The Complete Guide to Collecting Threat Intelligence

Learn how to transform raw data into threat intelligence that actually prevents attacks.

Infostealer attacks via phishing emails nearly doubled in 2024, with IBM tracking an 84% weekly increase compared to the previous year.

Yet your analysts waste 90% of their time filtering noise instead of hunting real threats.

Most threat intel programs fail because they collect everything instead of what really matters.

Here’s how to build a threat intelligence collection process that actually protect your organization.

How is threat intelligence collected?

Threat intelligence collection isn’t some magical process where data just appears on your desk. It’s actually a lot like being a detective, except instead of solving one crime, you’re trying to prevent thousands of them simultaneously.

The whole thing starts with what we call “requirements”. That’s basically figuring out what threats actually matter to your organization. You wouldn’t believe how many teams skip this step and end up drowning in irrelevant data about threats that’ll never touch their infrastructure. I’ve seen Fortune 500 companies tracking Linux malware when they’re a 100% Windows shop. Makes no sense, right?

Here’s how most teams actually collect threat intelligence: Automation is the backbone of any threat intel operation. We’re talking about:

• Threat feeds that pump in IoCs (indicators of compromise) 24/7
• APIs pulling data from security vendors
• Honeypots catching actual attack attempts
• Network sensors monitoring for suspicious patterns

But here’s the thing, automation only gets you so far. The really valuable intelligence often comes from human collection methods or HUMINT. Security researchers hanging out on dark web forums, analysts piecing together attack patterns from multiple incidents, even good old-fashioned information sharing between trusted partners.

I’ll let you in on something: some of the best threat intelligence I’ve ever seen came from a random conversation at a security conference. No fancy tools, just one CISO telling another, “Hey, we just got hit with this weird attack pattern…”

The technical side involves a ton of data normalization and enrichment. Raw threat data is messy, different formats, conflicting information, tons of false positives. You need solid processes to clean it up, correlate it with your environment, and turn it into something actionable. Think STIX/TAXII formats, MISP platforms, that sort of thing.

What really separates good threat intelligence collection from the mediocre stuff? Context and validation. Anyone can collect IP addresses and file hashes. But understanding why those indicators matter, how they fit into larger attack campaigns, and whether they’re actually relevant to your organization is where the real work happens.

The biggest mistake I see? Teams thinking more data equals better intelligence. You’re better off with a focused collection strategy that aligns with your actual risks than trying to boil the ocean. Quality beats quantity every single time in this game.

And honestly the collection process is constantly evolving. Threat actors change their tactics, new intel sources pop up, and what worked last year might be useless today. You’ve got to stay flexible and keep refining your approach.

Speaking of sources, that brings us to the next big question, where exactly does all this intelligence come from? Because knowing how to collect is only half the battle; you also need to know where to look…

What are common threat intelligence sources?

There is no single magic source that’ll give you everything you need. It’s more like assembling a puzzle where different pieces come from different places.

First up, you’ve got your open source intelligence (OSINT). This is the bread and butter for most teams, honestly. We’re talking Telegram channels, Twitter feeds from researchers, paste sites, and hacker forums where threat actors hang out. Yeah, you’ll spend time on some sketchy sites, but that’s where you often spot indicators before they hit mainstream feeds. Tools like Shodan and VirusTotal are absolute goldmines when you know how to use them right.

Then there’s commercial threat intelligence feeds. These aren’t cheap, but vendors like Recorded Future, CrowdStrike, and of course Breachsense do the heavy lifting of aggregating and enriching data. The reality is, if you’re protecting anything significant, you probably need at least one commercial feed. They’ve got analysts watching threat actor groups 24/7, something most companies can’t do in-house.

Your internal sources are criminally underrated. I’m talking about:

• Your SIEM logs and alerts
• Incident response reports from past breaches
• Honeypots (if you’re running them)
• Email gateway catches
• That weird behavior your SOC analyst noticed last Tuesday

Government sources deserve a mention too. CISA alerts, FBI flash reports, and sector-specific ISACs share genuinely useful intel. Sure, it’s not always cutting-edge, but when the feds issue a warning about active exploitation, you listen.

