Ibrahim Saud
@tektrixIndiaCompletionist
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11,679 detections
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Detects unauthorized access to or generation of Citrix NetScaler core dump files, trace outputs, or memory diagnostic artifacts. These artifacts are high-value targets for attackers, such as those exploiting CVE-2026-88772, who attempt to extract session tokens, credentials, and sensitive data residing in memory via these diagnostic mechanisms.
Detects command-line activity attempting to disable, unbind, or remove NetScaler AppFW (Web Application Firewall) profiles, signatures, or security policies. This activity is indicative of defense evasion following the exploitation of CVE-2026-88771 or CVE-2026-88772 to suppress security alerting on follow-on malicious activity.
Detects command-line activity on a NetScaler appliance indicative of defense evasion by truncating, deleting, or disabling audit logs (ns.log) and syslog forwarding services. This activity often follows the exploitation of public-facing application vulnerabilities where an attacker seeks to hide their presence.
Detects repeated crashes or restarts of the Citrix NetScaler packet engine (nsppe) correlated with a concurrent spike in inbound DTLS traffic. This pattern is indicative of potential memory-overflow exploitation attempts (consistent with CVE-2026-88772) targeting the VPN virtual server functionality, leading to a Denial of Service (DoS) condition.
Detects the physical connection of unauthorized IP-KVM devices (e.g., PiKVM) to corporate endpoints, which could be used for remote control via HDMI capture and USB HID emulation. This detection monitors Plug and Play (PnP) events for specific device descriptors and hardware identifiers commonly associated with remote access hardware.
Detects attempts by potentially malicious processes, such as web-browsing tools, scripts, or agents, to access the cloud instance metadata service (169.254.169.254) or associated metadata paths. This behavior is indicative of Server-Side Request Forgery (SSRF) exploitation aimed at stealing cloud instance credentials.
Detects network connection attempts by known AI agent or development-related runtime processes (python, node, etc.) to external endpoints that are not contained within a defined allowlist of LLM and infrastructure providers. This is intended to identify potential data exfiltration or unauthorized command and control communication originating from LLM-powered applications.
Detects suspicious process-injection related API calls (such as CreateRemoteThread, VirtualAllocEx, and WriteProcessMemory) where the source or target process is a common AI agent runtime environment (e.g., python.exe, node.exe, java.exe, dotnet.exe). This detects potential malicious code execution or reflective loading initiated by or targeting these runtime processes.
Detects anomalous authentication patterns associated with AI agent or service account credentials. The rule monitors for logins originating from multiple disparate network locations, ASNs, or countries within a 15-minute window, and detects unexpected MFA challenges directed at accounts that typically function as automated, headless identities.
This rule detects the execution of node.exe or a specific binary named 'ProfileQuickHost.exe' spawned by wscript.exe. This activity is indicative of a VBScript-based loader (often referred to as 'ChainScript') executing a staged Node.js RAT or secondary payload from user-writable application folders (AppData).
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