Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
3,750 detections
Filters
Last updated
All Time
Detection languages
2,544
328
307
253
149
Contributors
953
720
641
297
173
Categories
1,245
994
880
773
476
Platforms
2,850
1,449
1,229
356
73
Products / Services
10,683
9,759
6,695
4,421
3,750
MITRE Techniques
1,096
989
950
912
820
CVEs
17
6
2
1
1
IDS Classtypes
9
4
3
2
2
IDS Protocols
21
1
This rule performs a retrospective sweep for indicators of compromise (IOCs) associated with the 'CSuite' phishing and RMM (Remote Monitoring and Management) campaign. It monitors network, DNS, proxy, email, URL click, and file creation telemetry over the past 24 hours to identify interactions with known-malicious IP addresses, domains, URLs, and file hashes related to the campaign.
This rule detects potential data exfiltration by correlating access to files labeled as sensitive (confidential, restricted, etc.) with a subsequent upload to a personal cloud storage provider or transmission via email to a personal domain within a two-hour window.
Detects activity associated with the MALFEX npm supply-chain campaign (also known as Overlord/movinlike). This rule performs a sweep for known malicious file hashes, suspicious process command lines, outbound network connections to malicious domains or IPs, and email communications from identified adversary-controlled accounts.
Detects potential help-desk impersonation or social engineering activity involving account credential or MFA method resets, followed shortly by a sign-in from an unknown device or geography. The rule excludes activity tied to established ticketing systems or standard automated password expiration processes.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
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.
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.
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.
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.
Detects anomalous, high-volume file deletion, modification, or resource deletion operations performed by an identified AI agent service account within a short timeframe. This behavior is indicative of a compromised AI agent being leveraged for mass data destruction, ransomware activity, or disruptive configuration changes.
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 activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
Detects the registration of a new authentication method (e.g., FIDO2 key, authenticator app) shortly after a user account experiences a risky sign-in event. This pattern is indicative of an adversary attempting to establish persistent access and bypass MFA requirements, often following a successful AiTM (Adversary-in-the-Middle) phishing attack.
Detects phishing messages that deliberately mix writing systems/scripts/homoglyphs in the Subject line as ONE corroborating signal within a broader, multi-signal phishing pattern. Hardened against false positives: brand/product tokens (e.g. Microsoft, PayPal) are stripped before the Latin-script check so a lone brand mention in non-Latin correspondence doesn't count as mixed-script; a weighted score (script-mixing=2, homoglyph=3, high-confidence phishing vocabulary=2, threshold=6) means no two of the three signal categories can reach the threshold alone — all three must co-occur before the rule fires.
Detects phishing messages that mix writing systems/scripts/homoglyphs in the Subject line as one corroborating signal within a broader, multi-signal phishing pattern.
This rule detects potential adversarial reconnaissance activities targeting AI agents via multiple communication channels (e.g., email, collaboration tools). It identifies patterns where a sender transmits messages containing common 'jailbreak' or 'instruction-override' phrases (e.g., 'ignore previous instructions', 'bypass approval') across at least three distinct channels within a 24-hour window, indicating a concerted effort to manipulate or probe agent logic.
Detects a multi-stage exfiltration sequence consisting of: (1) bulk file archival/compression using common utilities, (2) suspicious OAuth grant or service principal authorization, and (3) abnormal network egress volume to common ports. This pattern suggests an adversary is preparing data, establishing or leveraging an identity/application for cloud access, and subsequently exfiltrating data.
This rule detects potential phishing attempts where the sender's display name is formatted as an email address and the sender's domain uses a capital 'I' character to mimic a well-known service provider (typosquatting/homoglyph attack), such as 'gmaiI.com'. It identifies discrepancies between the actual sender domain and the normalized domain name after character replacement.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
This rule monitors for indicators of compromise (IOCs) associated with the TrustSink rogue MFA provider, specifically tracking the domain 'trident-sip-filter.ngrok-free.dev' and its associated OIDC discovery path. It aggregates signals from sign-in logs, audit logs, DNS queries, and network proxy traffic to identify attempts to interact with this malicious infrastructure.
Page 12 of 179