Files
T
mukul975 cb8d79e068 Map all 754 skills to MITRE ATT&CK v19.1
- Add validated mitre_attack frontmatter to all 754 skills (286 distinct
  techniques), verified against MITRE ATT&CK v19.1 via the official
  mitreattack-python library: 0 revoked, deprecated, or invalid IDs
- Curate precise per-skill technique IDs for forensics, malware-analysis,
  threat-intel, and red-team skills (e.g. DCSync -> T1003.006,
  Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003)
- Reconcile v19.1 tactic restructuring: Defense Evasion split into
  Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.*
  family and T1070.001/.002 remapped to active equivalents (T1685.*)
- Normalize word-split tags across 35 skills (remove filename-derived
  stopword tags, add semantic cybersecurity tags)
- Add api-reference.md for 3 skills that were missing it
- Update README ATT&CK section with accurate v19.1 tactic distribution
2026-06-01 12:13:29 +02:00

13 KiB

name, description, domain, subdomain, tags, version, author, license, d3fend_techniques, nist_csf, mitre_attack
name description domain subdomain tags version author license d3fend_techniques nist_csf mitre_attack
building-attack-pattern-library-from-cti-reports Extract and catalog attack patterns from cyber threat intelligence reports into a structured STIX-based library mapped to MITRE ATT&CK for detection engineering and threat-informed defense. cybersecurity threat-intelligence
attack-pattern
cti-reports
mitre-attack
stix
detection-engineering
threat-intelligence
nlp
extraction
1.0 mahipal Apache-2.0
File Metadata Consistency Validation
Application Protocol Command Analysis
Identifier Analysis
Content Format Conversion
Message Analysis
ID.RA-01
ID.RA-05
DE.CM-01
DE.AE-02
T1566.001
T1059.001
T1003.001
T1558.003
T1550.002

Building Attack Pattern Library from CTI Reports

Overview

Cyber threat intelligence (CTI) reports from vendors like Mandiant, CrowdStrike, Talos, and Microsoft contain detailed descriptions of adversary behaviors that can be extracted, normalized, and cataloged into a structured attack pattern library. This skill covers parsing CTI reports to extract adversary techniques, mapping behaviors to MITRE ATT&CK technique IDs, creating STIX 2.1 Attack Pattern objects, building a searchable library indexed by tactic, technique, and threat actor, and generating detection rule templates from documented patterns.

When to Use

  • When deploying or configuring building attack pattern library from cti reports capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Python 3.9+ with stix2, mitreattack-python, spacy, requests libraries
  • Collection of CTI reports (PDF, HTML, or text format)
  • MITRE ATT&CK STIX data (local or via TAXII)
  • Understanding of ATT&CK technique structure and naming conventions
  • Familiarity with detection engineering concepts (Sigma, YARA)

Key Concepts

Attack Pattern Extraction

CTI reports describe adversary behaviors in natural language. Extraction involves identifying action verbs and technical terms that map to ATT&CK techniques, recognizing tool names and malware families, identifying infrastructure indicators, and mapping sequences of behaviors to attack chains (kill chain phases).

STIX 2.1 Attack Pattern Objects

STIX defines Attack Pattern as a Structured Domain Object (SDO) that describes ways threat actors attempt to compromise targets. Each pattern links to ATT&CK via external references, includes kill chain phases (tactics), and can be related to Intrusion Sets, Malware, and Tool objects.

Detection Rule Generation

Extracted attack patterns inform detection engineering by providing: specific procedure examples for Sigma rule creation, behavioral sequences for correlation rules, IOC patterns for YARA and Snort rules, and data source requirements for telemetry gaps.

Workflow

Step 1: Parse CTI Reports and Extract Behaviors

import re
import json
from collections import defaultdict

class CTIReportParser:
    """Parse CTI reports to extract adversary behaviors."""

