Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects invisible/non-printing Unicode codepoints (zero-width chars, bidi overrides, variation selectors, Unicode tag characters, and Private Use Area icon-font codepoints) embedded in process command lines - covering both classic command/script obfuscation and the emerging use of hidden codepoints to smuggle AI prompt-injection payloads into content later processed by AI copilots/agents. Tightened to require 2+ high-confidence codepoint hits (or 1 from a known scripting host/LOLBin), and gates Private-Use-Area-only matches (a common legitimate icon-font false-positive source) to scripting hosts with 5+ hits, maps to T1027.018.
Detects invisible/non-printing Unicode codepoints (zero-width chars, bidi overrides, variation selectors, Unicode tag characters, and Private Use Area icon-font codepoints) embedded in process command lines - covering both classic command/script obfuscation and the emerging use of hidden codepoints to smuggle AI prompt-injection payloads into content later processed by AI copilots/agents. Tightened to require 2+ high-confidence codepoint hits (or 1 from a known scripting host/LOLBin), and gates Private-Use-Area-only matches (a common legitimate icon-font false-positive source) to scripting hosts with 5+ hits, maps to T1027.018.
Detects MayaBot's scheduled-task persistence chain by correlating two signals on the same device within a 60-minute window: (1) schtasks.exe creating a daily task referencing a hidden batch script (update.bat/backup.bat/firewall-update.bat) under AppData\Local, spawned from wscript.exe/cscript.exe/cmd.exe, and (2) cmd.exe launching a hidden-window PowerShell process referencing the same batch scripts under AppData\Local. Requiring both signals together, anchored to the AppData\Local path, sharply reduces false positives compared to alerting on either behavior alone.
Detects network connections to known SideCopy/ReverseRAT command-and-control infrastructure, including a static C2 IP address and two C2/hosting domains (matched exactly and as proper subdomains to avoid substring false positives).
Detects mshta.exe spawning suspicious child processes (cmd.exe, powershell.exe, or reg.exe) that are characteristic of the ReverseRAT backdoor. The rule identifies common discovery commands or persistence attempts via Registry Run keys triggered from mshta.exe.
Detects the execution of known NTLM Certificate Enrollment Service (CES) relay tools alongside subsequent outbound network connections to Active Directory Certificate Services (AD CS) CES enrollment endpoints. This behavioral pattern indicates an adversary attempting to relay NTLM authentication to an AD CS server to request a certificate, typically for privilege escalation or persistence.
Detects the execution of known NTLM Certificate Enrollment Service (CES) relay tools alongside subsequent outbound network connections to Active Directory Certificate Services (AD CS) CES enrollment endpoints. This behavioral pattern indicates an adversary attempting to relay NTLM authentication to an AD CS server to request a certificate, typically for privilege escalation or persistence.
Detects DNS-based Kerberos coercion attacks where adversaries inject marshaled credential structures into DNS records to spoof SPNs and redirect authentication such as in CVE-2025-33073. This detection leverages suricata looking for specific CREDENTIAL_TARGET_INFORMATION structures in DNS queries.
This rule detects potential remote code execution (RCE) attempts targeting AI agent applications, specifically those utilizing the Semantic Kernel framework. It identifies suspicious command-line patterns indicative of a Python type hierarchy traversal attack (CVE-2026-26030), which is used to bypass security blocklists within an eval() sink to execute arbitrary commands like 'os.system()'. The rule monitors for the spawning of common shell or utility processes by Python or .NET processes associated with AI agent activity.
Detects a potential post-exploitation attack chain where a user receives a phishing lure and subsequently executes a rapid burst of distinct process commands on the same host. This pattern is consistent with an adversary utilizing an LLM to iteratively troubleshoot and refine command syntax during a post-exploitation phase.
Detects a potential post-exploitation attack chain where a user receives a phishing lure and subsequently executes a rapid burst of distinct process commands on the same host. This pattern is consistent with an adversary utilizing an LLM to iteratively troubleshoot and refine command syntax during a post-exploitation phase.
Detects a potential post-exploitation attack chain where a user receives a phishing lure and subsequently executes a rapid burst of distinct process commands on the same host. This pattern is consistent with an adversary utilizing an LLM to iteratively troubleshoot and refine command syntax during a post-exploitation phase.
Detects instances where package management tools (pip, npm, docker) spawn child processes that immediately attempt to read sensitive files (SSH keys, cloud/container credentials) or perform outbound network connections. This behavior is indicative of a trojanized supply-chain package executing malicious post-install logic to exfiltrate secrets or establish initial communication with a C2 server.
Detects non-browser and non-approved application processes establishing outbound network connections to known public LLM/AI API endpoints, such as OpenAI or Azure OpenAI services. This behavior is indicative of potential command-and-control (C2) activity where an attacker abuses legitimate AI APIs as a bidirectional communication channel to poll for instructions.
Detects the installation of a specific known malicious npm package named 'tw-pkgprobe-7731' via the command line, which may indicate a supply chain compromise or an attempt to execute malicious code within a development environment.
Detects execution of rundll32.exe from non-standard locations or utilizing specific exported DLL functions often associated with bypassing application whitelisting, executing scripts, or proxying malicious code execution.
Detects usage of the Windows certutil.exe utility with flags commonly used by adversaries to download files from remote URLs or decode base64 encoded files. These techniques are often utilized for ingress tool transfer or deobfuscating malicious payloads.
Detects instances where a trusted, system-protected executable loads a DLL file from a user-writable or temporary directory that is not digitally signed or has an invalid signature. This is a common indicator of DLL side-loading or DLL hijacking, where an adversary attempts to execute malicious code by placing a malicious DLL in a location searched by a legitimate process.
Detects the use of the BITSAdmin command-line utility to perform file downloads or add files to a transfer job. Adversaries may abuse the Background Intelligent Transfer Service (BITS) for downloading malicious files while evading detection or maintaining persistence.
Detects the use of the native Windows reg.exe utility to save the Security Account Manager (SAM) registry hive to a file. This technique is commonly used by adversaries to perform offline credential extraction or to dump local account password hashes.
Detects a sequence of events consistent with credential dumping of sensitive Windows registry hives (SAM, SYSTEM, SECURITY). The attack involves querying shadow copies using vssadmin, creating a symbolic link to the shadow copy volume via mklink, and copying the hive files from that location. Cleanup attempts using rmdir are also monitored.
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