본문으로 건너뛰기
cccskills
무료GitHub에 공개

collecting-indicators-of-compromise

Collect indicators of compromise, technical clues such as suspicious domains and file hashes, from incident evidence. Add context and confidence scores, then prepare them for detection, blocking, and structured sharing with partners.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.

실행 점수 미검증

설치 방법 보기

이럴 때 유용합니다

  • Extracting threat indicators from incident evidence
  • Adding threat context and confidence scores to indicators
  • Preparing indicator lists for detection and blocking
  • Packaging indicators for partner sharing

포함된 파일(4)

  • SKILL.md10.5 KB
  • LICENSE11.0 KB
  • references/api-reference.md2.2 KB
  • scripts/agent.py7.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Collecting Indicators of Compromise

When to Use

  • During active incident response to identify and block adversary infrastructure
  • Post-incident to document all observed adversary artifacts for future detection
  • When sharing threat intelligence with ISACs, sector partners, or law enforcement
  • When building detection rules in SIEM, EDR, or network security tools
  • When enriching IOCs with threat intelligence context for risk scoring

Do not use for behavioral TTP analysis without accompanying technical indicators; use MITRE ATT&CK mapping for behavioral characterization.

Prerequisites

  • Access to incident evidence sources: SIEM logs, EDR telemetry, memory dumps, disk images, network captures
  • Threat intelligence platform (MISP, OpenCTI, ThreatConnect) for IOC management and sharing
  • IOC enrichment tools: VirusTotal, OTX (AlienVault Open Threat Exchange), Shodan, DomainTools
  • STIX 2.1 knowledge for structured IOC representation
  • Sharing agreements with relevant ISACs (FS-ISAC, H-ISAC, IT-ISAC) or sector partners

Workflow

Step 1: Identify IOC Categories

Collect indicators across all categories from incident evidence:

Network Indicators:

  • IP addresses (C2 servers, staging servers, exfiltration destinations)
  • Domain names (C2 domains, phishing domains, DGA domains)
  • URLs (malware download, C2 check-in, exfiltration endpoints)
  • JA3/JA3S hashes (TLS client/server fingerprints)
  • User-Agent strings (custom or unusual HTTP headers)
  • DNS query patterns (tunneling signatures, DGA patterns)

Host Indicators:

  • File hashes (MD5, SHA-1, SHA-256 of malware, tools, scripts)
  • File paths (known malware installation directories)
  • Registry keys (persistence mechanisms, configuration storage)
  • Scheduled tasks and service names (persistence)
  • Mutex/event names (malware instance synchronization)
  • Named pipes (C2 communication channels, e.g., Cobalt Strike)

Email Indicators:

  • Sender addresses and domains (spoofed or attacker-controlled)
  • Subject lines and body content patterns
  • Attachment names and hashes
  • Embedded URLs
  • Email header anomalies (SPF/DKIM/DMARC failures)

Step 2: Extract IOCs from Evidence Sources

Systematically extract indicators from each evidence source:

From SIEM/Log Analysis:

# Extract unique destination IPs from firewall logs
index=firewall action=blocked
| stats count by dest_ip
| where count > 100

# Extract domains from DNS query logs
index=dns query=*evil* OR query=*c2*
| stats count by query

From Memory Forensics:

# Extract network connections
vol -f memory.raw windows.netscan | grep ESTABLISHED

# Extract strings from suspicious process memory
vol -f memory.raw windows.memmap --pid 3847 --dump
strings -n 8 pid.3847.dmp | grep -E "(http|https)://"

From Malware Analysis:

Sandbox Report IOC Extraction:
- Dropped files:      3 (hashes extracted)
- DNS queries:        update.evil[.]com, cdn.malware[.]net
- HTTP connections:   POST to https://185.220.101[.]42/gate.php
- Registry modified:  HKCU\Software\Microsoft\Windows\CurrentVersion\Run\svcupdate
- Mutex created:      Global\MTX_0x1234ABCD
- Named pipe:         \\.\pipe\MSSE-1234-server

Step 3: Enrich IOCs with Context

Add threat intelligence context to each indicator:

IOC Enrichment Report:
━━━━━━━━━━━━━━━━━━━━━
IP: 185.220.101.42
  VirusTotal:     12/89 vendors flag as malicious
  Shodan:         Open ports: 443, 8443, 80
  Geolocation:    Netherlands, AS208476
  First Seen:     2025-10-01
  Threat Intel:   Associated with Qakbot C2 infrastructure
  Confidence:     High
  TLP:            AMBER

Domain: update.evil[.]com
  Registration:   2025-10-28 (recently registered)
  Registrar:      Namecheap
  WHOIS Privacy:  Yes
  VirusTotal:     8/89 vendors flag as malicious
  DNS History:    Resolved to 185.220.101.42, 91.215.85.17
  Confidence:     High
  TLP:            AMBER

Step 4: Score and Prioritize IOCs

Assign confidence and risk scores to each indicator:

ScoreConfidence LevelCriteria
90-100Confirmed MaliciousMultiple TI sources confirm, observed in active attack
70-89Highly SuspiciousSingle TI source confirms, behavioral analysis supports
50-69SuspiciousLimited TI data, contextually suspicious
30-49UnconfirmedNo TI matches, but anomalous in environment
0-29Likely BenignFalse positive indicators or legitimate infrastructure