Don’t overlook industry sharing groups either. Whether it’s formal ISACs or informal Slack channels with peers, these communities often share indicators faster than any vendor. Nothing beats a heads-up from someone who just dealt with the same attack you’re about to face.

Dark web monitoring is another piece of the puzzle. You can do this yourself (with proper precautions) or pay for a service. Either way, knowing when your company’s data shows up for sale is pretty valuable intel.

The trick isn’t just collecting from all these sources, it’s knowing which ones to trust for what. That forum post might give you early warning, but your commercial feed probably has better attribution. Your internal logs might show the actual attack, while OSINT helps you understand the campaign behind it. Think about it this way: effective threat intelligence is really about correlating all these different sources to build a complete picture. And that brings us perfectly to how you actually process all this information through the different stages…

What are the 5 stages of threat intelligence?

So you’ve got all these sources spewing data at you, now what? This is where the threat intelligence lifecycle comes in, and yeah, there are five stages everyone talks about. But here’s what they actually look like in practice.

Stage 1: Planning and Direction

This is where you figure out what questions you’re actually trying to answer. “We need threat intelligence” isn’t a plan - it’s a wish. You need specifics. Are you worried about ransomware hitting your endpoints? Supply chain attacks? That new CVE everyone’s freaking out about? I’ve seen too many teams skip this stage and end up drowning in irrelevant data. Trust me, spending time here saves you from chasing ghosts later.

Stage 2: Collection

Remember all those sources we just talked about? Now you’re actively pulling from them. But collection isn’t just hoarding every IOC you find. It’s targeted gathering based on what you decided in stage one. Maybe you’re pulling specific actor TTPs from your commercial feed, grabbing relevant samples from VirusTotal, or monitoring paste sites for your company mentions. The key? Don’t try to boil the ocean.

Stage 3: Processing

Raw data is basically useless. That massive CSV of domains? Those unstructured forum posts? They need to be normalized, deduplicated, and enriched. This is where you’ll spend most of your time (or your tools will). You’re turning that mess of information into something your systems can actually use, standardized formats like STIX/TAXII if you’re fancy, or maybe just clean JSON that your SIEM can ingest.

Stage 4: Analysis

Here’s where the magic happens. You’re connecting dots, identifying patterns, and figuring out what actually matters to YOUR organization. That campaign targeting healthcare? Maybe not your problem if you’re in manufacturing. But wait, they’re using a technique that could work against your VPN setup? Now we’re talking. Good analysis turns noise into actionable intelligence.

Stage 5: Dissemination

Intelligence sitting in an analyst’s head helps nobody. You need to get the right information to the right people in a format they’ll actually use. Your SOC needs IOCs for detection. Leadership wants to know about strategic threats. The vulnerability management team needs to know which CVEs threat actors are actually exploiting. Different audiences, different products.

The thing is, this isn’t a one-and-done process. It’s a cycle that keeps spinning. That disseminated intelligence generates feedback, new requirements pop up, and you’re back to planning again.

Now, here’s the million-dollar question: with all this intelligence flowing through these stages, how do you know if what you’re producing is actually any good? Because let me tell you, not all threat intelligence is created equal…

How to evaluate threat intelligence quality

I’ve seen teams waste countless hours chasing bad intel, so let’s talk about how to spot the good stuff. Quality threat intelligence isn’t just about having the latest IOCs, it’s about having intel you can actually trust and use.

Relevance is your first filter. I don’t care how sophisticated that APT campaign analysis is, if they’re targeting Linux servers and you’re running pure Windows, it’s noise. Ask yourself: Does this actually apply to my environment? My industry? My tech stack? The best intelligence in the world is worthless if it doesn’t match your threat landscape.

Timeliness matters more than people think. That IP address might’ve been malicious last week, but what about now? Threat actors rotate infrastructure constantly. I’ve watched teams block IPs that had already been cleaned and repurposed for legitimate use. Fresh intel isn’t always better intel, but stale intel can be worse than no intel.

Here’s how I judge accuracy and confidence:

• Does the source explain HOW they know this?
• Are they showing their work or just making claims?
• Can you corroborate it with other sources?
• Is there a confidence level attached?

If someone says “high confidence” without explaining why, I’m skeptical.

