Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,588 detections
Filters
Last updated
All Time
Detection languages
1,194
459
310
204
161
Contributors
487
455
323
171
123
Categories
1,884
937
415
400
360
Platforms
1,349
560
343
329
257
Products / Services
601
314
306
286
271
MITRE Techniques
18,115
15,636
12,582
8,393
6,221
2,588
CVEs
9
5
5
5
2
IDS Classtypes
142
96
49
11
6
IDS Protocols
177
49
44
17
4
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 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.
Detects network traffic indicating the use of Rclone to exfiltrate data to MEGA cloud storage, a technique associated with Akira ransomware campaigns.
This rule detects the suspicious copying of a Chromium-based browser 'Web Data' file (which stores sensitive information like saved passwords, credit cards, or address data) to a temporary file, followed by an outbound network connection to a specific exfiltration endpoint pattern within a 30-minute window.
Detects high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects unauthorized cross-account copying of AWS EC2 or RDS snapshots, a key indicator of data exfiltration or staging as part of a snapshot-theft attack chain. The rule correlates copy events where the source snapshot owner is different from the destination account ID.
This rule detects the use of browser-based cloud shells (AWS CloudShell, Azure Cloud Shell) as an entry point for post-exploitation activities, specifically tracking when these sessions are followed by object storage operations (S3 PutObject/GetObject or equivalent Azure Blob operations) within the same session context. This pattern is indicative of attackers using ephemeral cloud shells to stage stolen data or download offensive tooling, thereby bypassing host-based EDR monitoring.
This rule detects the use of browser-based cloud shells (AWS CloudShell, Azure Cloud Shell) as an entry point for post-exploitation activities, specifically tracking when these sessions are followed by object storage operations (S3 PutObject/GetObject or equivalent Azure Blob operations) within the same session context. This pattern is indicative of attackers using ephemeral cloud shells to stage stolen data or download offensive tooling, thereby bypassing host-based EDR monitoring.
Detects modifications to RDS or Aurora snapshot attributes that grant public access ('all') or share the snapshot with an external AWS account ID. This activity indicates a potential data exfiltration attempt, as sharing a snapshot allows an external party to restore the database in their own environment, bypassing existing application-layer access controls.
Detects the creation of an AWS CloudShell environment followed by a high volume of file transfer activity (PutFile, GetFile, or PutObject) by the same user within a short time window. This pattern is indicative of potential initial access or abuse of CloudShell for tool staging or unauthorized data exfiltration.
Detects modifications to AWS EBS or RDS snapshot attributes to grant access to unauthorized or external AWS accounts, or the copying of snapshots to unauthorized accounts, which are common techniques for data exfiltration from cloud environments.
This rule detects modifications to AWS EC2 Snapshot or AMI (Image) attributes that result in the resource becoming publicly accessible ('all') or shared with an unapproved AWS account ID. Such activities are often precursors to data exfiltration or unauthorized access to sensitive disk images.
This rule detects potentially compromised accounts by correlating suspicious authentication activity (such as risky sign-ins, impossible travel, or malicious OAuth/Mail-rule configurations) with a subsequent spike in SharePoint or OneDrive file access, downloads, or external link sharing within a one-hour window. This behavior is indicative of an adversary performing cloud-based data exfiltration after gaining unauthorized access to an account.
Detects high-volume file download activity in Office 365/SharePoint/OneDrive audit logs. The rule correlates download spikes with users who have recently triggered security alerts related to session hijacking, token theft, or risky sign-ins, which are indicators of a potential cloud account takeover scenario.
Detects an anomalous volume of file access or synchronization activity on cloud document platforms (Microsoft SharePoint, OneDrive, or Google Drive) that occurs following a high-severity risky sign-in event. The rule specifically flags potential exfiltration patterns such as large volumes of data transfer or numerous file accesses, especially if associated with unmanaged devices or connections to known personal/external file-sharing services.
Detects the creation of anonymous or guest-access sharing links for SharePoint items that are classified as sensitive (having a sensitivity label applied). This activity could indicate potential data exfiltration or unauthorized sharing of protected corporate information.
Detects modifications to AWS EC2 snapshot or AMI attributes that grant cross-account permissions, including making them publicly accessible. This activity may indicate an attempt to exfiltrate volume data, such as credentials, configuration, or database contents, to an external AWS account.
Detects execution of the CHOSEN BRICK implant (process names smdqservice.exe or winappx.exe) initiating a network connection to Telegram infrastructure (C2) followed by a network connection to a cloud object-storage provider (vultrobjects.com, storjshare.io, or backblazeb2.com) for data exfiltration within a 30-minute window.
Detects rapid mass-cloning or downloading of private GitHub repositories shortly after an OAuth token authorization, originating from IP addresses or countries not previously associated with the user account. This behavior is indicative of unauthorized bulk data extraction using compromised credentials, consistent with threat actor activity (e.g., TeamPCP/UNC6780).
Page 11 of 124