Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,686 detections
Filters
Last updated
All Time
Detection languages
1,342
389
264
219
197
Contributors
620
506
358
209
102
Categories
20,442
11,831
5,875
5,151
4,864
2,686
Platforms
1,168
638
452
382
359
Products / Services
593
445
403
264
229
MITRE Techniques
1,884
787
525
521
510
CVEs
11
5
5
5
3
IDS Classtypes
189
133
34
10
7
IDS Protocols
243
58
33
22
12
Detects HTTP POST requests directed to the URI path '/api/credentials' over the non-standard TCP port 8133, which is indicative of AMOS (Atomic macOS) Stealer exfiltrating stolen credentials to a C2 server.
Detects the use of legitimate data-transfer utilities (rclone, MEGA client, restic, WinSCP) configured to exfiltrate data to cloud storage providers. This behavior is identified as a precursor to double-extortion ransomware attacks, where attackers steal sensitive data before encrypting it.
Detects unauthorized data staging activities using archival utilities followed by data exfiltration to known public cloud storage providers. The rule specifically excludes hosts experiencing mass file renaming activity, focusing on extortion-only scenarios where data is stolen without encryption.
Detects potential browser-based infostealer activity where a non-standard process, launched from temporary or user-download directories, accesses sensitive browser data files (cookies, login data) followed by a suspicious outbound network connection to a previously unseen domain, matching common patterns for LummaStealer or Vidar malware.
Detects network activity associated with the RatHat Android malware, specifically identifying C2 data exfiltration API calls over FRP (FRP/Go Agent) tunnels and WebSocket handshake traffic for command-and-control communication.
Detects HTTP traffic from the Psychedelic Stealer malware as it exfiltrates stolen browser passwords and session tokens to a specific command-and-control endpoint, and identifies the staging of Chromium Web Data files ('wd_tmp.db') within HTTP POST requests.
Detects a multi-stage, automated attack chain performed by AI-based development agents (e.g., Claude, Copilot, Cursor). The rule correlates process discovery, credential access, file collection (staging), and exfiltration over web services within a tight 15-minute window, identifying potential autonomous exploitation and data exfiltration. Covered T1046, T1552.001, T1078, T1005, T1567
Detects network traffic indicative of VelvetCake malware exfiltrating data. The rule specifically monitors for HTTP POST requests to 'logout.php' containing 'OKey' and 'Who' parameters, using a user agent string that includes 'WebClient', which is often associated with PowerShell-based network requests.
Detects instances where a non-browser process initiates network connections to multiple AI service providers and Discord within a 15-minute correlation window, potentially indicating automated data exfiltration or unauthorized interaction with AI platforms using tools other than standard web browsers.
Detects two-stage network activity associated with Adversary-in-the-Middle (AiTM) phishing kits. The first part detects the submission of stolen credentials or session data to a local WebDAV panel (xwps.php), and the second part detects the subsequent exfiltration of that captured data to the Telegram Bot API.
This rule monitors for high-frequency download or access events of files associated with AI development, such as model weights (.pt, .ckpt, .safetensors, .h5, .onnx, .pkl, .pb), checkpoints, and research datasets from cloud storage. It triggers when an account accesses or downloads 20 or more unique AI-related files within a 60-minute window, which is indicative of unauthorized data exfiltration of intellectual property.
This rule monitors for suspicious command-line activity involving the Fortis payment processor's webhook log files. It detects when attackers use tools like 'findstr', 'cmd', or 'dir' to navigate directories containing webhook data and specifically searches for payment card fields such as CVV, primary account numbers, and expiration dates, which is a common indicator of post-compromise data exfiltration.
This rule detects HTTP POST requests from mobile user agents (Android, Dalvik, okhttp) that contain keywords indicative of contactless payment card data exfiltration, specifically looking for fields such as 'track2', 'pan', 'atc', and 'cryptogram'. This behavior is consistent with malicious mobile applications attempting to transmit skimmed NFC credit card data to an external server.
Detects outbound HTTP PUT requests characteristic of data exfiltration associated with Qilin ransomware. The rule monitors for the use of command-line tools like s5cmd or rclone for uploading data, often used during the double extortion phase where stolen data is uploaded to leak sites.
Detects HTTP PUT/POST requests targeting external domains with URI patterns and filename structures characteristic of TheGentlemen ransomware group's data exfiltration activities. The rule monitors for large HTTP request payloads (>50KB) and suspicious TLS subject fields (e.g., presence of CN without an O field) associated with potential C2 communication.
Detects high-risk destructive database operations (DROP, TRUNCATE, or UPDATE) on sensitive tables executed within six hours of a large outbound data transfer from the same host, a pattern indicative of anti-forensic database wiping following data exfiltration.
This rule detects potentially malicious C2 communication by monitoring high-frequency HTTP POST requests from the 'rnpkeys.exe' process. It aggregates network events over 30-second windows and flags activity exceeding a threshold of 5 POST requests directed at known suspicious domains or specific high-port network destinations, which is characteristic of beaconing or data exfiltration activity.
Detects a multi-stage network communication pattern characteristic of agent sandbox evasion and subsequent data exfiltration. The rule first identifies an unusual volume of connections to URL-shorteners using encoded fragments in the URI, and subsequently flags calls to common screenshot or rendering services containing 'url=' parameters, suggesting possible pixel-based data exfiltration over a command and control channel.
This rule detects internal users submitting potentially sensitive data to public generative AI applications (e.g., ChatGPT, Claude, Gemini) where Microsoft Purview DLP or a comparable inspection service has triggered a policy match. It correlates cloud application outbound signals with content inspection logs to identify high-risk exfiltration events while excluding sanctioned enterprise-licensed AI instances.
Detects outbound HTTP GET requests containing an 'auth=' parameter with a long string of alphanumeric characters, characteristic of an OAuth token exfiltration attempt by a malicious Twitch extension (JeetBot). The rule flags requests to external destinations that are not official Twitch, Twitch Video Network, or JTV domains.
Detects a behavioral chain where a process establishes persistence using a 'WindowsUpdate' Registry Run key or a scheduled task, followed within five minutes by an outbound network connection from the same process. The rule specifically excludes cases where a ZIP file was written to disk, identifying potential in-memory staging for exfiltration.
Page 10 of 128