Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,294 detections
Filters
Last updated
All Time
Detection languages
1,284
250
199
142
138
Contributors
660
544
375
96
95
Categories
20,456
11,839
5,876
5,155
4,865
2,294
Platforms
1,505
929
381
70
51
Products / Services
743
407
225
164
140
MITRE Techniques
856
683
604
437
302
CVEs
12
10
9
9
8
IDS Classtypes
24
4
3
1
1
IDS Protocols
20
6
6
1
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
This rule detects multiple suspicious file write operations on a Linux host, specifically targeting directories often used for persistence such as /etc/apt/apt.conf.d, /etc/profile.d, and /etc/cron.d. The rule flags hosts where at least two of these specific persistence techniques are utilized within a 24-hour window, which is indicative of an automated, redundant persistence strategy often employed by cryptocurrency miners like XMRig.
This rule detects suspicious activity associated with Redis server processes attempting to write to SSH 'authorized_keys' files or executing commands (such as BGREWRITEAOF or directory reconfiguration) commonly used by attackers to inject malicious SSH public keys into a Redis installation for persistent remote access.
Detects the creation or modification of a file within the /etc/cron.d/ directory, followed shortly by a Bash process invocation using /dev/tcp redirection. This pattern is commonly used by attackers to achieve persistence via cron and establish reverse shells, bypassing potential limitations of default system shells that do not support /dev/tcp syntax.
Detects the Redis server process writing or modifying files within cron configuration directories. This is a common persistence technique used by attackers to gain recurring execution after exploiting vulnerable or misconfigured Redis instances.
This rule detects suspicious activity involving macOS LaunchAgents and files within the 'Application Support/System' directory, often associated with persistence or malicious background execution. The detection looks for the creation or modification of specific plist files (e.g., com.apple.finder.agent.plist) or git-related files in Application Support, correlated with process execution of commands like 'sysnotif-repair', 'launchctl' manipulating agents, or git operations involving custom hooks paths.
Detects the creation, modification, or renaming of common JSP web shell filenames (x.jsp, u.jsp, u2.jsp) within known web application directories (e.g., webapps, Peoplesoft, WebLogic). This pattern is indicative of an adversary attempting to establish a web shell for persistent access or command execution on a vulnerable web server.
This rule detects a specific persistence technique used by AvisLoader malware. It monitors for the creation of a .lnk.backup file alongside a corresponding .lnk shortcut modification in common shell locations (Desktop, Taskbar, etc.), coupled with the execution of wscript.exe or cscript.exe referencing the 'VLCAssistant' VBScript within a short time window. This sequence indicates an attempt to persist malicious activity by backing up existing shortcuts and replacing them with a launcher for the AvisLoader payload.
Detects execution of shell commands (cmd, powershell) by processes associated with AvisLoader (e.g., 78324.exe, VLCAssistant.exe, auto.exe), followed by the creation or modification of files in suspicious user-writable directories (e.g., appdata, temp) within a 10-minute window, suggesting potential C2 activity and secondary payload staging.
Detects suspicious file create or write operations within the domain SYSVOL Policies directory. This pattern is commonly associated with attackers attempting to deploy malicious payloads, such as ransom notes or configuration changes, via Group Policy Objects (GPO). The rule monitors Windows Event ID 4663 to identify unauthorized modification attempts by non-system accounts.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
Detects UNC6240 PSEMHUB.war web shell/tunnel/trojanized installer artifacts by distinctive content markers (x.jsp, u.jsp, tunnel.jsp/jspx, Ple64.exe)
Detects UNC6240 PSEMHUB.war web shell/tunnel/trojanized installer artifacts by distinctive content markers (x.jsp, u.jsp, tunnel.jsp/jspx, Ple64.exe)
Detects sensitive cPanel/WHM administrative commands or system file modifications occurring within one hour of a suspected authentication bypass event, indicative of potential post-exploitation activity related to CVE-2026-41940.
This rule detects unauthorized tampering with AI container images within a container registry. It identifies when existing image tags are overwritten by actors outside of authorized CI/CD pipelines, or when production MLOps infrastructure pulls unsigned or invalid container images, potentially indicating a supply chain attack targeting AI model artifacts.
Page 13 of 110