API-first AI-curated threat intelligence feed

Best threat intelligence feed APIs for AI-curated, actionable threats

My top recommendation is Recorded Future for enterprise-grade intelligence, and ThreatCluster for an API-first, AI-oriented workflow worth evaluating. If you want emerging threats distilled into prioritized incidents, enriched indicators, vulnerability intelligence, and machine-readable data rather than a flood of raw IOCs (indicators of compromise), the best choice depends on how much automation, context, and budget you need.

The important distinction is between a feed that simply supplies threat indicators and an intelligence API that correlates sources, assesses risk, explains why a threat matters, and helps trigger a security response.www.ciopages.com+1

Top recommendations

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1. Recorded Future

(Best enterprise choice)

Commercial · Risk scoring, enrichment, threat context

Best when you need high-quality, contextual intelligence for SOC analysts, incident response, and automated security workflows. Its APIs provide risk scores, evidence, threat-actor information, and bulk enrichment for IPs, domains, URLs, file hashes, and CVEs.docs.recordedfuture.com+1

Why choose it: Actionable risk assessments backed by evidence, rather than just a list of suspicious indicators.

API documentation

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2. ThreatCluster

(Best to evaluate for AI workflows)

API-first · Incident aggregation, REST, MCP

Combines threat reporting from many sources into scored incident records, validated indicators, vulnerability intelligence, and dark-web-related reporting. It advertises more than 70 REST endpoints, along with feeds and AI-agent integrations via MCP.threatcluster.io

Why choose it: A promising fit if your application needs to retrieve emerging incidents and their supporting evidence programmatically for an AI analyst or security automation agent.

API and documentation

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3. Google Threat Intelligence

Commercial · Adversary research and attribution

Strong candidate when you need expert-curated intelligence about threat actors, campaigns, and adversary behavior, not just machine-generated IOC feeds. Particularly worth evaluating for incident response and investigations involving sophisticated attackers.www.ciopages.com+1

Why choose it: Deeper adversary context and research to help analysts understand the threat behind an alert.

Google Cloud security intelligence

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4. GreyNoise

Specialist API · IP reputation and attacker activity

Particularly useful for deciding whether an internet-facing IP is associated with opportunistic scanning, malicious activity, or known benign research. It offers curated feeds and integrations with security platforms.docs.greynoise.io+1

Why choose it: Better signal for IP-centric triage and filtering noisy network alerts. It is a complement to a broad threat intelligence provider, rather than a complete replacement.

GreyNoise documentation

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5. Microsoft Graph Threat Intelligence API

Commercial ecosystem · APIs and security enrichment

Supports programmatic access to threat intelligence articles, profiles, indicators, reputation verdicts, and infrastructure enrichment. Especially relevant if your organization already uses Microsoft security products.learn.microsoft.com

Why choose it: Integrating intelligence into an existing Microsoft-centric detection and response stack.

Official API documentation

Which one fits your requirements?

Pricing and API access

Two practical starting points stand out:

• ThreatCluster: Its published plans include free access with 100 API credits per day, a Starter tier at $7.99/month, and a Growth tier at $29/month. It advertises AI-generated analysis, source citations, scored incidents, and structured threat data. These are vendor-published prices, not an independent performance assessment.threatcluster.io+1
• Recorded Future: Offers commercial packages with API entitlements and usage limits that vary by subscription. Pricing is quote-based.docs.recordedfuture.com+1

What I would test before choosing

Whichever provider you shortlist, evaluate it against a real sample of emerging threats and check that its API provides:

1. Source provenance: Links to original reports and evidence supporting each claim.
2. Actionable prioritization: Confidence, severity, exploitation status, and relevance to your environment.
3. Freshness: First-seen timestamps, update cadence, and clear separation of newly emerging threats from older reporting.
4. Automation: REST API, webhooks, STIX 2.1, and integrations with your SIEM/SOAR.
5. False-positive control: Deduplication, indicator validation, and measurable precision on your own data.

One important caveat: AI-generated recommendations should be evidence-backed and verified before automatically blocking infrastructure or deploying changes.

My final verdict: Start with ThreatCluster if you want an accessible API that emphasizes AI-generated threat analysis and incident aggregation. Choose Recorded Future if you need a mature enterprise intelligence provider with extensive risk-enrichment capabilities. I would benchmark both against the same incidents before committing.

One question that would help me narrow this down: Are you building an AI security agent or product that consumes threat intelligence, or are you selecting a feed for an existing SOC/SIEM? The best API differs considerably between those two use cases.

Top AI-powered threat intelligence feeds with APIs (2026)

The strongest options are platforms that combine machine learning, threat-actor attribution, behavioral analytics, and continuously updated threat data with APIs that let you turn intelligence into action — such as blocking malicious infrastructure, prioritizing vulnerabilities, detecting emerging campaigns, and automating incident response.

One important distinction: not every threat intelligence API is AI-powered. Some deliver raw indicators of compromise (IOCs), while others use AI, graph analytics, and analyst-curated intelligence to explain which threats matter and what to do about them.