Actionability separates real intelligence from interesting reading. Can you actually DO something with this information? “Threat actors are increasingly sophisticated” - thanks, super helpful. But “This specific PowerShell command is being used to establish persistence”? Now I can hunt for that. I can write detections. That’s actionable.

The source reputation game is tricky. Even good sources have bad days, and sometimes random researchers drop absolute gold. But patterns matter. Track which sources consistently deliver value for YOUR needs. That blogger who always covers ICS threats? Gold for an energy company, maybe less so for a retail chain.

Don’t forget about context and attribution. “This IP is bad” tells me nothing. “This IP is hosting a C2 server for FIN7’s latest campaign targeting restaurant POS systems” tells me everything. Context transforms data points into intelligence.

I also look at completeness. Are they giving you:

• Just IOCs or also TTPs?
• Single indicators or campaign patterns?
• Technical details AND strategic implications?

Here’s a practical tip: Set up a simple scoring system. Rate each piece of intel on relevance, timeliness, accuracy, and actionability. After a few months, you’ll see which sources consistently score high for your needs.

The reality is, even with these quality checks in place, getting good threat intelligence is harder than it should be. There are some fundamental challenges everyone faces when trying to collect useful intel…

What are the most common challenges in threat intelligence collection?

Let’s be honest, collecting threat intelligence can be a absolute nightmare sometimes. Every team I’ve worked with hits the same walls:

Information overload is the big one. You set up your feeds thinking more data equals better security, and suddenly you’re drowning in 50,000 new IOCs daily. Your analysts are spending all day just trying to keep up with the firehose instead of actually analyzing threats. I’ve seen talented analysts burn out just from alert fatigue. The worst part? Less than 1% of those indicators actually matter for your environment.

Then there’s the lack of context problem. You get an alert: “Malicious IP detected!” Cool, but malicious how? Part of a targeted campaign against your industry? Some spray-and-pray botnet? A compromised WordPress site hosting malware? Without context, you’re flying blind. Most feeds give you data without the story, and the story is what helps you prioritize.

False positives will drive you insane. That “malicious” domain your expensive feed flagged? It’s Microsoft’s update server. That suspicious file hash? Legitimate software your dev team uses. You block it, stuff breaks, people get angry, and suddenly threat intelligence has a bad reputation in your org. I’ve spent way too many hours explaining why half our marketing team couldn’t access their analytics tools.

Standardized Data formats is something vendors love to ignore. One feed gives you JSON, another uses STIX 1.x (yeah, the old version), a third sends CSVs, and your OSINT scripts output whatever format seemed good that day. Now you need a data pipeline just to normalize everything before you can even start analysis.

Timeliness versus accuracy is a constant battle. Fast intel is often wrong. Accurate intel is often late. By the time that thoroughly-vetted report hits your inbox, the campaign might be over. But jump on every unverified indicator? You’ll be chasing false leads all day.

Don’t get me started on attribution challenges. Everyone wants to know “who’s attacking us?” but attribution is hard, expensive, and often impossible. Threat actors share tools, buy the same exploits, and deliberately plant false flags. Unless you’re a nation-state target, perfect attribution might not even matter - focus on the behaviors instead.

Resource constraints hit everyone. Good threat intelligence requires:

• Skilled analysts (expensive and hard to find)
• Time for actual analysis (not just clicking through alerts)
• Tools and infrastructure (those commercial feeds add up)
• Ongoing training (threats evolve fast)
• Most teams are understaffed, underbudgeted, and overwhelmed.

The trust and validation issue is huge too. How do you verify intel without tipping off attackers? How do you share sensitive findings without exposing your own vulnerabilities? That “trusted” sharing group might include your competitors, or worse, the threat actor.

Here’s the thing though, these challenges aren’t going away. What separates successful threat intelligence programs from failures isn’t avoiding these problems, it’s building processes and tooling to manage them effectively…

What are the best practices for integrating threat intelligence tools?

Alright, so you’ve got your threat intel sources figured out, you know the challenges - now let’s talk about actually making these tools work together without losing your mind. Because buying tools is easy; integrating them properly? That’s where things get interesting.

