Ankit Mehta
@SecvynIndiaTrusted contributorCompletionist
8 followers9,573 downloads10,241 copies160 likes55,494 views
8,655 detections
Filters
Last updated
All Time
Detection languages
5,827
1,081
677
439
436
Categories
2,646
2,040
1,304
944
814
Platforms
5,999
954
874
706
593
Products / Services
2,800
1,372
1,362
725
707
MITRE Techniques
2,087
2,043
1,442
1,092
1,085
CVEs
17
16
15
11
11
IDS Classtypes
250
132
95
68
64
IDS Protocols
405
140
49
36
14
Detects Python processes (python.exe, pythonw.exe) making more than 3 connections to public IP addresses. This activity could indicate data exfiltration, command and control communication, or other suspicious network behavior originating from a Python script.
Detects suspicious process activity originating from WSMProvHost, suggesting potential lateral movement or remote command execution
Detects scheduled tasks created with embedded PowerShell XOR decoding logic, ReadAllBytes, and Invoke-Expression techniques that may be used to establish persistence and execute obfuscated payloads. The rule specifically looks for 'schtasks.exe' creating a task with '/create', containing 'OneDrive', 'Startup', 'Task' in the command line, and also includes '-bxor', 'ReadAllBytes', 'iex', and '[Text.Encoding]::UTF8.GetBytes' which are indicative of obfuscated PowerShell execution via XOR decoding.
Detects the creation of disk image files (ISO, IMG, VHD, VHDX, WIM) within temporary folders under a user's AppData directory. This activity can be indicative of malware staging or unpacking, often associated with initial access techniques where malicious payloads are delivered as disk images.
Identifies creation or modification of hidden files named .sys within temporary Linux directories commonly abused by C0XMO for payload storage and persistence. Such activity is highly unusual and may indicate malware deployment or persistence establishment.
This rule detects potential GitHub token theft or abuse activity by identifying GitHub tokens that are used from an unusually high number of distinct IP addresses or for an unusually high number of uses within a one-hour window. Specifically, it looks for tokens with more than 5 uses and more than 2 distinct IP addresses in an hour. This behavior could indicate that a compromised token is being used by an attacker from multiple locations or in an automated fashion.
This rule detects suspicious NTLM network or remote interactive logon activity. It specifically looks for multiple distinct accounts logging in from the same device and remote IP address within a one-hour window, using NTLM authentication via NtLmSsp or Seclogon processes. This pattern can indicate credential stuffing, NTLM relay attacks, or other forms of credential misuse.
This rule detects the execution of known credential dumping tools, Mimikatz and ProcDump, when specific command-line arguments associated with credential extraction from LSASS are used. It specifically looks for `mimikatz.exe` or `procdump.exe` combined with arguments like `sekurlsa`, `logonpasswords`, or `-ma` which are commonly used to dump credentials from memory.
This rule detects devices exhibiting high volume outbound network traffic, specifically more than 10MB of data transferred across more than 100 sessions to a single remote IP address within a one-minute window. This behavior can be indicative of data exfiltration, unauthorized data transfer, or other suspicious network activity.
Detects potential WordPress malware activity that abuses Steam Community profile comments as a command-and-control (C2) channel. The malware retrieves encoded payloads hidden in Steam profile comments using invisible Unicode characters, decodes malicious URLs, and downloads additional JavaScript payloads. This rule identifies outbound connections from WordPress servers to Steam Community URLs or known malicious infrastructure associated with this campaign.
Page 839 of 866