Agent skill

Building Attack Pattern Library From Cti Reports

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

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…

Apache-2.0Auto-check passedSecurity

Install Building Attack Pattern Library From Cti Reports

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-attack-pattern-library-from-cti-reports -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-attack-pattern-library-from-cti-reports --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/building-attack-pattern-library-from-cti-reports .claude/skills/building-attack-pattern-library-from-cti-reports && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
building-attack-pattern-library-from-cti-reports
GitHub stars
34k
Token cost
~3.4k tokens
SKILL.md length
391 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

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…

  • Works in 3 steps: Parse CTI Reports and Extract Behaviors → Map Behaviors to ATT&CK Techniques → Create STIX 2.1 Attack Pattern Library
  • Cataloging attack patterns from CTI reports for threat-informed detection engineering
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; reaches attack.mitre.org

What it does

Building Attack Pattern Library From Cti Reports is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Security operations and OSINT. It works with Python. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Cataloging attack patterns from CTI reports for threat-informed detection engineering
  • Generating Sigma/YARA templates from documented behaviors

Example prompts

  • “/building-attack-pattern-library-from-cti-reports”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Parse CTI Reports and Extract Behaviors
  2. Map Behaviors to ATT&CK Techniques
  3. Create STIX 2.1 Attack Pattern Library

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • attack.mitre.org

    Also links to:

    • github.com
    • docs.oasis-open.org
    • cisa.gov

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Building Attack Pattern Library From Cti Reports loads about 3.4k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 391 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~121
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 391 words, ~3,443 tokens.

Download SKILL.mdSave it as .claude/skills/building-attack-pattern-library-from-cti-reports/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
building-attack-pattern-library-from-cti-reports
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).

Show full SKILL.md (179 more words)Show less
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

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/building-attack-pattern-library-from-cti-reports of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Works with

Categories

Questions about Building Attack Pattern Library From Cti Reports

What does Building Attack Pattern Library From Cti Reports do?

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…. Building Attack Pattern Library From Cti Reports is an agent skill from mukul975/Anthropic-Cybersecurity-Skills.1 attack-pattern library with detection templates.

When should I use Building Attack Pattern Library From Cti Reports?

Building Attack Pattern Library From Cti Reports fits situations like: cataloging attack patterns from CTI reports for threat-informed detection engineering; generating Sigma/YARA templates from documented behaviors.

How do I install Building Attack Pattern Library From Cti Reports in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-attack-pattern-library-from-cti-reports -a claude-code`. Or copy the skill folder (skills/building-attack-pattern-library-from-cti-reports in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/building-attack-pattern-library-from-cti-reports in your project. Claude Code loads it when a task matches its description.

How do I install Building Attack Pattern Library From Cti Reports in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-attack-pattern-library-from-cti-reports -a codex`. Or copy the skill folder (skills/building-attack-pattern-library-from-cti-reports in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/building-attack-pattern-library-from-cti-reports in your project. Codex loads it when a task matches its description.

Can I use Building Attack Pattern Library From Cti Reports in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-attack-pattern-library-from-cti-reports -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-attack-pattern-library-from-cti-reports, .gemini/skills/building-attack-pattern-library-from-cti-reports, .github/skills/building-attack-pattern-library-from-cti-reports and .opencode/skills/building-attack-pattern-library-from-cti-reports in your project.

What does Building Attack Pattern Library From Cti Reports need to run?

Going by SKILL.md and its folder, Building Attack Pattern Library From Cti Reports needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Building Attack Pattern Library From Cti Reports access the network?

SKILL.md names 4 domains. In commands or code: attack.mitre.org; the agent is likely to contact it when it follows the instructions. As links in the text: github.com, docs.oasis-open.org and cisa.gov. This is read from the text; nothing was executed.

Is Building Attack Pattern Library From Cti Reports safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Building Attack Pattern Library From Cti Reports use?

Building Attack Pattern Library From Cti Reports is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Building Attack Pattern Library From Cti Reports use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 358 tokens, read only when the agent opens those files.

What are the alternatives to Building Attack Pattern Library From Cti Reports?

Skills that share tags, products or a category with Building Attack Pattern Library From Cti Reports: Osint Investigation (johnson7788/MultiUserClaw, 327 stars), Enrich Ioc (dandye/ai-runbooks, 127 stars), Domain Intel (Tommy-yw/RunbookHermes, 546 stars) and Threat Intel Campaign (SCStelz/security-investigator, 250 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building Attack Pattern Library From Cti Reports?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,993 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.