본문으로 건너뛰기
cccskills
무료GitHub에 공개

analyzing-threat-intelligence-feeds

Analyze threat intelligence feeds to extract indicators of compromise, observable clues of possible attacks, and their campaign context. Assess source quality, standardize formats, remove duplicates, and enrich indicators for distribution to security monitoring systems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Analyzes structured and unstructured threat intelligence feeds to extract actionable indicators, adversary tactics, and campaign context. Use when ingesting commercial or open-source CTI feeds, evaluating feed quality, normalizing data into STIX 2.1 format, or enriching existing IOCs with campaign attribution. Activates for requests involving ThreatConnect, Recorded Future, Mandiant Advantage, MISP, AlienVault OTX, or automated feed aggregation pipelines.

설치 방법 보기

이럴 때 유용합니다

  • Assessing the quality and relevance of threat intelligence feeds
  • Standardizing indicators into STIX 2.1
  • Removing duplicates and adding attack campaign context
  • Distributing enriched indicators to security monitoring systems

포함된 파일(4)

  • SKILL.md6.1 KB
  • LICENSE11.0 KB
  • references/api-reference.md2.3 KB
  • scripts/agent.py6.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Analyzing Threat Intelligence Feeds

When to Use

Use this skill when:

  • Ingesting new commercial or OSINT threat feeds and assessing their signal-to-noise ratio
  • Normalizing heterogeneous IOC formats (STIX 2.1, OpenIOC, YARA, Sigma) into a unified schema
  • Evaluating feed freshness, fidelity, and relevance to the organization's threat profile
  • Building automated enrichment pipelines that correlate IOCs against SIEM events

Do not use this skill for raw packet capture analysis or live incident triage without first establishing a CTI baseline.

Prerequisites

  • Access to a Threat Intelligence Platform (TIP) such as ThreatConnect, MISP, or OpenCTI
  • API keys for at least one commercial feed (Recorded Future, Mandiant Advantage, or VirusTotal Enterprise)
  • TAXII 2.1 client library (taxii2-client Python package or equivalent)
  • Role with read/write permissions to the TIP's indicator database

Workflow

Step 1: Enumerate and Prioritize Feed Sources

List all available feeds categorized by type (commercial, government, ISAC, OSINT):

  • Commercial: Recorded Future, Mandiant Advantage, CrowdStrike Falcon Intelligence
  • Government: CISA AIS (Automated Indicator Sharing), FBI InfraGard, MS-ISAC
  • OSINT: AlienVault OTX, Abuse.ch, PhishTank, Emerging Threats

Score each feed on: update frequency, historical accuracy rate, coverage of your sector, and attribution depth. Use a weighted scoring matrix with criteria from NIST SP 800-150 (Guide to Cyber Threat Information Sharing).

Step 2: Ingest via TAXII 2.1 or API

For TAXII-enabled feeds:

taxii2-client discover https://feed.example.com/taxii/
taxii2-client get-collection --collection-id <id> --since 2024-01-01

For REST API feeds (e.g., Recorded Future):

  • Query /v2/indicator/search with risk_score_min=65 to filter low-confidence IOCs
  • Apply rate limiting and exponential backoff for API resilience

Step 3: Normalize to STIX 2.1

Convert each IOC to STIX 2.1 objects using the OASIS standard schema:

  • IP address → indicator object with pattern: "[ipv4-addr:value = '...']"
  • Domain → indicator with pattern: "[domain-name:value = '...']"
  • File hash → indicator with pattern: "[file:hashes.SHA-256 = '...']"

Attach relationship objects linking indicators to threat-actor or malware objects. Use confidence field (0–100) based on source fidelity rating.

Step 4: Deduplicate and Enrich

Run deduplication against existing TIP database using normalized value + type as composite key. Enrich surviving IOCs:

  • VirusTotal: detection ratio, sandbox behavior reports
  • PassiveTotal (RiskIQ): WHOIS history, passive DNS, SSL certificate chains
  • Shodan: banner data, open ports, geographic location

Step 5: Distribute to Consuming Systems

Export enriched indicators via TAXII 2.1 push to SIEM (Splunk, Microsoft Sentinel), firewalls (Palo Alto XSOAR playbooks), and EDR platforms. Set TTL (time-to-live) per indicator type: IP addresses 30 days, domains 90 days, file hashes 1 year.

Key Concepts

TermDefinition
STIX 2.1Structured Threat Information Expression — OASIS standard JSON schema for CTI objects including indicators, threat actors, campaigns, and relationships
TAXII 2.1Trusted Automated eXchange of Intelligence Information — HTTPS-based protocol for sharing STIX content between servers and clients
IOCIndicator of Compromise — observable artifact (IP, domain, hash, URL) that indicates a system may have been breached
TLPTraffic Light Protocol — color-coded classification (RED/AMBER/GREEN/WHITE) defining sharing restrictions for CTI
Confidence ScoreNumeric value (0–100 in STIX) reflecting the producer's certainty about an indicator's malicious attribution
Feed FidelityHistorical accuracy rate of a feed measured by true positive rate in production detections

Tools & Systems

  • ThreatConnect TC Exchange: Aggregates 100+ commercial and OSINT feeds; provides automated playbooks for IOC enrichment
  • MISP (Malware Information Sharing Platform): Open-source TIP supporting STIX/TAXII; widely used by ISACs and government CERTs
  • OpenCTI: Open-source platform with native MITRE ATT&CK integration and graph-based relationship visualization
  • Recorded Future: Commercial feed with AI-powered risk scoring and real-time dark web monitoring
  • taxii2-client: Python library for TAXII 2.0/2.1 client operations (pip install taxii2-client)
  • PyMISP: Python API for MISP feed management and IOC submission

Common Pitfalls

  • IOC age staleness: IP addresses and domains rotate frequently; applying 1-year-old IOCs generates false positives. Enforce TTL policies.
  • Missing context: Blocking an IOC without understanding the associated campaign or adversary can disrupt legitimate business traffic (e.g., CDN IPs shared with malicious actors).
  • Feed overlap without deduplication: Ingesting the same IOC from five feeds without deduplication inflates indicator counts and SIEM rule complexity.
  • TLP violation: Redistributing RED-classified intelligence outside authorized boundaries violates sharing agreements and trust relationships.
  • Over-blocking on low-confidence indicators: Indicators with confidence below 50 should trigger detection-only rules, not blocking, to avoid operational disruption.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing saved credential exposure in authorized tests
  • Examining collected DPAPI files offline
  • Reviewing protected browser and RDP credentials
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing risky permissions identified in BloodHound
  • Validating account takeover without resetting a password
  • Generating directory change records during security exercises
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Define the assessment scope for systems handling controlled information
  • Calculate an SPRS score and prioritize unmet security requirements
  • Prepare security plans, remediation milestones, and assessment evidence
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Preserving a suspect drive before investigation
  • Creating evidence copies of USB devices or memory cards
  • Verifying that a disk image matches its source
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Auditing excessive Active Directory permissions
  • Investigating privilege escalation paths from ordinary accounts
  • Reporting affected objects and permission remediation recommendations
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Triage suspicious APK files without running them
  • Inspect dangerous permission combinations and suspicious API calls
  • Extract network indicators for malware detection rules
mukul975/Anthropic-Cybersecurity-Skills3.5만2026년 8월 31일 업데이트

mukul975의 스킬 모두 보기

이 스킬의 문제 신고