Based on current vendor documentation and 2026 industry comparisons, these are the providers I'd shortlist.www.cyware.com+2

1. Top providers to evaluate

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1. Recorded Future

(Best overall for risk context) (Commercial)

Uses an AI-driven Intelligence Graph to correlate open-web, dark-web, malware, technical, and other intelligence sources. It can help surface threat campaigns, adversary infrastructure, credential exposures, and risks relevant to your organization.www.recordedfuture.com+1

• API:Recorded Future API documentation
• Actionable output: Risk scores, threat-actor context, alerts, indicator enrichment, detection rules, and bulk IOC enrichment.
• Best for: Enterprise SOCs, threat hunting, cyber-risk teams, and automated prioritization.
• Caveat: Commercial access and API entitlements are required for relevant capabilities.

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2. Google Threat Intelligence

(Best for adversary intelligence) (Commercial)

Combines Mandiant threat research, Google security telemetry, and VirusTotal intelligence to help connect malware, threat actors, campaigns, and infrastructure. Google also offers AI-assisted security analysis across its security ecosystem.www.cyware.com+4

• API: VirusTotal API and Mandiant threat intelligence integration.
• Actionable output: IOC reputation, malware and campaign context, threat research, and enrichment for security investigations.
• Best for: Organizations needing high-quality adversary intelligence and malware analysis.
• Caveat: Access to premium Mandiant intelligence is distinct from standard VirusTotal API access.

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3. CrowdStrike Falcon Adversary Intelligence

(Best for detection and response) (Commercial)

Connects adversary intelligence with endpoint and cloud security operations. Its value is strongest when threat intelligence needs to feed into existing detection, investigation, and response workflows.www.ciopages.com+2

• API:CrowdStrike developer portal
• Actionable output: Threat and adversary context, indicator enrichment, and intelligence integrated with security operations.
• Best for: Teams already using Falcon or seeking to connect threat intelligence to EDR/XDR.
• Caveat: Verify which intelligence endpoints and entitlements are included in your subscription.

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4. Anomali ThreatStream

(Best for intelligence aggregation) (Commercial)

Aggregates and operationalizes intelligence from multiple sources, making it useful when you want to normalize, correlate, enrich, and distribute indicators across a security stack. Its marketplace supports integrations with multiple intelligence providers.www.anomali.com+1

• API:Anomali
• Actionable output: Consolidated IOC feeds, enrichment, intelligence distribution, and integrations with downstream tools.
• Best for: Enterprises combining multiple commercial and open-source feeds.
• Caveat: It is primarily an intelligence-management and operationalization platform; AI features and feed quality depend on the specific capabilities and sources deployed.

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5. Cloudflare Threat Intelligence APIs

(Best for infrastructure enrichment) (Plan-dependent)

Provides programmatic domain and IP intelligence, historical domain information, passive DNS, and custom indicator feeds. These capabilities are particularly useful for enriching events with infrastructure context.developers.cloudflare.com+1

• API:Official Threat Intelligence API documentation
• Actionable output: Domain/IP context, infrastructure relationships, historical signals, and custom feed data.
• Best for: Network security, DNS investigations, and web infrastructure risk analysis.
• Caveat: Strong enrichment capabilities, but don't assume every endpoint itself exposes AI-generated threat assessments.

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6. VirusTotal

(Best for IOC and malware enrichment) (Free and paid access)

Provides APIs for querying files, URLs, domains, IP addresses, reputation, and relationships between suspicious artifacts. Multi-engine analysis and behavioral evidence help automate triage; richer threat context can be added through supported integrations.docs.virustotal.com+2

• API:VirusTotal API v3
• Actionable output: Detection verdicts, artifact relationships, reputation signals, and investigation pivots.
• Best for: Security automation, malware pipelines, incident response, and enrichment of incoming alerts.
• Caveat: Multi-engine analysis is not the same as an AI-driven early-warning feed; API quotas and commercial-use terms matter.

2. Best additional options for emerging-risk detection

These are particularly worth considering if your goal is to discover new campaigns or reduce time between a threat emerging and your organization acting on it.

The first three are the stronger candidates when you need enterprise workflows and contextual intelligence. OTX and abuse.ch are useful complements, but should not be treated as equivalent to an AI-powered predictive intelligence platform.

3. How I would choose

For AI-driven early warning and risk prioritization

Start with Recorded Future and Google Threat Intelligence. Evaluate how well they identify relevant campaigns, correlate weak signals, and produce evidence-backed alerts.

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For automated detection and response

Evaluate CrowdStrike, particularly if you already use Falcon. Check whether its intelligence can be delivered directly to your SIEM, SOAR, EDR, or custom detection pipeline.

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For a multi-source intelligence pipeline

Evaluate Anomali ThreatStream or ThreatConnect to aggregate feeds, correlate indicators, manage intelligence, and route high-confidence findings into downstream controls.

