Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects persistence attempts using common Windows auto-start registry keys or scheduled tasks where the initiating process is unsigned or has an invalid signature. The rule focuses on binaries executing from suspicious, user-writable directories (e.g., Temp, AppData, Downloads) and specifically targets persistence mechanisms involving the 'SecurityHealthService.exe' filename.
Detects 2CLoader samples containing the embedded config magic bytes alongside rolling-XOR, AES-GCM, and sha256-seed-derived key material used in its payload decryption chain
Detects 2CLoader samples containing the embedded config magic bytes alongside rolling-XOR, AES-GCM, and sha256-seed-derived key material used in its payload decryption chain
Detects 2CLoader samples containing the embedded config magic bytes alongside rolling-XOR, AES-GCM, and sha256-seed-derived key material used in its payload decryption chain
This rule performs an indicator of compromise (IOC) sweep for activities associated with the TOPHIT / VHX Harvester / @prime0 NPM typosquatting campaign. It detects known malicious C2 network connections (IPs and URLs), file artifacts (hashes) on endpoints, and suspicious email activity involving specific operator email addresses.
This rule performs an indicator of compromise (IOC) sweep for activities associated with the TOPHIT / VHX Harvester / @prime0 NPM typosquatting campaign. It detects known malicious C2 network connections (IPs and URLs), file artifacts (hashes) on endpoints, and suspicious email activity involving specific operator email addresses.
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.
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.
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.
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.
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 SectopRAT (Arechclient2) .NET RAT binaries deployed via tampered libcef.dll / JetBrains helper DLL sideloading that harvest browser credentials, cookies, credit card data, and files. Tightened to require combined sideload+family+target indicators plus .NET CLR import evidence, avoiding standalone generic strings.
This rule performs a retrospective hunt for indicators of compromise (IOCs) associated with the ClosedQuorum malware. It identifies suspicious activity by matching against known file hashes, specific filenames, and network traffic directed towards services (such as DeepSeek, OpenRouter, Mistral, and Discord) which the malware uses for C2 or data exfiltration. The detection logic aggregates results from file system, process, and network telemetry.
Detects specific malicious Mach-O binary payloads associated with the Atomic macOS Stealer (AMOS) discovered in the Macfinger ClickFix campaign. The rule uses static file hashes to identify these specific samples.
Detects specific malicious Mach-O binary payloads identified as Atomic Stealer (AMOS) that are associated with Macfinger ClickFix first-stage infection campaigns. The rule uses static file signatures (Mach-O headers), specific file size ranges, and known SHA-256 hashes of the payloads.
This rule monitors network, file, and process telemetry for matches against a predefined list of malicious IP addresses, domain names, and file hashes. It flags suspicious network connections to known C2 infrastructure and the presence or execution of known malicious files based on SHA256 and SHA1 indicators.
This rule correlates multiple telemetry sources (File Events, Certificate Info, Network Events, and DNS Events) to detect known malicious indicators, including specific file hashes, IP addresses, domains, and URLs associated with malicious activity.
This rule detects potential malicious activity by matching file hashes against a known list of malicious indicators and monitoring for suspicious network connections. The network monitoring includes connections to hardcoded malicious IP addresses, specific C2 URLs, and DNS queries for known fallback domains used in malicious infrastructure when the initiating process is not a recognized web browser or wallet application.
This rule monitors endpoint telemetry for known indicators of compromise associated with the Casbaneiro/Ousaban banking trojan. It identifies activity across network connections (IPs and domain patterns), DNS queries for specific C2 domains, and the presence or execution of known malicious file hashes (e.g., PDF lures, HTA, AutoIt scripts, and payload binaries).
This rule monitors for file and process creation events associated with known MD5 and SHA256 hashes linked to the Vidar infostealer malware.
This rule performs a retrospective hunt for indicators of compromise (IOCs) associated with the ClosedQuorum malware. It identifies suspicious activity by matching against known file hashes, specific filenames, and network traffic directed towards services (such as DeepSeek, OpenRouter, Mistral, and Discord) which the malware uses for C2 or data exfiltration. The detection logic aggregates results from file system, process, and network telemetry.
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