    BEHAVIOR_INDICATORS = [
        "used", "executed", "deployed", "leveraged", "exploited",
        "established", "created", "modified", "downloaded", "uploaded",
        "exfiltrated", "injected", "enumerated", "spawned", "dropped",
        "persisted", "escalated", "moved laterally", "collected",
        "encrypted", "compressed", "encoded", "obfuscated",
    ]

    TOOL_PATTERNS = [
        r'\b(Cobalt Strike|Mimikatz|PsExec|BloodHound|Rubeus|Impacket)\b',
        r'\b(PowerShell|cmd\.exe|WMI|WMIC|certutil|bitsadmin)\b',
        r'\b(Metasploit|Empire|Covenant|Sliver|Brute Ratel)\b',
        r'\b(Lazagne|SharpHound|ADFind|Sharphound|Invoke-Obfuscation)\b',
    ]

    TECHNIQUE_KEYWORDS = {
        "spearphishing": "T1566",
        "phishing attachment": "T1566.001",
        "phishing link": "T1566.002",
        "powershell": "T1059.001",
        "command line": "T1059.003",
        "scheduled task": "T1053.005",
        "registry run key": "T1547.001",
        "process injection": "T1055",
        "dll side-loading": "T1574.002",
        "credential dumping": "T1003",
        "lsass": "T1003.001",
        "kerberoasting": "T1558.003",
        "pass the hash": "T1550.002",
        "remote desktop": "T1021.001",
        "smb": "T1021.002",
        "winrm": "T1021.006",
        "data staging": "T1074",
        "exfiltration over c2": "T1041",
        "dns tunneling": "T1071.004",
        "web shell": "T1505.003",
    }

    def parse_report(self, text, report_metadata=None):
        """Parse a CTI report and extract behaviors."""
        sentences = re.split(r'[.!?]\s+', text)
        behaviors = []

        for sentence in sentences:
            sentence_lower = sentence.lower()
            # Check for behavior indicators
            for indicator in self.BEHAVIOR_INDICATORS:
                if indicator in sentence_lower:
                    behavior = {
                        "sentence": sentence.strip(),
                        "action": indicator,
                        "tools": self._extract_tools(sentence),
                        "technique_hints": self._match_techniques(sentence_lower),
                    }
                    if behavior["technique_hints"]:
                        behaviors.append(behavior)
                    break

        print(f"[+] Extracted {len(behaviors)} behavioral indicators from report")
        return behaviors

    def _extract_tools(self, text):
        """Extract tool/malware names from text."""
        tools = set()
        for pattern in self.TOOL_PATTERNS:
            matches = re.findall(pattern, text, re.IGNORECASE)
            tools.update(matches)
        return list(tools)

    def _match_techniques(self, text):
        """Match text to ATT&CK technique hints."""
        matches = []
        for keyword, tech_id in self.TECHNIQUE_KEYWORDS.items():
            if keyword in text:
                matches.append({"keyword": keyword, "technique_id": tech_id})
        return matches

parser = CTIReportParser()
sample_report = """
The threat actor used spearphishing attachments with macro-enabled documents to
gain initial access. Once inside, they executed PowerShell scripts to download
additional tooling. The actor leveraged Mimikatz to dump credentials from LSASS
memory. They then used pass the hash techniques for lateral movement via SMB
to multiple systems. Data was staged in a compressed archive and exfiltrated
over the existing C2 channel. The actor established persistence through
scheduled tasks and registry run keys.
"""
behaviors = parser.parse_report(sample_report)

Step 2: Map Behaviors to ATT&CK Techniques

from attackcti import attack_client

class ATTACKMapper:
    def __init__(self):
        self.lift = attack_client()
        self.techniques = {}
        self._load_techniques()

    def _load_techniques(self):
        """Load all ATT&CK techniques for mapping."""
        all_techs = self.lift.get_enterprise_techniques()
        for tech in all_techs:
            tech_id = ""
            for ref in tech.get("external_references", []):
                if ref.get("source_name") == "mitre-attack":
                    tech_id = ref.get("external_id", "")
                    break
            if tech_id:
                self.techniques[tech_id] = {
                    "name": tech.get("name", ""),
                    "description": tech.get("description", "")[:500],
                    "tactics": [p.get("phase_name") for p in tech.get("kill_chain_phases", [])],
                    "platforms": tech.get("x_mitre_platforms", []),
                    "data_sources": tech.get("x_mitre_data_sources", []),
                }
        print(f"[+] Loaded {len(self.techniques)} ATT&CK techniques")