Step 5: Distribute IOCs for Detection and Blocking

Push IOCs to defensive systems for immediate protection:

  • Firewall/IPS: Block C2 IPs and domains
  • DNS: Sinkhole malicious domains
  • EDR: Add file hashes to blocklist, create custom IOC watchlists
  • Email Gateway: Block sender domains, attachment hashes, malicious URLs
  • SIEM: Create correlation searches for IOC matches
  • Web Proxy: Block URLs and domains in web filtering policy

Step 6: Share IOCs with Partners

Package IOCs in STIX 2.1 format for sharing:

{
  "type": "indicator",
  "spec_version": "2.1",
  "id": "indicator--a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "created": "2025-11-15T18:00:00Z",
  "modified": "2025-11-15T18:00:00Z",
  "name": "Qakbot C2 Server IP",
  "indicator_types": ["malicious-activity"],
  "pattern": "[ipv4-addr:value = '185.220.101.42']",
  "pattern_type": "stix",
  "valid_from": "2025-11-15T14:23:00Z",
  "confidence": 95,
  "labels": ["c2", "qakbot"],
  "object_marking_refs": ["marking-definition--f88d31f6-486f-44da-b317-01333bde0b82"]
}

Submit to MISP, ISAC portals, and TAXII servers per sharing agreements.

Key Concepts

TermDefinition
IOC (Indicator of Compromise)Technical artifact observed during a security incident that indicates adversary presence (hash, IP, domain, etc.)
TLP (Traffic Light Protocol)Standard for classifying the sharing restrictions of threat intelligence: WHITE, GREEN, AMBER, AMBER+STRICT, RED
STIX (Structured Threat Information Expression)Standard language for representing cyber threat intelligence in a structured, machine-readable format
TAXII (Trusted Automated Exchange of Intelligence Information)Transport protocol for sharing STIX-formatted threat intelligence between organizations
Confidence ScoreNumerical rating (0-100) indicating the analyst's certainty that an indicator is truly malicious
IOC LifecycleProcess of creating, validating, distributing, and eventually retiring indicators as they lose relevance
DefangingPractice of modifying malicious URLs and domains in reports to prevent accidental clicks (e.g., evil[.]com)

Tools & Systems

  • MISP: Open-source threat intelligence sharing platform for managing, storing, and distributing IOCs
  • VirusTotal: Multi-engine malware scanning and threat intelligence platform for IOC enrichment
  • OpenCTI: Open-source cyber threat intelligence platform supporting STIX 2.1 natively
  • Yeti: Open-source platform for organizing observables, indicators, and TTPs
  • CyberChef: GCHQ's data transformation tool useful for decoding, defanging, and formatting IOCs

Common Scenarios

Scenario: Post-Incident IOC Package for ISAC Sharing

Context: After responding to a Qakbot infection that led to Cobalt Strike deployment, the IR team must package all IOCs for sharing with the Financial Services ISAC (FS-ISAC).

Approach:

  1. Compile all network, host, and email indicators from the investigation
  2. Enrich each IOC with VirusTotal and MISP correlation data
  3. Assign confidence scores based on direct observation vs. secondary correlation
  4. Mark all IOCs with TLP:AMBER for partner sharing
  5. Export as STIX 2.1 bundle and submit to FS-ISAC TAXII feed
  6. Create a human-readable IOC summary report for email distribution

Pitfalls:

  • Including internal IP addresses or hostnames in shared IOC packages (information leakage)
  • Sharing IOCs at TLP:WHITE that should be restricted to TLP:AMBER
  • Not defanging URLs and domains in human-readable reports
  • Sharing IP addresses of legitimate CDNs or cloud providers as malicious IOCs

Output Format

INDICATOR OF COMPROMISE REPORT
================================
Incident:     INC-2025-1547
Date:         2025-11-15
TLP:          AMBER
Sharing:      FS-ISAC, internal SOC

NETWORK INDICATORS
Type     | Value                    | Confidence | Context
---------|--------------------------|------------|--------
IPv4     | 185.220.101[.]42         | 95         | Qakbot C2 server
IPv4     | 91.215.85[.]17           | 90         | Cobalt Strike C2
Domain   | update.evil[.]com        | 95         | Staging domain
URL      | hxxps://185.220[.]101.42/gate.php | 95  | C2 check-in
JA3      | a0e9f5d64349fb13191bc7...| 80         | Qakbot TLS fingerprint

HOST INDICATORS
Type     | Value                    | Confidence | Context
---------|--------------------------|------------|--------
SHA-256  | a1b2c3d4e5f6...         | 100        | Qakbot dropper
SHA-256  | b2c3d4e5f6a7...         | 100        | Cobalt Strike beacon
FilePath | C:\Users\*\AppData\Local\Temp\update.exe | 85 | Dropper location
RegKey   | HKCU\...\Run\svcupdate  | 90         | Persistence
Mutex    | Global\MTX_0x1234ABCD   | 95         | Qakbot instance lock
Task     | WindowsUpdate           | 90         | Scheduled task persistence

EMAIL INDICATORS
Type     | Value                    | Confidence | Context
---------|--------------------------|------------|--------
Sender   | billing@spoofed[.]com   | 95         | Phishing sender
Subject  | "Invoice-Nov2025"       | 70         | Phishing subject line
Hash     | c3d4e5f6a7b8...         | 100        | Malicious .docm attachment

TOTAL: 14 indicators | HIGH confidence avg: 91

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