performing-active-directory-forest-trust-attack

name	performing-active-directory-forest-trust-attack
description	Enumerate and audit Active Directory forest trust relationships using impacket for SID filtering analysis, trust key extraction, cross-forest SID history abuse detection, and inter-realm Kerberos ticket assessment. Use when working with performing active directory forest trust attack.
domain	cybersecurity
subdomain	red-team
tags	["active-directory","forest-trust","impacket","SID-filtering","kerberos","red-team","trust-enumeration"]
version	1.0
author	oyi77
license	Apache-2.0
nist_csf	["ID.RA-01","GV.OV-02","DE.AE-07"]

Performing Active Directory Forest Trust Attack

Overview

Active Directory forest trusts enable authentication across organizational boundaries but introduce attack surface if misconfigured. This skill uses impacket to enumerate trust relationships, analyze SID filtering configuration, detect SID history abuse vectors, perform cross-forest SID lookups via LSA/LSAT RPC calls, and assess inter-realm Kerberos ticket configurations for trust ticket forgery risks.

When to Use

Trigger phrases:

• "performing active directory forest trust attack"

• "Enumerate and audit Active Directory forest trust relationships using impacket f"

• When conducting security assessments that involve performing active directory forest trust attack

• When following incident response procedures for related security events

• When performing scheduled security testing or auditing activities

• When validating security controls through hands-on testing

Prerequisites

• Python 3.9+ with impacket, ldap3
• Domain credentials with read access to AD trust objects
• Network access to Domain Controllers (ports 389, 445, 88)
• Authorized penetration testing engagement or lab environment

Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.

Steps

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v  IOC_PATTERNS.items()}