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

Term	Definition
STIX 2.1	Structured Threat Information Expression — OASIS standard JSON schema for CTI objects including indicators, threat actors, campaigns, and relationships
TAXII 2.1	Trusted Automated eXchange of Intelligence Information — HTTPS-based protocol for sharing STIX content between servers and clients
IOC	Indicator of Compromise — observable artifact (IP, domain, hash, URL) that indicates a system may have been breached
TLP	Traffic Light Protocol — color-coded classification (RED/AMBER/GREEN/WHITE) defining sharing restrictions for CTI
Confidence Score	Numeric value (0–100 in STIX) reflecting the producer's certainty about an indicator's malicious attribution
Feed Fidelity	Historical 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.

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.1 (Monitoring), CC7.2 (Anomaly Detection)
• ISO 27001: A.6.1 (Threat Intelligence), A.16.1 (Security Incident Management)
• NIST 800-53: PM-16 (Threat Awareness), RA-3 (Risk Assessment), SI-5 (Security Alerts)
• NIST CSF: ID.RA (Risk Assessment), DE.AE (Anomalies & Events)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add analyzing-threat-intelligence-feeds

# Or load dynamically via MCP
grc.load_skill("analyzing-threat-intelligence-feeds")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.