Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects the forced removal of legitimate cryptocurrency wallet applications (Ledger Wallet, Trezor Suite, Exodus) followed by the extraction of new applications into the /Applications directory on macOS. It also looks for chmod commands to make the new applications executable and attempts to download suspicious zip files from 'wusetail.com'. This activity is indicative of the AMOS malware campaign, which aims to replace legitimate wallet applications with trojanized versions to steal cryptocurrency.
This rule detects the use of common utilities to transfer executable files (shell scripts, python scripts, perl scripts, or ELF binaries) between systems.
This rule detects various indicators associated with the 'Fake Clawdbot VS Code Extension' malware, which is known to install the ScreenConnect Remote Access Trojan (RAT). Detection logic includes suspicious domain names, specific file names downloaded from those domains or Dropbox, known malicious IP addresses, specific SHA256 hashes of malicious files, outbound network connections on port 8041 (excluding common private/reserved IP ranges), ScreenConnect service installations/starts, and suspicious file writes or process executions from temporary directories related to ScreenConnect or 'Code.exe'.
This detection identifies network requests matching a URL pattern used by the Coruna iOS exploit kit to deliver encrypted binary payloads. The framework generates resource URLs using a 40-character hash and serves them as files ending in ".min.js".
Attackers do not only use emojis in the subject. Sometimes they also use them in the file name itself to make the file look more attractive or legitimate. Based on my experience, I am not expecting legitimate files names with icons so it can be an interesting case to easily convert the hunting into a detection. For example:
📄Invoice.pdf
🔐Reset_Password.html
📦Delivery_Document.zip
This can help find:
- Suspicious files dropped on disk
- Files downloaded from phishing emails
- User-downloaded scam files
- Payloads with social engineering names
📄Invoice.pdf
🔐Reset_Password.html
📦Delivery_Document.zip
This can help find:
- Suspicious files dropped on disk
- Files downloaded from phishing emails
- User-downloaded scam files
- Payloads with social engineering names
Identifies file downloads (archives, shortcuts) originating from a legitimate OAuth provider URL that contains error parameters. This pattern is indicative of an attacker abusing OAuth error redirection to deliver a malicious payload.
This rule detects various stages of the VOID#GEIST multi-stage Python loader as described in the Securonix blog. It identifies initial batch file execution, Chrome decoy PDF lures, hidden PowerShell relaunching of the batch file, persistence via the Startup folder, curl commands downloading zip payloads, Python embedded runtime downloads, and final Python payload execution. The rule is designed to catch the distinct command-line patterns associated with each stage of this specific malware.
This rule detects suspicious PowerShell activity that involves hidden windows, execution policy bypass, and attempts to download or execute files. It specifically looks for PowerShell processes launched by common parent processes like explorer.exe, cmd.exe, mshta.exe, wscript.exe, cscript.exe, or rundll32.exe, combined with command-line arguments indicative of stealthy execution and payload delivery. The rule identifies two main scenarios: 'Hidden Downloader and Execution' where PowerShell is used with hidden window styles and download commands, and 'Inline Launcher and Payload Delivery' where PowerShell is used with no profile and download/execution commands.
Identifies file downloads (archives, shortcuts) originating from a legitimate OAuth provider URL that contains error parameters. This pattern is indicative of an attacker abusing OAuth error redirection to deliver a malicious payload.
Detects network connections to Hugging Face to download a large Large Language Model (LLM) module, a technique used by the SURXRAT Android RAT to induce network lag and degrade device performance.
Detects a PowerShell command pattern commonly used by the IClickFix framework. This involves using a hidden window to download a script (often .ps1 or .json) and execute it, bypassing the execution policy. This is a common technique following a "ClickFix" social engineering lure.
Detects instances where a development environment like VS Code or Cursor spawns a shell process that then uses a download utility to fetch and execute remote content. This is a known TTP for the 'Contagious Interview' campaign which abuses IDE task auto-execution features.
This rule detects various stages of an attack chain, starting from an Apache ActiveMQ exploit (CVE-2023-46604) leading to LockBit-style ransomware. It identifies process creation anomalies (java.exe spawning certutil.exe for downloads), network connections to known Metasploit C2 infrastructure, the presence of specific ransomware file hashes, and attempts to clear Windows event logs, all indicative of the described attack scenario.
Detects curl or wget download followed by chmod and execution, consistent with staged malware delivery used by malicious OpenClaw skills distributing AMOS.
Detects a Java process spawning a command shell to download a file using the certutil.exe utility. This behavior was observed in the exploitation of Apache ActiveMQ (CVE-2023-46604), where the threat actor used this technique to download a secondary payload.
Detects the Java process, commonly associated with Apache ActiveMQ, spawning certutil.exe to download a file from a remote URL. This behavior is a strong indicator of initial compromise via vulnerabilities like CVE-2023-46604.
This rule detects suspicious Spring bean XML content, specifically looking for indicators related to the exploitation of Apache ActiveMQ CVE-2023-46604. It targets XML payloads that attempt to execute commands using 'ProcessBuilder' and download files via 'certutil -urlcache' from an HTTP source, consistent with observed attack patterns.
Detects a PowerShell process initiating a network connection to download an image or text file from domains associated with a Remcos RAT campaign. In this campaign, PowerShell is used to download a steganographic image containing the next stage payload.
This rule detects attempts to download Android Application Package (APK) files directly to an endpoint. This activity is often associated with 'quishing' (QR code phishing) attacks, where users are tricked into scanning a malicious QR code that leads to a direct APK download, bypassing official app store security checks. The rule specifically looks for network connection success events where the remote URL or additional fields contain '.apk'.
This detection identifies suspicious command-line pipelines commonly used in "ClickFix" attacks. It specifically searches for the use of 'curl' or 'wget' to download a payload that is immediately executed via a shell, often hidden within a subshell `$(...)` or piped directly to an interpreter. This "download and execute" pattern is a high-fidelity indicator of a successful ClickFix lure, where a user has been tricked into running a malicious command.
This rule detects attempts to download the 'clawd.bot' or 'openclaw.ai' installation scripts using various command-line tools. It specifically looks for the use of 'curl', 'wget', 'aria2c', 'fetch', 'powershell', 'pwsh', 'certutil', 'bitsadmin', or 'mshta' when their command lines contain either 'clawd.bot/install.sh' or 'openclaw.ai/install.sh'. This activity is indicative of potential malware deployment or initial access attempts related to the OpenClaw/Clawd threat.
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