
Ibrahim Saud
@tektrixIndiaCompletionist
2 followers18,458 downloads7,116 copies47 likes38,555 views
11,679 detections
Filters
Last updated
All Time
Detection languages
3,760
1,874
1,586
966
944
Categories
4,878
3,246
1,529
1,303
1,122
Platforms
7,678
1,824
1,066
999
986
Products / Services
2,963
1,768
1,278
953
798
MITRE Techniques
3,615
3,555
2,488
1,474
1,186
CVEs
36
27
26
25
23
IDS Classtypes
360
113
38
24
24
IDS Protocols
315
114
93
47
10
This rule detects potential credential theft by monitoring for file access (creation, modification, or renaming) to common web browser sensitive files (Login Data or Cookies) followed by an outbound network connection from the same process within a 10-minute window. This behavior often indicates an adversary attempting to exfiltrate browser-stored credentials or session cookies.
This rule detects the creation of specific shortcut files (.lnk) within the Windows Startup folder and monitors for the usage of WScript.Shell to interact with the Startup directory. This behavior is commonly associated with persistence mechanisms where an adversary attempts to automatically execute malicious code upon user login.
Detects suspicious Git activity or file modifications within the plugin directories of various AI coding assistants (such as Claude, Codex, Copilot, or Gemini). This may indicate an attempt to inject malicious code or persistence mechanisms into the local environment via untrusted plugins.
Detects instances where Windows Explorer (explorer.exe) spawns PowerShell with heavily obfuscated command lines, characterized by caret-obfuscation and execution policy bypass flags. This pattern is characteristic of ClickFix social engineering, where a user is tricked into pasting malicious commands into the Windows Run dialog.
Detects the creation of a Git branch where the branch name matches the pattern of a 40-character hexadecimal SHA-1 hash. This behavior is associated with the 'Plugin4Shell' technique, which exploits how some git implementations prioritize matching ref names over target commit objects, enabling an attacker to manipulate or swap code in automated systems or AI coding agents that rely on SHA-pinning.
Detects the execution of git-related operations (fetch, pull, clone) as child processes of common AI coding agent binaries. This pattern is indicative of potential unattended or malicious background plugin auto-updates, which could be leveraged for 'Plugin4Shell' style zero-click plugin distribution attacks.
Detects the execution of the Windows cipher.exe utility with the /w flag, which is used to overwrite deleted data on a disk to prevent forensic recovery. This is a common technique used by adversaries to perform data destruction or cover their tracks.
Detects potential indirect prompt injection attacks against LLM agents. The rule monitors for ingested or retrieved content containing known injection patterns (e.g., hidden comments, 'system:' role spoofing) that is followed within 5 minutes by a privileged tool invocation by the agent, such as data exfiltration or system command execution.
Detects anomalous AI orchestration or API gateway activity that suggests potential command and control (C2) communication. The rule monitors for unauthorized external endpoints, high-frequency low-payload beaconing patterns, and unauthorized cross-tenant agent-to-agent calls.
Detects anomalous AI agent behavior characterized by excessive recursive tool-call chain depth or task durations exceeding the 95th percentile baseline. This activity is indicative of adversarial prompting designed to increase operational compute costs or induce resource exhaustion.
Page 405 of 1168
