--- name: building-attack-pattern-library-from-cti-reports-dafd1817515d description: Parse cyber threat intelligence reports (Mandiant, CrowdStrike, Talos, Microsoft) with stix2, mitreattack-python, and spaCy to extract adversary behaviors, map them to MITRE ATT&CK technique IDs, and build a searchable STIX 2.1 attack-pattern library with detection templates. Use when cataloging attack patterns from CTI reports for threat-informed detection engineering, or generating Sigma/YARA templates from documented behaviors. domain: cybersecurity subdomain: threat-intelligence tags: - attack-pattern - cti-reports - mitre-attack - stix - detection-engineering - threat-intelligence - nlp - extraction version: '1.0' author: mahipal license: Apache-2.0 d3fend_techniques: - File Metadata Consistency Validation - Application Protocol Command Analysis - Identifier Analysis - Content Format Conversion - Message Analysis nist_csf: - ID.RA-01 - ID.RA-05 - DE.CM-01 - DE.AE-02 mitre_attack: - 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 ```python 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 ```python 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 ```python 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 - [MITRE ATT&CK](https://attack.mitre.org/) - [STIX 2.1 Attack Pattern SDO](https://docs.oasis-open.org/cti/stix/v2.1/os/stix-v2.1-os.html#_axjijf603msy) - [CISA: Best Practices for ATT&CK Mapping](https://www.cisa.gov/sites/default/files/2023-01/Best%20Practices%20for%20MITRE%20ATTCK%20Mapping.pdf) - [attackcti Python Library](https://github.com/OTRF/ATTACK-Python-Client) - [Sigma Rules Project](https://github.com/SigmaHQ/sigma) - [MITRE ATT&CK STIX Data](https://github.com/mitre/cti) --- Source attribution: hironow Original project: https://github.com/hironow/cyber/blob/20efb3a6a2a9e7ebbde38ed32325979866110540/.agents/skills/building-attack-pattern-library-from-cti-reports/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: hironow Original project: https://github.com/hironow/cyber/blob/20efb3a6a2a9e7ebbde38ed32325979866110540/.agents/skills/building-attack-pattern-library-from-cti-reports/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering, Product Management Roles: Data Analyst, Data Scientist, ML / AI Engineer, Product Manager, Security Engineer Specialties: API, Backend Tools: Mitreattack Python, Requests, Spacy, Stix2 Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: d580d6c39673eea145197ca2dc423fc6a3be454274c97b592f8a20d3d58de802