Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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IDS Classtypes
1
Detects the use of rundll32.exe to execute comsvcs.dll's MiniDump functionality against the LSASS process, a common technique for dumping credentials. The rule includes behavioral correlation by identifying the same user account executing this pattern on multiple devices within a one-hour window.
Detects the use of rundll32.exe to execute comsvcs.dll's MiniDump functionality against the LSASS process, a common technique for dumping credentials. The rule includes behavioral correlation by identifying the same user account executing this pattern on multiple devices within a one-hour window.
Detects a potential process hollowing technique where 'Finalized.dll' (loaded from unconventional locations like a ComponentsFolder or System32) is used to spawn 'clspack.exe' in a suspended state from a non-standard path (e.g., AppData\Microsoft). This sequence indicates an attempt to mask malicious execution under a legitimate process name.
Detects potential persistence attempts via registry modifications involving rundll32.exe. The rule monitors for two patterns: registry keys associated with shell commands for specific file types triggering rundll32.exe, and registry 'Run' keys using a 'Locked' value name with a custom URI handler, often indicative of malware or suspicious persistence mechanisms.
Detects potential persistence attempts via registry modifications involving rundll32.exe. The rule monitors for two patterns: registry keys associated with shell commands for specific file types triggering rundll32.exe, and registry 'Run' keys using a 'Locked' value name with a custom URI handler, often indicative of malware or suspicious persistence mechanisms.
Detects attempts to disable Windows Defender by either executing known Defender Control utilities or by modifying registry keys associated with the disabling of anti-spyware features or the WinDefend service startup.
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 the execution of known Python scripts (CES_Enroll.py, ntlm_ces_relay.py, ces_negotiate_ntlm.py) often associated with NTLM relay attacks or forced authentication techniques. These scripts leverage Python to interact with authentication protocols or relay requests.
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 an accelerated sequence of attack phases—specifically recon, privilege escalation, lateral movement, and persistence—occurring on a single device within a short timeframe (15 minutes). This behavioral pattern indicates potential automated or script-orchestrated intrusion 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 a browser or agentic-browser process initiates a file download and subsequently executes that same file within a five-minute window, without the intervention of a user-driven process like explorer.exe. This pattern is indicative of automated 'agentic' browser activity, potentially signifying hijacked web instructions or malicious automated tool execution flows.
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 anomalous activities within CI/CD runner environments, specifically targeting unauthorized processes attempting to access OIDC identity tokens or executing package publication commands (e.g., npm, twine) outside of standard runner execution workflows. This technique is consistent with supply chain compromise efforts to exfiltrate identity tokens and publish malicious artifacts.
Detects the execution of MicrosoftIME.exe or the creation of scheduled tasks referencing it from non-standard directories such as User, Temp, or AppData folders. This behavior is indicative of masquerading or persistence mechanisms where a malicious process mimics the legitimate Microsoft Input Method Editor (IME) binary.
Detects the presence of known Vidar infostealer samples by matching file hashes against a list of identified malicious artifacts. The rule monitors for file creation events, process execution (both as the primary process and as an initiating process), and network activity originating from these known malicious files.
Detects the BotHelper RAT utilizing its msedge_proxy.exe process to execute 'ClipperStart' or 'ClipperStop' commands. These commands are indicative of the malware's clipboard-address substitution functionality, which is used to redirect cryptocurrency transactions by modifying clipboard content.
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