Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
61,044 detections
Filters
Last updated
All Time
Detection languages
23,953
16,903
4,364
4,342
3,270
Contributors
11,679
8,654
7,555
6,800
4,504
Categories
20,589
11,933
5,910
5,193
4,872
Platforms
40,153
7,368
6,547
3,915
3,691
Products / Services
10,809
9,795
6,757
4,421
3,770
MITRE Techniques
18,176
15,735
12,661
8,477
6,293
CVEs
71
71
64
58
49
IDS Classtypes
1,937
503
461
381
237
IDS Protocols
2,431
869
408
324
97
This rule detects a multi-stage attack chain targeting a single user within a 2-hour window. It identifies the combination of email bombing (a distraction technique), an incoming external or anonymous Teams call (social engineering channel), and the installation of common remote access tools (e.g., AnyDesk, TeamViewer) on the same host.
Detection of suspicious network traffic directed toward Slack APIs, characterized by the use of hardcoded Slack bot tokens and specific communication patterns associated with the 'indexed-btree' npm malware family, indicating potential C2 communication or data exfiltration.
Detects Azure AD sign-in events indicative of a session token replay attack. The rule identifies successful sign-ins where the traffic source originates from known residential proxy infrastructure (anonymizing services often used by attackers) and the authentication process lacks a fresh interactive MFA challenge, suggesting the use of a stolen, valid session token.
This rule detects the use of specific tools associated with credential dumping and memory forensics, including Dokan driver installations for file system mounting, the use of DumpIt for creating memory dumps, and the subsequent analysis of these dumps using MemProcFS to access sensitive process memory information such as LSASS minidumps.
Detects the abuse of the forfiles.exe utility to indirectly execute command-line interpreters such as cmd.exe, powershell.exe, or other common LOLBins. Adversaries use this technique to bypass security controls that monitor or restrict direct execution of these interpreters.
Detects the invocation of Windows Subsystem for Linux (WSL) binaries (wsl.exe or wslconfig.exe) using command-line arguments that enable arbitrary command execution, such as -e, --exec, or shell interpreters (bash -c, sh -c), or web-based retrieval tools like curl/wget. This technique is often used to execute commands or download payloads within a Linux environment on Windows, potentially bypassing security controls focused on native Windows processes.
Detects instances where AI coding assistants or tools (e.g., Claude, Copilot, Gemini) invoke git.exe to clone or fetch repositories from non-standard (non-GitHub) hosts, followed by a checkout operation within a short timeframe. This behavior may indicate an attacker using automated tools to stage or exfiltrate sensitive code repositories to unauthorized infrastructure.
Detects a multi-stage attack pattern against publicly exposed AI service endpoints. The detection correlates: (1) Enumeration of sensitive AI/MCP-related API endpoints (minimum 3 distinct hits) in a 10-minute window; (2) Subsequent POST requests to AI service endpoints within 15 minutes of the enumeration; and (3) A spike of 5 or more server errors (HTTP 5xx) within 10 minutes following the POST activity. This pattern suggests automated reconnaissance followed by attempted exploitation of exposed AI model interfaces or orchestration services. Covers T1595.002, T1190
Detects potential multimodal prompt injection attacks where an AI agent process ingests a file (PDF, image, etc.) from a browser or mail client and subsequently performs suspicious downstream activity, such as spawning a shell with execution primitives or making network connections to rare, non-reputable external domains. Covers T1204, T1059, T1105
This rule monitors for DNS queries and network connections to known infrastructure domains associated with the threat group UTA0565. It acts as an indicator of compromise (IOC) sweep to identify internal systems attempting to communicate with malicious command-and-control (C2) servers identified by typosquatting and registration-pattern analysis.
This rule monitors for DNS queries and network connections to known infrastructure domains associated with the threat group UTA0565. It acts as an indicator of compromise (IOC) sweep to identify internal systems attempting to communicate with malicious command-and-control (C2) servers identified by typosquatting and registration-pattern analysis.
Detects outbound network connections to specific IOCs associated with UTA0565 threat activity, including the use of an exploit-loader path (/config.html) on impersonated decoy sites.
This rule detects potentially malicious child processes spawned by Visual Studio Code (Code.exe) when using VS Code tasks (tasks.json). It identifies suspicious CLI arguments often associated with downloading, executing, or obfuscating scripts (e.g., PowerShell, curl, python, mshta) that are not part of standard development workflows like npm, yarn, or git, which are explicitly filtered out as noise.
KQL Query
KQL Query
KQL Query from file: Network detection - C2 domains and static key
KQL Query from file: Network detection - C2 domains and static key
KQL Query from file: Network detection - C2 domains and static key
This rule detects internal users submitting potentially sensitive data to public generative AI applications (e.g., ChatGPT, Claude, Gemini) where Microsoft Purview DLP or a comparable inspection service has triggered a policy match. It correlates cloud application outbound signals with content inspection logs to identify high-risk exfiltration events while excluding sanctioned enterprise-licensed AI instances.
This rule detects internal users submitting potentially sensitive data to public generative AI applications (e.g., ChatGPT, Claude, Gemini) where Microsoft Purview DLP or a comparable inspection service has triggered a policy match. It correlates cloud application outbound signals with content inspection logs to identify high-risk exfiltration events while excluding sanctioned enterprise-licensed AI instances.
KQL Query from file: Network detection - C2 domains and static key
Page 465 of 2907