Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
40,057 detections
Filters
Last updated
All Time
Detection languages
15,357
13,598
2,797
1,803
1,721
Contributors
7,678
5,999
5,315
4,504
4,191
Categories
18,110
9,757
3,852
3,759
3,713
Platforms
40,057
7,331
6,542
3,907
3,664
Products / Services
10,439
9,678
6,723
1,887
1,879
MITRE Techniques
13,737
13,117
8,066
5,949
4,414
CVEs
49
45
30
30
29
IDS Classtypes
214
56
43
23
19
IDS Protocols
183
172
20
16
8
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
IOC hunt across DNS, network, and file-hash telemetry for the Ledger Google Ads phishing campaign. Vercel redirect domains are matched by exact hostname (DNS query name / parsed URL host) rather than substring, eliminating false positives from unrelated strings that merely contain a look-alike domain fragment. GCS bucket and Google Sites path IOCs remain substring-matched since the bucket IDs and page slugs are already highly specific.
Detects a suspicious execution sequence associated with the SectopRAT loader. The rule monitors for ReportDump.exe being launched from a ProgramData directory by common scheduling or service host processes, followed immediately by the loading of a malicious sdkcra.dll library.
Detects anomalous, bulk file access activity targeting browser credential databases, cryptocurrency wallet data, and application-specific configuration stores, characteristic of the SectopRAT 'DeployBrowserKey' command.
Detects the specific command-line sequence used by SectopRAT for self-deletion. The malware uses 'choice' to create a delay followed by a 'del' command to remove its own executable, a technique for deleting files after the process has terminated.
Detects DB/DLL files masquerading as legitimate components that embed an XOR-encrypted PE (SectopRAT payload) or the sdkcra.dll loader export used in the FrameworkBase.dll tampered-IAT chain
Detects instances where common AI agent orchestration runtimes (e.g., LangChain, AutoGPT, CrewAI) spawn command-line or scripting interpreters as child processes. This behavior is highly suspicious and often indicative of malicious command execution triggered by prompt injection attacks, where an adversary manipulates the agent into executing arbitrary system commands.
This rule detects the installation of common AI agent and orchestration frameworks (e.g., LangChain, AutoGen, CrewAI) using command-line package managers (pip, npm, conda) that point to non-standard or unverified package indexes. This behavior is a common indicator of a potential software supply-chain compromise, where an adversary attempts to inject malicious code by forcing the installation of packages from an attacker-controlled source.
This rule detects automated browser-based processes (such as chromedriver, msedgedriver, geckodriver, playwright, or node/python scripts leveraging browser automation frameworks) initiating network connections to domains or URLs identified in active threat intelligence as malicious. This behavior is indicative of an AI agent or automated script being steered toward attacker-controlled infrastructure, potentially for drive-by compromise or exploitation.
Detects DNS query activity from processes commonly used as AI agent runtimes (e.g., python.exe, node.exe) toward domains characterized by DGA-like patterns, such as long alphanumeric strings or high-consonant density, which may indicate command-and-control communication.
Detects a burst of file delete or overwrite operations initiated by a configured AI agent service identity. This behavior, if deviating from established baselines, may indicate a compromised agent performing malicious destructive activities such as mass data deletion or ransomware-style file destruction.
Detects anomalous, high-volume HTTP requests to AI agent orchestration endpoints (e.g., tool invocation, plugins, or webhooks) followed by suspicious process execution or outbound network connections from the same host. This behavior is indicative of RCE exploitation against an AI agent framework, such as insecure deserialization or SSRF within a plugin connector.
Detects the installation of known AI-powered coding assistant extensions (e.g., Copilot, Tabnine, Cursor) on a device, followed by significant source-code repository cloning or archival activity by Git within two hours. This pattern is potentially indicative of intellectual property theft or sensitive source code exfiltration facilitated by a newly introduced AI tool.
Detects non-browser processes (e.g., non-chrome.exe/msedge.exe) modifying critical browser configuration files such as 'Secure Preferences' followed by near-simultaneous writes to extension-related directories like 'Extension State' or 'Extensions'. This pattern is indicative of a malicious attempt to bypass browser security integrity checks to silently install or load unauthorized extensions.
Detects instances where a Claude process accesses a 'SKILL.md' file, followed closely by a suspicious command execution on the same device. The rule specifically targets command-line activity that involves encoding, download-and-execute patterns, staging in sensitive directories, or communication with suspicious domains/IPs, which is indicative of a supply-chain or poisoned agent-skill file attack.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
Detects the execution of PowerShell with a bypass execution policy that performs a download or web request to save content to a file in the user's temp directory, followed by the immediate execution of that file. This pattern is characteristic of multi-stage malware droppers or fileless attack techniques attempting to stage and execute malicious scripts from temporary locations.
This rule monitors for network communication with a specific known malicious IP address and URL path, as well as the execution or presence of associated malicious file hashes. Additionally, it flags emails involving specific indicators identified as potentially associated with malicious activity.
Detects service-creation commands (sc create / New-Service / reg add under a Services key) whose COMMAND LINE itself references a known NeedyMantis binary name or sideload staging folder. Requiring the malicious reference to appear in the command being executed -- rather than merely in the calling process's own folder location -- removes false matches from unrelated legitimate software that happens to be installed under a similarly-named folder.
Detects Impacket-style hands-on-keyboard staging: a NeedyMantis bundle file dropped by cmd.exe/wmiprvse.exe/services.exe carrying the distinctive remote-execution fingerprint (ADMIN$ share reference, %COMSPEC% invocation, or 2>&1 output redirection used by wmiexec/smbexec/atexec), followed within 15 minutes by execution referencing the same bundle folder with the same fingerprint. Requiring the ADMIN$/%COMSPEC%/redirection fingerprint on both the copy and the execution -- rather than just matching on common process names like cmd.exe or svchost.exe -- removes the bulk of ordinary software installation and update activity that also uses cmd.exe to stage files.
Detects evidence of potential adversarial interference with Windows Defender updates and MRT.exe (Malicious Software Removal Tool). The rule correlates high volumes of temporary file creation in user directories with unauthorized access to MRT.exe by third-party processes and repeated Windows Defender update failures, indicating a potential attempt to disrupt endpoint security operations.
Page 99 of 1908