Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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IDS Classtypes
1
Detects evidence of active exploitation targeting the libarchive ZIP entry declared-vs-actual size boundary vulnerability. The rule identifies the execution of known proof-of-concept (PoC) scripts (make_debuginfod_zip.py, run_stock_marker.py) as well as the creation of specific marker files or CLI output from bsdunzip/bsdtar that confirm successful boundary exploitation.
This rule detects suspicious activity associated with the BeepRAT malware loader chain. It monitors for the execution of TCC.exe (a common name for Tiny C Compiler used by some malwares for dynamic compilation) with specific command-line arguments like -nostdlib and -run, as well as the spawning of suspicious child processes (cmd.exe, powershell.exe, or conhost.exe) by TCC.exe or the presence of a temp.bin file in the command line, which is indicative of BeepRAT shellcode loading behavior.
Detects suspicious subprocesses spawned by IDE or extension host processes (like VS Code or Amazon Q) that execute AWS CLI commands to enumerate identity or immediately exfiltrate data via curl/wget, indicating potential credential abuse by malicious plugins or MCP servers.
This rule correlates suspicious process initiation originating from common web browsers or document handlers (e.g., encoded PowerShell, obfuscated CMD) with subsequent high-impact activities such as QEMU emulator launch, local account creation, DLL side-loading, volume shadow copy deletion, or creation of ransom-related files. This detection follows a multi-stage logic to identify potentially advanced threats or ransomware precursors within a 4-hour window.
Detects execution of WMI queries against Win32_OperatingSystem and CIM_Memory classes by processes identified as associated with BeepRAT (e.g., HFY.exe or processes within TCC paths). This behavior is characteristic of post-infection system enumeration, hardware ID generation, and environmental keying used in operations such as DragonClone.
Detects activity indicative of container escape attempts, specifically identifying the use of 'docker cp' with path traversal sequences to manipulate host files, or the unauthorized execution of shells and utilities directly spawned by the container runtime daemon (dockerd). It also monitors for execution patterns associated with known container escape proof-of-concept scripts.
Detects potential container breakout or privilege escalation attempts originating from Gitea act-runner processes. The rule monitors for the execution of containers with dangerous security configurations (e.g., host PID/IPC namespace, privileged capabilities, disabled security modules) or the use of nsenter to break out of a container into the host environment.
Detects a multi-stage attack where an adversary uses a fake job interview theme to lure a user into cloning a malicious repository. The repository contains a Model Context Protocol (MCP) configuration file that, when opened in an IDE like VS Code, Cursor, or Windsurf, leads to the execution of unauthorized or suspicious child processes.
Detects the creation of Model Context Protocol (MCP) server configuration files (such as .mcp.json or those in .vscode/ and .amazonq/ directories) shortly after a Git operation (pull, fetch, merge, or clone). This pattern is indicative of a supply chain attack where a contributor introduces malicious MCP configurations into a workspace, which are subsequently loaded by development tools like VS Code, Cursor, or language servers to execute arbitrary code or exfiltrate data.
Detects the use of the 'docker cp' command with suspicious path traversal characters or known PoC artifacts in the destination parameter. This behavior is indicative of an attempt to exploit path traversal vulnerabilities in the Docker daemon (such as those allowing container escape) by writing files outside the container's intended scope onto the host filesystem.
Detects Gitea act_runner spawning Docker containers with dangerous runtime flags (e.g., --pid=host, --privileged, --cap-add=ALL) that facilitate host namespace escape. This activity is indicative of exploitation of CVE-2026-20896, where malicious CI/CD workflow YAML files inject these options to break out of the container sandbox and access the host filesystem.
Detects exploitation attempts against the Flowise MCP environment variable case-sensitivity vulnerability. Attackers can leverage a lowercase 'node_options' environment variable on Windows to bypass Flowise security denylists, allowing the injection of arbitrary JavaScript via the Node.js --require flag. The rule also monitors for the execution of associated proof-of-concept (PoC) python scripts and markers.
Detects AnyDesk spawning suspicious child processes (cmd, powershell, etc.) indicative of local privilege escalation via the AnyDesk printer COM object impersonation vulnerability. This technique involves an attacker-controlled process communicating with the AnyDesk service's named pipe (adprinterpipe) to trigger code execution in the context of the LocalSystem AnyDesk service.
This rule detects the execution of common command-line interface tools (such as PowerShell, cmd, wscript, and certutil) spawned by the SimpleHelp remote support binary ('simplehelp.exe'). It also monitors for specific network connections associated with the SimpleHelp infrastructure (IP 96.126.130.126 on port 58942) that may indicate remote support activity or misuse of the platform.
Detects potential exploitation attempts involving ImageMagick and Ghostscript. It monitors for two primary suspicious behaviors: ImageMagick spawning Ghostscript from non-standard or hijackable file paths, and Ghostscript spawning shells or common script interpreters, which is a common indicator of command injection via image processing delegates.
This rule detects a two-stage DLL sideloading chain associated with Mustang Panda campaigns, specifically utilizing the SHARDLOADER and ZOHOMURK malware components. It monitors for the loading of malicious DLLs ('SolidPDFCreator.dll', 'ctxmui.dll') by specific binaries, as well as the execution of associated staging processes and file creation events in public directories.
Detects the creation of scheduled tasks using schtasks.exe or at.exe where the command line contains suspicious indicators such as execution from AppData/Temp directories, use of LOLBins (rundll32, regsvr32, powershell), encoded commands, or suspicious command-line patterns, specifically when the initiating process is not signed by Microsoft.
This rule detects the use of native Windows utilities to inhibit system recovery (e.g., deleting shadow copies or boot configuration changes) and to clear system event logs. These behaviors are common precursors or indicators of post-exploitation activity, such as ransomware deployment or intrusion cleanup.
Detects the execution of known suspicious files located in non-standard or typically restricted paths such as ProgramData, Public Documents, or disguised as benign file names like 'Project Proposal.exe'.
Detects execution of the SharpADWS reconnaissance tool or suspicious outbound network connections to Active Directory Web Services (ADWS) port 9389. This activity is used by threat actors, such as Mustang Panda, to perform Active Directory reconnaissance by bypassing standard LDAP logging.
Detects Visual Studio Code or Cursor IDE spawning interpreter processes like node.exe or python.exe. This behavior is indicative of a malicious .vscode/tasks.json configuration leveraging the 'runOn': 'folderOpen' feature to achieve automatic execution of code upon opening a workspace, a technique associated with the Lazarus Group 'Contagious Interview' campaign.
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