Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
205 detections
Filters
Last updated
All Time
Detection languages
117
32
20
18
9
Contributors
72
45
32
9
8
Categories
105
95
39
34
28
Platforms
108
63
28
21
16
Products / Services
75
29
29
27
27
MITRE Techniques
18,108
15,613
12,573
8,384
6,203
CVEs
2
2
1
1
1
IDS Classtypes
24
3
3
2
IDS Protocols
23
5
1
1
1
Correlates devices touched by known IoC IP scan waves with PHP software inventory, vulnerability management data for PHP CVEs, and active PHP process execution telemetry to identify vulnerable exposed web servers.
Detects process command lines containing C2 operator start flags or strings alongside reconnaissance tools or platforms like fofa or skynet.
Detects the execution of two or more distinct Active Directory discovery, credential extraction, or coercion tools (such as NetExec, Kerbrute, noPac, PetitPotam, SoftPerfect Network Scanner, or Impacket scripts) on the same device within a 1-hour window.
Detects the deployment of the ARTEX AI penetration testing framework via Docker/Docker-compose combined with the execution of offensive security and scanning tools (such as nmap, sqlmap, nuclei, httpx, apktool, frida) on the same host within a specified timeframe.
Detects high volume and diverse URI requests targeting login, search, or inquiry endpoints on IIS servers within a short time window, indicative of web brute force or active reconnaissance scanning.
Detects potential vulnerability scanning, enumeration, or bulk data extraction against Request Tracker (RT) web paths by monitoring high request volumes, distinct URI counts, or large response byte sizes within CommonSecurityLog data.
Detects high volume and diverse URI requests targeting login, search, or inquiry endpoints on IIS servers within a short time window, indicative of web brute force or active reconnaissance scanning.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects clusters of high-volume external source IPs from multiple countries sweeping the same financial web services within an hour.
Detects clusters of high-volume external source IPs from multiple countries sweeping the same financial web services within an hour.
Detects clusters of high-volume external source IPs from multiple countries sweeping the same financial web services within an hour.
Detects API reconnaissance and endpoint scanning activity against Ollama servers by identifying sources probing multiple API endpoints within short timeframes, particularly when using HEAD requests or accessing diverse endpoint paths, which indicates systematic enumeration to map the API surface, discover hidden endpoints, or identify vulnerabilities before launching targeted attacks.
Detects clusters of high-volume external source IPs from multiple countries sweeping the same financial web services within an hour.
Detects clusters of high-volume external source IPs from multiple countries sweeping the same financial web services within an hour.
The following analytic detects the execution of tools commonly exploited by cybercriminals, such as those used for unauthorized access, network scanning, privilege escalation, password dumping or data exfiltration.
It leverages process activity data from Endpoint Detection and Response (EDR) agents, focusing on known attacker tool names.
This activity is significant because it serves as an early warning system for potential security incidents, enabling prompt response. If confirmed malicious, this activity could lead to unauthorized access, data theft, or further network compromise, posing a severe threat to the organization's security infrastructure.
It leverages process activity data from Endpoint Detection and Response (EDR) agents, focusing on known attacker tool names.
This activity is significant because it serves as an early warning system for potential security incidents, enabling prompt response. If confirmed malicious, this activity could lead to unauthorized access, data theft, or further network compromise, posing a severe threat to the organization's security infrastructure.
Detects potential reconnaissance or port scanning activities against firewall or UTM management interfaces from external IP addresses. The rule identifies sources that trigger a high volume of blocked or denied attempts across multiple management ports (e.g., SSH, HTTP/S, GUI ports) within a one-hour window.
This Splunk query analyzes web access logs to identify and categorize non-browser user agents, detecting various types of security tools, scripting languages, automation frameworks, and suspicious patterns. This activity can signify malicious actors attempting to interact with web endpoints in non-standard ways.
Page 1 of 10