
Arnold Chan
@slazTrusted contributorCompletionist
2 followers2,099 downloads4,333 copies51 likes25,881 views
7,555 detections
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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.
Detects a sequence of events on a single device involving a remote MSI installation followed by PowerShell-based process elevation and administrative checks using fltmc.exe. This pattern is indicative of an attacker attempting to deploy malicious packages remotely and escalate privileges within the environment.
Detects a suspected device-code phishing attack where a user visits a known malicious lure domain and shortly thereafter completes a successful Microsoft 365 device-code authentication. This rule correlates network events with sign-in logs within a 10-minute window to identify session hijacking attempts that bypass traditional MFA.
Detects a suspected device-code phishing attack where a user visits a known malicious lure domain and shortly thereafter completes a successful Microsoft 365 device-code authentication. This rule correlates network events with sign-in logs within a 10-minute window to identify session hijacking attempts that bypass traditional MFA.
This rule monitors for execution of files with specific SHA256 hashes known to be malicious, and network connections to a known malicious domain associated with Vultr storage. It aggregates file creation, process execution, and network connection events to detect potential threat activity.
Detects the execution of the 'gitshot' binary, which is known to automatically create public repositories and release tags to host screenshots or screen recordings. This behavior can be abused by insiders or attackers to exfiltrate sensitive data outside of corporate control.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects a suspicious pattern where an AI coding agent or user creates a public GitHub repository with specific naming conventions (e.g., 'sweeper-demo', 'gitshot-images') and subsequently pushes content containing sensitive terms like 'screenshot' within a short timeframe. This behavior is indicative of potential data exfiltration of internal development screenshots to a public repository.
This rule performs a retrospective sweep for indicators of compromise (IOCs) associated with the DragonForce TURN/MQTT campaign, as detailed in Lab52 threat research. It monitors for file and process activity matching known malicious hashes, as well as network connections to specific domains and URLs associated with the campaign's command-and-control infrastructure.
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