building-attack-pattern-library-from-cti-reports▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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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.
| name | building-attack-pattern-library-from-cti-reports |
| description | 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. |
| 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 |
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,requestslibraries - 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
How to use building-attack-pattern-library-from-cti-reports on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add building-attack-pattern-library-from-cti-reports
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches building-attack-pattern-library-from-cti-reports from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate building-attack-pattern-library-from-cti-reports. Access the skill through slash commands (e.g., /building-attack-pattern-library-from-cti-reports) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★47 reviews- ★★★★★Hana Khan· Dec 28, 2024
Keeps context tight: building-attack-pattern-library-from-cti-reports is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Maya Sethi· Dec 20, 2024
building-attack-pattern-library-from-cti-reports has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Meera Verma· Dec 12, 2024
Registry listing for building-attack-pattern-library-from-cti-reports matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Dhruvi Jain· Dec 4, 2024
building-attack-pattern-library-from-cti-reports fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Oshnikdeep· Nov 23, 2024
Registry listing for building-attack-pattern-library-from-cti-reports matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kwame Abebe· Nov 19, 2024
I recommend building-attack-pattern-library-from-cti-reports for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Charlotte Huang· Nov 3, 2024
building-attack-pattern-library-from-cti-reports fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Mateo Martin· Oct 22, 2024
We added building-attack-pattern-library-from-cti-reports from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ganesh Mohane· Oct 14, 2024
building-attack-pattern-library-from-cti-reports reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Maya Martin· Oct 10, 2024
Useful defaults in building-attack-pattern-library-from-cti-reports — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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