Start with your existing security stack. I can’t stress this enough, don’t build a separate threat intel empire. Your SIEM, EDR, firewall, and other tools probably already have threat intel capabilities. Use them! I’ve seen teams spend six figures on a TIP (Threat Intelligence Platform) when their SIEM could’ve handled 80% of their needs with proper configuration.

API integration is your best friend. If a threat intel tool doesn’t have a decent API, think twice. You want automated ingestion, not analysts copying and pasting IOCs. Set up your integrations to:

• Pull fresh intel automatically
• Push enrichment data back
• Update confidence scores based on local observations
• Remove stale indicators (please, for the love of all that’s holy, age out old IOCs)

Here’s my integration hierarchy:

1. Direct integration (tool talks directly to tool)
2. TIP as a middleman (if you need heavy processing/enrichment)
3. SOAR platform (when you need complex workflows)
4. Custom scripts (last resort, but sometimes necessary)

Normalize everything at ingestion. Remember the lack of standardized formats I mentioned? Fix it once at the integration point, not every time you need to use the data. Pick a standard (STIX 2.1 is solid) and stick to it. Your future self will thank you.

Context enrichment should be automatic. When an IOC comes in, your tools should automatically:

• Check if you’ve seen it before
• Pull related threat actor info
• Add GeoIP data
• Check against your asset inventory
• Calculate relevance scores

Manual enrichment doesn’t scale.

Set up feedback loops. This is where most integrations fail. Your SOC sees a false positive? That should flow back to adjust confidence scores. Your IR team confirms a true positive? That should boost the source’s reputation. Without feedback, you’re just consuming intel, not improving it.

Watch out for performance impacts. I’ve crashed production firewalls by loading too many threat intel rules. Test your limits:

• How many IOCs can your firewall handle?
• What’s your SIEM’s lookup limit?
• How fast can your EDR process updates?

Build in rate limiting and prioritization.

Deduplication is critical. You’ll get the same IOC from five different feeds. Without deduplication, you’re wasting resources and possibly triggering multiple alerts for the same thing. Dedupe based on the indicator AND context. Note, the same IP but different campaign context might be worth keeping separate.

The human element matters too. Train your team on:

• Which tool to check for what
• How to pivot between platforms
• When to trust automated enrichment vs. manual analysis
• How to contribute intel back

A few practical tips that’ll save you headaches:

• Version control your integration configs
• Monitor API rate limits religiously
• Build in graceful failure handling
• Create separate feeds for high-confidence vs. experimental intel
• Document which tools consume which feeds

Testing and validation should be continuous. Run regular drills:

• Drop a known-bad indicator into your environment (safely!)
• Time how long until detection
• Track which tools caught it
• Identify gaps in coverage

And that’s it…

That’s all you need to know about collecting threat intel.

All that’s left is to get started.

Good luck!

Collecting Threat Intelligence FAQ

What are the three types of threat intelligence?

The three types are strategic (high-level trends and actor motivations for executives), operational (campaign details and TTPs for security teams), and tactical (specific IOCs like IPs and hashes for your tools).

What are TTPs and IOCs?

TTPs (Tactics, Techniques, and Procedures) are the adversary’s playbook — how they actually break in, move laterally, and achieve their objectives. IOCs (Indicators of Compromise) are the breadcrumbs they leave behind like malicious IPs, file hashes, or domain names. Focus on TTPs for proactive defense since IOCs expire quickly, but you’ll still need both. IOCs for immediate blocking and TTPs for understanding what attackers will do next.

What Are Threat Intelligence Feeds?

Treat threat intelligence feeds as continuous streams of security data from commercial vendors, open source, or ISACs. They deliver IOCs, vulnerability intel, and threat actor updates directly into your security stack.

What is a Threat Intelligence Platform?

A Threat Intelligence Platform (TIP) is your central hub for collecting, enriching, and distributing threat intel. It turns raw data feeds into actionable intelligence your security tools can actually use. Instead of manually copying IOCs between spreadsheets and consoles, a TIP automates the entire workflow from ingestion through deployment while tracking which threats actually matter to your environment.

What is a SOAR?

A SOAR (Security Orchestration, Automation, and Response) platform automates your repetitive security tasks, like data enrichment, running playbooks, and coordinating responses across your entire security stack.