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Detecting Remote Script Proxy Execution via PubPrn.vbs

Execution Prevention: Prevent the execution of unauthorized or malicious code on systems by implementing application control, script blocking, and other execution prevention mechanisms. This ensures that only trusted and authorized code is executed, reducing the risk of malware and unauthorized actions. This mitigation can be implemented through the following measures:

Application Control:

• Use Case: Use tools like AppLocker or Windows Defender Application Control (WDAC) to create whitelists of authorized applications and block unauthorized ones. On Linux, use tools like SELinux or AppArmor to define mandatory access control policies for application execution.
• Implementation: Allow only digitally signed or pre-approved applications to execute on servers and endpoints. (e.g., New-AppLockerPolicy -PolicyType Enforced -FilePath "C:\Policies\AppLocker.xml")

Script Blocking:

• Use Case: Use script control mechanisms to block unauthorized execution of scripts, such as PowerShell or JavaScript. Web Browsers: Use browser extensions or settings to block JavaScript execution from untrusted sources.
• Implementation: Configure PowerShell to enforce Constrained Language Mode for non-administrator users. (e.g., Set-ExecutionPolicy AllSigned)

Executable Blocking:

• Use Case: Prevent execution of binaries from suspicious locations, such as %TEMP% or %APPDATA% directories.
• Implementation: Block execution of .exe, .bat, or .ps1 files from user-writable directories.

Dynamic Analysis Prevention:

• Use Case: Use behavior-based execution prevention tools to identify and block malicious activity in real time.
• Implemenation: Employ EDR solutions that analyze runtime behavior and block suspicious code execution.

Behavior Prevention on Endpoint: Behavior Prevention on Endpoint refers to the use of technologies and strategies to detect and block potentially malicious activities by analyzing the behavior of processes, files, API calls, and other endpoint events. Rather than relying solely on known signatures, this approach leverages heuristics, machine learning, and real-time monitoring to identify anomalous patterns indicative of an attack. This mitigation can be implemented through the following measures:

Suspicious Process Behavior:

• Implementation: Use Endpoint Detection and Response (EDR) tools to monitor and block processes exhibiting unusual behavior, such as privilege escalation attempts.
• Use Case: An attacker uses a known vulnerability to spawn a privileged process from a user-level application. The endpoint tool detects the abnormal parent-child process relationship and blocks the action.

Unauthorized File Access:

• Implementation: Leverage Data Loss Prevention (DLP) or endpoint tools to block processes attempting to access sensitive files without proper authorization.
• Use Case: A process tries to read or modify a sensitive file located in a restricted directory, such as /etc/shadow on Linux or the SAM registry hive on Windows. The endpoint tool identifies this anomalous behavior and prevents it.

Abnormal API Calls:

• Implementation: Implement runtime analysis tools to monitor API calls and block those associated with malicious activities.
• Use Case: A process dynamically injects itself into another process to hijack its execution. The endpoint detects the abnormal use of APIs like OpenProcess and WriteProcessMemory and terminates the offending process.

Exploit Prevention:

• Implementation: Use behavioral exploit prevention tools to detect and block exploits attempting to gain unauthorized access.
• Use Case: A buffer overflow exploit is launched against a vulnerable application. The endpoint detects the anomalous memory write operation and halts the process.