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Building Attack Pattern Library From Cti Reports

mukul975/anthropic-cybersecurity-skills

  • 188 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

building-attack-pattern-library-from-cti-reports is a Claude Code security skill that extracts adversary techniques from threat intelligence reports into a STIX-based library mapped to MITRE ATT&CK for detection engineer

About

This skill extracts adversary techniques from cyber threat intelligence reports and catalogs them into a structured STIX 2.1 attack pattern library mapped to MITRE ATT&CK. It parses reports from vendors like Mandiant and CrowdStrike, matches behaviors to ATT&CK technique IDs, and generates detection rule templates such as Sigma and YARA. A security engineer uses it for detection engineering and threat-informed defense. It requires Python with the stix2, mitreattack-python, and spaCy libraries.

  • Extracts adversary behaviors from CTI reports via NLP
  • Maps techniques to MITRE ATT&CK technique IDs
  • Builds STIX 2.1 Attack Pattern objects
  • Generates Sigma and YARA detection rule templates

Building Attack Pattern Library From Cti Reports by the numbers

  • 188 all-time installs (skills.sh)
  • +8 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #798 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

building-attack-pattern-library-from-cti-reports capabilities & compatibility

Free skill; requires Python libraries and MITRE ATT&CK STIX data.

Capabilities
cti parsing · attack pattern extraction · mitre attack mapping · detection rule generation
Use cases
security audit · research · data analysis
Pricing
Free
From the docs

What building-attack-pattern-library-from-cti-reports says it does

Extract and catalog attack patterns from cyber threat intelligence reports
SKILL.md
STIX defines Attack Pattern as a Structured Domain Object (SDO) that describes ways threat actors attempt to compromise targets.
SKILL.md
Python 3.9+ with `stix2`, `mitreattack-python`, `spacy`, `requests` libraries
SKILL.md
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill building-attack-pattern-library-from-cti-reports

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Installs188
repo stars★ 27.3k
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills ↗

How do I turn narrative CTI reports into structured, ATT&CK-mapped attack patterns and detection rules?

Extracting adversary techniques from CTI reports into a STIX library mapped to MITRE ATT&CK for detection engineering.

Who is it for?

Detection engineers and threat-intel analysts turning vendor CTI reports into a searchable ATT&CK-mapped pattern library.

Skip if: Teams without CTI reports to process or without detection-engineering context (Sigma, YARA, ATT&CK).

When should I use this skill?

When establishing threat-informed defense: parsing CTI reports to catalog adversary techniques and generate detection rule templates.

What you get

A searchable STIX 2.1 attack pattern library indexed by tactic, technique, and threat actor, with detection rule templates.

  • STIX 2.1 Attack Pattern objects mapped to ATT&CK
  • Searchable library indexed by tactic, technique, threat actor
  • Sigma/YARA detection rule templates

By the numbers

  • 5 MITRE ATT&CK technique references (T1566.001, T1059.001, T1003.001, T1558.003, T1550.002)
  • 5 D3FEND techniques referenced

Files

SKILL.mdMarkdownGitHub ↗

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

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FAQ

What does this skill produce?

STIX 2.1 Attack Pattern objects mapped to MITRE ATT&CK, a library indexed by tactic, technique and threat actor, and detection rule templates.

Which sources can it parse?

CTI reports from vendors like Mandiant, CrowdStrike, Talos, and Microsoft in PDF, HTML, or text format.

What are the dependencies?

Python 3.9+ with stix2, mitreattack-python, spacy, and requests, plus local or TAXII MITRE ATT&CK STIX data.

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