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For developer-led enrichment

Start with VirusTotal and Cloudflare's intelligence APIs. Add Recorded Future or Google Threat Intelligence when you need deeper adversary context and prioritized emerging-risk alerts.

4. What makes a feed genuinely actionable?

Before choosing a vendor, check that its API exposes the information your automation needs.

One key caution: AI-generated summaries are not the same as predictive threat intelligence. Ask vendors to demonstrate that their platform detects emerging threats earlier or improves prioritization compared with a baseline of conventional feeds.

My final recommendation

I'd begin with a proof of concept comparing Recorded Future, Google Threat Intelligence, and CrowdStrike Falcon Adversary Intelligence against the same set of real-world threat scenarios. Add VirusTotal as a technical IOC-enrichment baseline and consider Anomali if consolidating multiple feeds is a primary requirement.

Score each on detection lead time, precision, false positives, API latency, contextual quality, and the percentage of alerts that lead to a concrete security action.

One question that would help me narrow this to the best three: What is your primary use case?

Primary objective

Discover emerging threats before they affect us

Enrich IPs, domains, URLs, hashes, and malware

Prioritize vulnerabilities and active exploitation

Monitor dark web, leaked credentials, and targeted threats

Automate threat detection and response

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Budget preference

Free or open-source feeds

Enterprise-grade commercial APIs

A combination of free and paid sources

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Target integration

SIEM / SOAR

Custom application or data pipeline

Cloud or network security

Threat research or threat hunting

[Find the best-fit providers]

API-based threat intelligence feeds leveraging artificial intelligence (AI), machine learning (ML), and large language models (LLMs) have shifted security operations from reactive indicators of compromise (IoCs) to predictive infrastructure analysis.anomali.com+1

The top API-driven, AI-leveraging threat intelligence platforms and feeds providing actionable insights on emerging risks include:

1. BforeAI (PreCrime Intelligence)
   • The AI Edge: BforeAI uses behavioral AI and supervised learning to monitor the "DevOps of cybercriminals". By observing infrastructure buildup (such as domain registrations and DNS mutations), its predictive engine maps out a massive knowledge graph of infrastructure behaviors to score and predict malicious intent (phishing, ransomware, fraud) weeks to months before activation (with a false positive rate under 0.05%).
   • Actionability: Integrates via modern APIs into existing DNS resolvers, firewalls, and proxies to preemptively drop or block malicious infrastructure before a campaign even launches. Learn more on the BforeAI Platform.bfore.ai+3
2. CrowdStrike Falcon Intelligence / Charlotte AI
   • The AI Edge: Powered by the massive telemetry of the CrowdStrike Security Cloud, CrowdStrike pairs high-fidelity adversary attribution with generative AI (Charlotte AI) to interpret, query, and contextualize threat data via the CrowdStrike Developer Center API Reference . It processes real-time indicator streams and surfaces automated threat reports regarding emerging zero-days and threat-actor tactics.
   • Actionability: Delivers automated context-enriched IoCs, threat actor profiles, and malware sandboxing data directly to Security Information and Event Management (SIEM) and SOAR platforms through robust API pipelines. Explore options on CrowdStrike Adversary Intelligence.crowdstrike.com+1
3. Anomali Threat Intelligence with Machine Learning Feeds
   • The AI Edge: Anomali ingests vast global telemetry and applies machine learning algorithms to normalize, de-duplicate, and score threat data, filtering out noise from open-source intelligence (OSINT), dark web, and partner feeds.
   • Actionability: Through the Anomali Marketplace , users can consume consolidated, highly curated, AI-ranked feeds covering emerging phishing, mobile malware, and C2 infrastructure via standardized APIs (STIX/TAXII or native REST APIs).cycognito.com+1
4. IBM X-Force Exchange / Watson-Powered Threat Intelligence
   • The AI Edge: IBM utilizes advanced NLP and machine learning models to scour millions of unstructured data sources (paste sites, dark web forums, research papers, and vulnerability disclosures) and turn them into structured, actionable threat indicators.
   • Actionability: The IBM X-Force Exchange API delivers real-time risk scores on IP reputations, URLs, malware hashes, and emerging vulnerabilities, allowing automated playbooks to quarantine or re-evaluate assets instantly.
5. Mandiant Advantage Threat Intelligence API
   • The AI Edge: Backed by frontline incident response data, Mandiant leverages machine learning to cluster threat activities, associate threat groups with evolving campaigns, and prioritize vulnerabilities based on real-world exploitability rather than just theoretical CVSS severity.
   • Actionability: The Mandiant Advantage API feeds automated priority alerts and machine-readable threat indicators straight into local security controls to secure environments against targeted emerging attacks.

If you're looking to integrate one of these into your stack, let me know:

• What security tools/SIEM are you currently using (e.g., Splunk, Microsoft Sentinel, CrowdStrike)?
• Are you looking more for predictive domain/infrastructure blocking or post-exploit adversary tracking?

I can help narrow down which API ecosystem fits your workflow best.