Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

18,128 detections

Detects phishing messages that deliberately mix writing systems/scripts/homoglyphs in the Subject line as ONE corroborating signal within a broader, multi-signal phishing pattern. Hardened against false positives: brand/product tokens (e.g. Microsoft, PayPal) are stripped before the Latin-script check so a lone brand mention in non-Latin correspondence doesn't count as mixed-script; a weighted score (script-mixing=2, homoglyph=3, high-confidence phishing vocabulary=2, threshold=6) means no two of the three signal categories can reach the threshold alone — all three must co-occur before the rule fires.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
002
Detects autonomous behavior where AI-driven processes attempt multiple network connections (SMB, SSH, HTTP, RDP, WinRM) to diverse targets following failed access attempts. The rule correlates initial failure activity with subsequent credential-related events and new lateral movement traffic from the same agent process within a short window, suggesting adaptive adversary pivoting.
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Arnold Chan@slaz
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Hunters
1 month ago
002
Detects a multi-stage exfiltration sequence consisting of: (1) bulk file archival/compression using common utilities, (2) suspicious OAuth grant or service principal authorization, and (3) abnormal network egress volume to common ports. This pattern suggests an adversary is preparing data, establishing or leveraging an identity/application for cloud access, and subsequently exfiltrating data.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
204
Detects a behavioral fingerprint associated with the NeedyMantis group, characterized by the creation of a DLL and a identically-named, extensionless, encrypted archive file in the same directory within a short time window. This approach identifies the underlying packaging strategy rather than relying on static file names or known paths.
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Ankit Mehta@Secvyn
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SlimKQL
1 month ago
203
Detects .ps1-named files dropped to disk that are never actually executed by a PowerShell interpreter (powershell.exe / pwsh.exe) within a short window afterward. NeedyMantis's second-stage loader (e.g. encryptbase64.ps1) is raw x64 shellcode, not a real script -- it's read and executed directly by the dropping process, so no genuine PowerShell host process ever references the file by name. Replaces an earlier version of this rule that watched DeviceImageLoadEvents for a .ps1 extension: Windows can only emit an image-load event for a file with a valid PE header loaded via the OS loader, and raw shellcode has no PE header and is never mapped that way, so that approach would not have fired on this malware. Caveat: legitimate deployment tooling that stages a script for delayed or remote execution can also produce this create/execute mismatch; tune the window and add known-good deployment-tool exclusions for your environment.
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Ankit Mehta@Secvyn
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SlimKQL
1 month ago
003
Detects unauthorized file deletion activity performed directly by a Node.js process acting as a ChainScript RAT. The RAT uses a bundled node.exe process, operating within specific masquerading directories in the user profile, to execute file system operations such as recursive deletion without spawning child processes.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
2017
This rule detects potential persistence via scheduled tasks that masquerade as legitimate network components (e.g., 'System Health Monitor'), as well as abnormal use of WebDav via rundll32.exe or net.exe in the context of the Star Blizzard (COLDRIVER) campaign. It monitors for task creation/updates, schtasks command lines, registry artifacts related to task scheduling, and suspicious WebDav network utility usage, while excluding common security tool processes.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
002
This rule detects activities associated with the Star Blizzard (also known as APT28 or Callisto) group's CosmicPulse malware, specifically the downloader and Python-based backdoor. It monitors for suspicious CPL file execution via UNC paths by rundll32.exe or control.exe, unauthorized modifications to the HKCU\Software\Classes\.mollis registry key used for COM hijacking, and anomalous spawning of Python executables from control host processes in user-writable directories.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
002
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
204
Detects post-exploitation command execution originating from a compromised explorer.exe process. The rule identifies processes like cmd.exe, powershell.exe, or conhost.exe spawned by an explorer.exe instance that has previously loaded the malicious 'MicrosoftEdgeUpdateCore.dll' module, correlating this activity with the established 'tailcat.exe' command-and-control tunnel.
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Arnold Chan@slaz
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Hunters
1 month ago
004
Detects the Windows Installer service (msiexec.exe) being launched by known remote access software processes like msra.exe (Microsoft Remote Assistance) or anydesk.exe. This behavior is often associated with unauthorized software installation or payload delivery via remote support tools.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
105
Detects malicious instruction-override payloads, hidden HTML comments, or obscured text (e.g., zero-font size) in third-party content ingested into LLM/RAG systems, commonly used for indirect prompt injection.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
This rule detects various process injection techniques (such as CreateRemoteThread, QueueUserAPC, and remote memory writes) initiated by external processes targeting high-value, commonly abused Windows system processes like svchost.exe, lsass.exe, and explorer.exe. These techniques are often used by ransomware and other malware to hide malicious code execution within trusted system memory space.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
Detects suspicious command line patterns on macOS where base64 encoded strings are decoded and piped directly into a shell interpreter (bash/zsh/sh). This pattern is commonly used by adversaries to execute obfuscated payloads or scripts directly in memory.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
405
Detects network exploitation attempts targeting Fortinet FortiOS and FortiProxy vulnerabilities (CVE-2024-55591, CVE-2025-24472) involving authentication bypass via HTTP header manipulation (Forwarded, X-Forwarded-For) and unauthorized access to the /jsconsole endpoint.
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Arnold Chan@slaz
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Hunters
1 month ago
003
Detects network exploitation attempts targeting Fortinet FortiOS and FortiProxy vulnerabilities (CVE-2024-55591, CVE-2025-24472) involving authentication bypass via HTTP header manipulation (Forwarded, X-Forwarded-For) and unauthorized access to the /jsconsole endpoint.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
This rule correlates web clicks on Google Sites URLs containing keywords related to GlobalProtect with the subsequent creation or renaming of an unsigned or improperly signed GlobalProtect.msi file on the same endpoint within a 30-minute window. This behavior is indicative of a spearphishing attempt using a masqueraded landing page to deliver malicious or unauthorized software.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
103
Detects a fake ClaudeDesktop.exe installer / tampered libcef.dll sideload chain deploying the SectopRAT .NET RAT, requiring multiple corroborating indicators and a PE anomaly consistent with DLL sideloading rather than a single generic string
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
006
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
104
Detects a service principal attempting to delete multiple Azure SQL databases in a short timeframe, resulting in failures. This pattern is characteristic of malicious data destruction activity, such as that observed in Storm-3168 (JADEPUFFER) campaigns, but accounts for the possibility of misconfigured infrastructure-as-code pipelines by requiring a high volume of failed requests across distinct resources.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
104
This rule detects potential brute force or account compromise attempts by identifying user accounts that have successfully authenticated or initiated authentication events from two or more distinct IP addresses within the observed time window. It monitors Windows Event IDs 4624 (Successful Logon), 4648 (Logon attempted using explicit credentials), and 4776 (The domain controller attempted to validate the credentials for an account).
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
4156
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