    def map_behaviors(self, behaviors):
        """Map extracted behaviors to ATT&CK techniques."""
        mapped = []
        for behavior in behaviors:
            for hint in behavior.get("technique_hints", []):
                tech_id = hint["technique_id"]
                if tech_id in self.techniques:
                    tech_info = self.techniques[tech_id]
                    mapped.append({
                        "technique_id": tech_id,
                        "technique_name": tech_info["name"],
                        "tactics": tech_info["tactics"],
                        "source_sentence": behavior["sentence"],
                        "tools_observed": behavior["tools"],
                        "keyword_matched": hint["keyword"],
                        "data_sources": tech_info["data_sources"],
                    })
        print(f"[+] Mapped {len(mapped)} behaviors to ATT&CK techniques")
        return mapped

mapper = ATTACKMapper()
mapped_behaviors = mapper.map_behaviors(behaviors)

Step 3: Create STIX 2.1 Attack Pattern Library

from stix2 import AttackPattern, Relationship, Bundle, TLP_GREEN
from datetime import datetime

class AttackPatternLibrary:
    def __init__(self):
        self.patterns = []
        self.relationships = []

    def add_pattern_from_mapping(self, mapping, report_source="CTI Report"):
        """Create STIX Attack Pattern from mapped behavior."""
        pattern = AttackPattern(
            name=mapping["technique_name"],
            description=f"Observed: {mapping['source_sentence']}\n\n"
                        f"Tools: {', '.join(mapping['tools_observed']) or 'None identified'}\n"
                        f"Source: {report_source}",
            external_references=[{
                "source_name": "mitre-attack",
                "external_id": mapping["technique_id"],
                "url": f"https://attack.mitre.org/techniques/{mapping['technique_id'].replace('.', '/')}/",
            }],
            kill_chain_phases=[{
                "kill_chain_name": "mitre-attack",
                "phase_name": tactic,
            } for tactic in mapping["tactics"]],
            object_marking_refs=[TLP_GREEN],
        )
        self.patterns.append(pattern)
        return pattern

    def build_library(self, mapped_behaviors, report_source="CTI Report"):
        """Build complete attack pattern library from mappings."""
        seen_techniques = set()
        for mapping in mapped_behaviors:
            tech_id = mapping["technique_id"]
            if tech_id not in seen_techniques:
                self.add_pattern_from_mapping(mapping, report_source)
                seen_techniques.add(tech_id)

        bundle = Bundle(objects=self.patterns + self.relationships)
        print(f"[+] Library: {len(self.patterns)} attack patterns")
        return bundle

    def export_library(self, output_file="attack_pattern_library.json"):
        bundle = Bundle(objects=self.patterns + self.relationships)
        with open(output_file, "w") as f:
            f.write(bundle.serialize(pretty=True))
        print(f"[+] Library exported to {output_file}")

    def generate_detection_templates(self, mapped_behaviors):
        """Generate Sigma rule templates from attack patterns."""
        templates = []
        for mapping in mapped_behaviors:
            template = {
                "title": f"Detection: {mapping['technique_name']} ({mapping['technique_id']})",
                "status": "experimental",
                "description": f"Detects {mapping['technique_name']} based on CTI report observation",
                "references": [
                    f"https://attack.mitre.org/techniques/{mapping['technique_id'].replace('.', '/')}/",
                ],
                "tags": [
                    f"attack.{mapping['tactics'][0]}" if mapping['tactics'] else "attack.unknown",
                    f"attack.{mapping['technique_id'].lower()}",
                ],
                "data_sources": mapping.get("data_sources", []),
                "observed_tools": mapping.get("tools_observed", []),
                "source_context": mapping["source_sentence"],
            }
            templates.append(template)

        with open("detection_templates.json", "w") as f:
            json.dump(templates, f, indent=2)
        print(f"[+] Generated {len(templates)} detection templates")
        return templates

library = AttackPatternLibrary()
bundle = library.build_library(mapped_behaviors, "Sample CTI Report")
library.export_library()
templates = library.generate_detection_templates(mapped_behaviors)

Validation Criteria

  • CTI report parsed and behavioral indicators extracted
  • Behaviors mapped to ATT&CK techniques with confidence
  • STIX 2.1 Attack Pattern objects created with proper references
  • Library searchable by tactic, technique, and threat actor
  • Detection templates generated from documented patterns
  • Library exportable as STIX bundle for sharing

References