js processes, specifically targeting JavaScript files or VBScript agents. This pattern is often associated with the execution of remote access trojans (RATs) or custom malware loaders.
This rule detects the execution of npm or node.js commands involving specific, potentially malicious package names or internal project naming patterns often associated with dependency confusion or supply chain attacks. It monitors npm/node CLI arguments for targeted library names or installation commands that deviate from standard organizational behavior.
Detects the GHAPPIER loader pattern: a top-level require('https').get() call to the primevector-app924560.vercel.app C2 that evals the response, disguised inside a large benign-looking JavaScript benchmark file
Detects the GHAPPIER loader pattern: a top-level require('https').get() call to the primevector-app924560.vercel.app C2 that evals the response, disguised inside a large benign-looking JavaScript benchmark file
Detects the GHAPPIER loader pattern: a top-level require('https').get() call to the primevector-app924560.vercel.app C2 that evals the response, disguised inside a large benign-looking JavaScript benchmark file
Detects the execution of Ruby or Yard processes where specific command-line arguments (e.g., --load) are used to invoke potentially malicious Ruby script files like evil.rb, loader.rb, or script.rb. This pattern is indicative of an adversary leveraging existing legitimate tools to execute arbitrary script code.
Detects the Kimsuky APT-C-55 'Stella_Gary' attack chain, where PowerShell is used to download a JavaScript verification script from an external C2 (InfinityFree), followed by the execution of that script via cscript.exe in temporary directories. This behavior is used to bypass anti-bot mechanisms and retrieve secondary payloads from hardcoded C2 infrastructure.
Detects the Kimsuky APT-C-55 'Stella_Gary' attack chain, where PowerShell is used to download a JavaScript verification script from an external C2 (InfinityFree), followed by the execution of that script via cscript.exe in temporary directories. This behavior is used to bypass anti-bot mechanisms and retrieve secondary payloads from hardcoded C2 infrastructure.
Detects the Kimsuky APT-C-55 'Stella_Gary' attack chain, where PowerShell is used to download a JavaScript verification script from an external C2 (InfinityFree), followed by the execution of that script via cscript.exe in temporary directories. This behavior is used to bypass anti-bot mechanisms and retrieve secondary payloads from hardcoded C2 infrastructure.
Detects the creation of a scheduled task using schtasks.exe where the command line involves 'MicrosoftNodeRuntimeUpdater' and references 'node.exe' or '.js' files, specifically when initiated by script engines like node.exe, wscript.exe, or cscript.exe, while excluding known legitimate nodejs installation paths.
Detects the creation of a scheduled task using schtasks.exe where the command line involves 'MicrosoftNodeRuntimeUpdater' and references 'node.exe' or '.js' files, specifically when initiated by script engines like node.exe, wscript.exe, or cscript.exe, while excluding known legitimate nodejs installation paths.
This rule detects rapid, repetitive state change operations (such as think, act, or mode changes) occurring within the Microsoft Edge browser context when interacting with Microsoft domains. This behavior is indicative of automated browser interactions, such as those performed by botnets, automated testing frameworks, or potentially malicious browser automation scripts.
Detects high-frequency, automated interactions with popular AI assistant web interfaces (e.g., Gemini, Perplexity, Claude, Copilot) from common browser processes. This pattern often indicates unauthorized automated data submission or scraping, which may follow or facilitate automated exfiltration of browser-resident data.
Detects the creation of a scheduled task using schtasks.exe where the command line involves 'MicrosoftNodeRuntimeUpdater' and references 'node.exe' or '.js' files, specifically when initiated by script engines like node.exe, wscript.exe, or cscript.exe, while excluding known legitimate nodejs installation paths.
This rule detects potential reflective code injection or in-memory loading (fileless) where a DLL or PE image is loaded by mshta.exe or powershell.exe, but the module load event lacks a valid file path on disk (or indicates a device path). This behavior is often associated with the execution of malicious payloads such as the Amatera loader, where payloads are executed directly in memory to evade file-based security detections.
This rule monitors for a multi-stage attack pattern involving two potential indicators: first, it identifies phishing emails containing a 'Google Docs' link combined with an attachment named 'API Logic Flaw'. Second, it detects browser activity involving the paste of JavaScript code or suspicious browser clipboard activity, which may indicate an attacker attempting to execute malicious scripts directly in the user's browser context.
This rule detects potential reflective code injection or in-memory loading (fileless) where a DLL or PE image is loaded by mshta.exe or powershell.exe, but the module load event lacks a valid file path on disk (or indicates a device path). This behavior is often associated with the execution of malicious payloads such as the Amatera loader, where payloads are executed directly in memory to evade file-based security detections.
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