Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
3,647 detections
Filters
Last updated
All Time
Detection languages
1,768
374
351
273
255
Contributors
908
676
593
359
164
Categories
1,502
1,169
782
528
521
Platforms
39,941
7,266
6,537
3,866
3,647
Products / Services
807
512
432
340
300
MITRE Techniques
1,180
582
528
506
438
CVEs
17
16
9
8
7
IDS Classtypes
41
15
10
6
5
IDS Protocols
47
24
3
2
1
Detects potential misuse of AI model APIs by correlating process creation, network activity, and non-standard AI service ports.
Covers Ollama, OpenAI, Azure OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Copilot, OpenRouter, Together, and Perplexity.
Covers Ollama, OpenAI, Azure OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Copilot, OpenRouter, Together, and Perplexity.
Detects attempts to list or dump macOS Keychain data using the built-in 'security' utility. This activity can be indicative of credential theft attempts by an adversary.
Detects the malicious telemetry.js file used in the s1ngularity supply chain attack. This script harvests sensitive developer assets and exfiltrates them to attacker-controlled GitHub repositories.
Detects the execution of osascript with a command line that includes curl to download and execute a remote script, a technique used by the Odyssey Stealer malware.
Detects various techniques, procedures, and indicators associated with the RustyPages macOS malware dropper, including persistence, defense evasion, payload download, and known IOCs. This rule specifically looks for the use of `curl` to download a hidden file, `launchctl` to establish persistence, `chmod` to make the payload executable, `xattr` to clear extended attributes, `pgrep` to discover security tools, shell commands to silence notifications, C2 domain/IP connections, and known malware file hashes.
Detects the execution of a shell script downloaded via curl or wget on macOS, a technique associated with ClickFix campaigns delivering malware like Atomic macOS Stealer (AMOS).
Detects the execution of 'dscl . authonly' by a script interpreter, a technique used by Odyssey Stealer to validate user passwords obtained from a malicious dialog prompt.
Detects the creation of the 'socks' binary used by the Odyssey Stealer to establish a SOCKS5 proxy for network tunneling on compromised macOS systems. This rule identifies the binary based on specific SHA256 hashes and its filename 'socks'.
Detects the execution of an application from a mounted disk image (DMG) with a name known to be used by Odyssey Infostealer. This activity is indicative of initial access, where the user has been tricked into running a malicious application masquerading as a legitimate software installer or updater.
Detects the creation of a randomly named LaunchDaemon .plist file in /Library/LaunchDaemons/, a technique used by Odyssey Stealer for persistence.
Detects the creation of hidden configuration files used by the Odyssey Infostealer on macOS. These files are known to store sensitive data like passwords, C2 server details, and bot identifiers.
Detects a file being created in a temporary macOS directory, made executable, and then executed by a shell. This behavior is consistent with the Odyssey Infostealer, which downloads and runs scripts from temporary locations.
Detects the execution of an AppleScript, characteristic of the Odyssey Stealer, that displays a dialog box prompting the user for their password.
Detects potential Command and Control (C2) communication patterns based on ASIM-normalized network session data in Microsoft Sentinel. This detection covers three primary patterns:
1) Periodic beaconing with low jitter
2) Long-lived HTTP(S) long-polling sessions
3) Network traffic with very consistent payload sizes
Such patterns can indicate covert communication with compromised systems or malware infections.
1) Periodic beaconing with low jitter
2) Long-lived HTTP(S) long-polling sessions
3) Network traffic with very consistent payload sizes
Such patterns can indicate covert communication with compromised systems or malware infections.
High confidence that the same actor is responsible for earlier attacks attributed to BlueNoroff and the RustDoor/ThiefBucket and RustBucket campaigns. SentinelLABS observed the use of a novel persistence mechanism abusing the Zsh configuration file zshenv.
Detects files based on common ransomware file extensions or ransom note filenames. This rule is based on a community-sourced list and is intended for broad detection.
This rule detects attempts by scripting language interpreters (Node.js, Python, PowerShell) to access sensitive browser credential files such as 'Login Data', 'Web Data', and 'Cookies' from Chrome and Brave browser user data directories. It also includes specific file paths that might be associated with known browser extensions or malware that target these files. This activity is indicative of credential dumping or information stealing.
This rule detects when an email with a detected threat (e.g., malware, phishing) has an attachment that is subsequently observed on an endpoint device. This indicates that a malicious attachment from an email was downloaded and executed or saved on a device.
This rule detects suspicious activity where scripting interpreters (node.exe, python.exe, pwsh.exe, powershell.exe) are observed accessing a large number of potentially sensitive files (e.g., .env, secret, wallet, keypair, credential, recovery files, or common document/data file types like .pdf, .docx, .csv, .json, .txt) and subsequently exfiltrating a significant amount of data over the network. It correlates file access events with network outbound traffic from the same process within a 10-minute window, flagging instances where more than 20 distinct sensitive files are accessed and over 500KB of data is sent out.
This rule identifies devices that have software installed which has reached its End-Of-Support (EOS) status. This is crucial for identifying potential security vulnerabilities due to unpatched software and for maintaining compliance with organizational security policies. The rule summarizes the count of such software instances per device, along with the software name and its End-Of-Support date.
Detects the use of the 'mdimport' command to index sensitive user directories. This is a key step in the Sploitlight TCC bypass technique (CVE-2025-31199), where a malicious Spotlight importer is triggered to run within the 'mdworker' process and exfiltrate data from TCC-protected locations by writing it to the system log.
Page 165 of 174