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
20,443
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 anomalous 'Bind' operations in Microsoft 365 Exchange Online audit logs where the user-agent string includes 'Firefox/131.0' and 'Client=REST' while using specific Microsoft Outlook ClientAppId and APIId parameters. This pattern has been observed in automated, cross-tenant mailbox exfiltration campaigns targeting sensitive payroll and financial documentation.
Detects the creation of an email inbox rule that includes both a concealment/deletion action and an external forwarding destination, occurring within 4 hours of a high-risk or compromised device-code authentication event. This pattern is indicative of account takeover where an attacker establishes persistence and exfiltration while hiding their activity.
Detects the creation of an email inbox rule that includes both a concealment/deletion action and an external forwarding destination, occurring within 4 hours of a high-risk or compromised device-code authentication event. This pattern is indicative of account takeover where an attacker establishes persistence and exfiltration while hiding their activity.
Detects the creation of an email inbox rule that includes both a concealment/deletion action and an external forwarding destination, occurring within 4 hours of a high-risk or compromised device-code authentication event. This pattern is indicative of account takeover where an attacker establishes persistence and exfiltration while hiding their activity.
Detects high-volume file and data access events within Microsoft 365 services (SharePoint, OneDrive, Exchange) originating from Python-based user agents (e.g., 'python-requests', 'python-httpx'). This pattern is indicative of automated scraping, data exfiltration, or bulk activity performed by unauthorized scripts.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects high-volume file access or download activity by a single user in SharePoint or OneDrive over a 15-minute window. This behavior is indicative of bulk cloud data exfiltration often associated with extortion campaigns.
Detects outbound network traffic from internal hosts to public Telegram Bot API or Slack webhooks, indicative of potential data exfiltration by the npm indexed-btree malware or similar malicious actors utilizing these services for command and control or exfiltration.
This rule detects unauthorized mailbox access by identifying specific ClientAppId and API ID pairs known to be associated with an Office 365 email exfiltration toolkit. This activity is indicative of an attacker attempting to programmatically access or exfiltrate sensitive email data from the organization's environment.
This rule detects network traffic originating from internal hosts to Slack's domain that contains hardcoded Slack bot tokens and specific Slack channel IDs associated with a malicious npm supply chain campaign (indexed-btree). This indicates successful exfiltration of sensitive configuration credentials or data to an attacker-controlled Slack environment.
Detects network traffic associated with the malicious npm package 'indexed-btree', which uses the Telegram Bot API to exfiltrate data. The rules monitor for connections to api.telegram.org via HTTPS and identify specific hardcoded bot tokens and chat IDs associated with the malicious campaign.
Detects bulk uploads or downloads of AI/ML artifacts, such as model weights, datasets, and configuration files, to suspected personal or external cloud storage providers. This rule is designed to identify potential unauthorized exfiltration of proprietary AI/ML assets.
Detects Large Language Model (LLM) responses that contain sensitive information such as PII, internal proprietary markers, or credentials. This rule monitors model output for patterns matching social security numbers, credit card numbers, private keys, API keys, and internal company confidentiality labels, which could indicate data leakage or unintended disclosure.
Detects anomalous high-volume API requests from a single user/key to AI model inference endpoints. The rule tracks query diversity and total volume within an hour to identify behavior consistent with model extraction or cloning (AML.T0024.002) via systematic input/output pair collection.
Detects a sequence of suspicious activities associated with EvilTokens-style session hijacking. This includes the identification of non-interactive sign-in events involving the redemption of a refresh token without secondary MFA, followed by the creation or modification of Exchange Online mailbox rules to facilitate unauthorized email forwarding or exfiltration.
Detects anomalous activity where an AI coding assistant process reads sensitive local credential files (such as .env, .aws/credentials, or SSH keys) followed by an outbound network connection to a destination not associated with known package registries or AI provider APIs. This pattern is indicative of potential prompt-injection attacks targeting autonomous AI coding tools to exfiltrate developer secrets.
Detects outbound HTTP requests to the Telegram Bot API associated with the malicious 'indexed-btree' npm package. The rule specifically monitors for hardcoded Telegram bot tokens and chat IDs used for data exfiltration.
Detects outbound HTTP requests to the Telegram Bot API associated with the malicious 'indexed-btree' npm package. The rule specifically monitors for hardcoded Telegram bot tokens and chat IDs used for data exfiltration.
Detects outbound network traffic attempting to exfiltrate data to Slack or Telegram APIs using hardcoded bot tokens or channel identifiers associated with the 'indexed-btree' malware campaign.
Page 22 of 128