Ibrahim Saud
@tektrixIndiaCompletionist
2 followers18,458 downloads7,104 copies47 likes38,500 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
Detects instances where a user account successfully registers or joins a device to Entra ID (Azure AD) immediately after performing a sign-in operation that was flagged with a medium or high-risk level. This pattern may indicate an adversary is attempting to enroll a malicious device to bypass conditional access policies or establish persistence in the environment using compromised credentials.
Detects adversary-in-the-middle (AiTM) phishing activity utilizing reverse-proxy kits (such as Evilginx2, EvilProxy, or Modlishka) to bypass MFA. The rule identifies suspicious login requests by correlating common identity provider login paths with missing security headers (CSP/HSTS) and anomalous server or hostname characteristics typical of proxied phishing infrastructure.
Detects the reuse of a single authenticated session or refresh token from multiple distinct IP addresses or ASN origins within a short timeframe following a successful MFA event. This pattern is indicative of session hijacking, where an adversary uses an Adversary-in-the-Middle (AiTM) toolkit (e.g., Evilginx) to capture a valid session cookie from a victim and replay it from their own infrastructure to bypass authentication.
Detects successful multi-factor authentication (MFA) events associated with risk signals categorized as 'unfamiliarFeatures' in Azure AD sign-in logs. This combination is often indicative of an adversary-in-the-middle (AiTM) attack, where the attacker has captured authentication tokens or is forcing an MFA prompt and receiving immediate approval from a new or suspicious device and network location.
Detects outbound HTTP GET requests where the user agent is set to 'WebClient' and the URI ends in '.ps1'. This behavior is characteristic of PowerShell download cradles, which are often used by adversaries to fetch and execute remote malicious scripts directly into memory.
Detects the creation or modification of script files (bat, ps1, vbs, cmd) within the Windows Startup folder initiated by processes commonly associated with AI agents or developer frameworks (e.g., dotnet, python, w3wp). This activity indicates an AI agent environment being exploited to establish persistence, potentially facilitating delayed remote code execution upon user logon.
This rule detects potential remote code execution (RCE) attempts targeting AI agent applications, specifically those utilizing the Semantic Kernel framework. It identifies suspicious command-line patterns indicative of a Python type hierarchy traversal attack (CVE-2026-26030), which is used to bypass security blocklists within an eval() sink to execute arbitrary commands like 'os.system()'. The rule monitors for the spawning of common shell or utility processes by Python or .NET processes associated with AI agent activity.
Detects anomalous file access patterns by Semantic Kernel agent processes attempting to read sensitive host files such as SSH keys, configuration files, and credential stores. This activity is indicative of malicious use of agent file-transfer capabilities, potentially exploiting path traversal vulnerabilities or prompt injection to exfiltrate sensitive data from the host environment into the agent sandbox.
Detects high-volume AI/LLM inference or GPU-compute provisioning activity from a single identity within a short duration. This behavior is indicative of LLMJacking, where compromised cloud credentials are used to spin up unauthorized, resource-intensive AI workloads for profit.
Detects an accelerated sequence of attack phases—specifically recon, privilege escalation, lateral movement, and persistence—occurring on a single device within a short timeframe (15 minutes). This behavioral pattern indicates potential automated or script-orchestrated intrusion activity.
Page 239 of 1168