Detections

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

40,050 detections

Detects text/report artifacts (markdown, JSON, plain text) produced by an autonomous AI-driven vulnerability research pipeline that decompiles binaries, traces cross-references, hypothesizes memory-safety flaws, and generates/debugs proof-of-concept exploits
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
001
Detects anomalous activity patterns consistent with automated firmware reverse engineering pipelines, specifically correlating the high-frequency execution of firmware analysis tools (e.g., binwalk, Ghidra) with the creation of vulnerability research knowledge base artifacts. This behavioral heuristic aims to identify potential AI-driven or automated zero-day discovery workflows by tracking tool usage density and output characteristics.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
001
This rule detects potential automated web scraping activity by identifying high-volume, repetitive network requests directed towards domains identified as government (.gov) or military (.mil). It correlates these network patterns with the execution of common browser automation frameworks (e.g., Puppeteer, Playwright) or headless browsers, indicating a likely coordinated scraping operation or bot activity.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
001
This rule detects potential automated web scraping activity by identifying high-volume, repetitive network requests directed towards domains identified as government (.gov) or military (.mil). It correlates these network patterns with the execution of common browser automation frameworks (e.g., Puppeteer, Playwright) or headless browsers, indicating a likely coordinated scraping operation or bot activity.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
001
This rule detects potential automated web scraping activity by identifying high-volume, repetitive network requests directed towards domains identified as government (.gov) or military (.mil). It correlates these network patterns with the execution of common browser automation frameworks (e.g., Puppeteer, Playwright) or headless browsers, indicating a likely coordinated scraping operation or bot activity.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
101
Detects artifacts of the winAgent v2.0 Windows implant line, including mod_* modules, WUEngine persistence binaries, and COM/CLSID hijack strings used by AI-assisted implant development
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
001
This rule detects unauthorized or suspicious automated scraping behavior by identifying periodic, non-interactive tasks that perform high-volume outbound network requests to multiple external hosts. It specifically filters for processes launched via scheduling mechanisms (Task Scheduler, cron) that exhibit indicators of anti-bot or proxy-rotation bypass techniques (such as usage of headless browser tools or proxy-related keywords in command lines). The rule is tuned to ignore legitimate system maintenance, update, and monitoring processes.
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Arnold Chan@slaz
Defender - KQL
2 months ago
001
Identifies instances of Google Chrome running on endpoints with version numbers below the threshold patched for CVE-2026-85046. This detection focuses on specific build numbers (e.g., 152.0.7977.82 for Windows/Linux) to identify potentially vulnerable browser installations in the environment.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
203
Detects processes that access sensitive browser credential or cookie files (e.g., Login Data, Cookies) followed by network activity within a 10-minute window, which is a common behavior pattern of information-stealing malware such as Amatera or ACR Stealer.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
107
Detects suspected exploitation of CVE-2026-81963, an Elevation of Privilege vulnerability in the Windows Update stack. The rule monitors for the creation of reparse points, junctions, or symbolic links within update staging paths by Windows Update processes, followed by either the spawning of suspicious child processes or unauthorized file writes/renames outside of expected directories, which are indicative of a privileged link-following exploit.
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Ankit Mehta@Secvyn
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SlimKQL
2 months ago
003
This rule detects unauthorized attempts to modify CrowdStrike Falcon sensor exclusion registry keys or commands involving DLL loading techniques that may indicate evasion preparation, specifically referencing potential FalconFlank-related activities. It filters out legitimate management activity from known service accounts, SCCM, and the CrowdStrike Falcon agent itself.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
6013
Detects instances where a development-oriented web server (such as Vite or Node.js) is configured to bind to all network interfaces ('0.0.0.0') and is simultaneously receiving inbound connections from non-private, external IP addresses on a common development port (5173). This rule filters out common CI/CD environments to focus on potentially insecure exposure of development tools to the public internet.
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Arnold Chan@slaz
Defender - KQL
2 months ago
000
This rule detects inbound HTTP requests targeting a Vite development server that attempt to access the '.env' configuration file via the '//@fs/' path, which is a known technique for sensitive file exposure in misconfigured Vite environments.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
000
Detects high-volume bursts of HTTP GET requests against specific paths associated with a Vite development server (/@vite/client, /@fs/, /src/) on port 5173. This pattern is indicative of automated reconnaissance or vulnerability scanning targeting an exposed development environment.
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Arnold Chan@slaz
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Hunters
2 months ago
000
Detects a sequence of events where a PDF file opened from a Microsoft Outlook content directory triggers an immediate subsequent execution of a Microsoft Edge process pointing to a Google Sites URL, or containing suspicious command line arguments often associated with malicious redirection or web-based credential harvesting.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
2 months ago
104
CloudSEK researchers uncovered BigBear 2.0, a global Microsoft 365 phishing-as-a-service operation targeting hundreds of organizations across 40+ countries. The investigation exposed the attacker’s admin panel, affiliate network, phishing infrastructure, and thousands of stolen credentials and session cookies, revealing how modern AiTM attacks can hijack authenticated sessions even after MFA.
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Arnold Chan@slaz
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Hunters
2 months ago
000
CloudSEK researchers uncovered BigBear 2.0, a global Microsoft 365 phishing-as-a-service operation targeting hundreds of organizations across 40+ countries. The investigation exposed the attacker’s admin panel, affiliate network, phishing infrastructure, and thousands of stolen credentials and session cookies, revealing how modern AiTM attacks can hijack authenticated sessions even after MFA.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
000
This rule monitors for network connections to known command-and-control (C2) IP addresses and the execution or presence of files matching known hashes associated with the 'PhantomC2' threat group or malware family. It correlates data from DeviceNetworkEvents, DeviceFileEvents, and DeviceProcessEvents to identify potential compromise.
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Arnold Chan@slaz
Defender - KQL
2 months ago
100
This rule monitors for network connections to known command-and-control (C2) IP addresses and the execution or presence of files matching known hashes associated with the 'PhantomC2' threat group or malware family. It correlates data from DeviceNetworkEvents, DeviceFileEvents, and DeviceProcessEvents to identify potential compromise.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
000
Detects a command shell (cmd.exe, powershell.exe, powershell_ise.exe, pwsh.exe) created with a SYSTEM SID whose immediate parent process is a POSITIVELY IDENTIFIED non-SYSTEM account running at Low/Medium integrity. Excludes known-benign SYSTEM-spawning binaries and blank-parent scheduled-task/service noise confirmed via live telemetry and attached evidence logs, and drops the prior TokenElevationTypeFull branch which mostly matched routine UAC-elevated admin activity rather than an actual SYSTEM token.
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Ethan Andrews@eandrews
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Federal Signal Detections
2 months ago
11027
The following analytic detects shells, scripting engines, and common post-exploitation utilities spawned as child processes of smsexec.exe.
smsexec.exe is the core SCCM SMS Executive service process and has no legitimate reason to launch interactive shells or scripting interpreters.
An attacker who plants a malicious adsource.dll in the SCCMProvider bin\X64 directory will obtain code execution in the SCCM service context, typically resulting in a SYSTEM-level child process being spawned under smsexec.exe.
If confirmed malicious, this activity represents successful exploitation of the SCCM SMS Executive service and should be treated as a full host compromise.
Splunk Security@SplunkSecurity
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Splunk Security Content
2 months ago
105
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