Threat Intelligence Management: Best Practices

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Security teams rely on threat intelligence like a ship’s captain relies on a lighthouse. The information enables them to see new risks and steer clear of known threats. While threat intelligence provides benefits, many security teams struggle to use it effectively. They collect the information from various tools, meaning that they have no single source of information. To use threat intelligence, security teams need a way to combine all data so that they can correlate information and analyze it efficiently. 

By following some best practices for threat intelligence management, security teams can enhance their risk mitigation and cyber resilience strategies.

What Is Threat Intelligence Management?

Threat intelligence management consists of the tools and processes used to collect, normalize, and enrich cyber threat intelligence data so that security and incident response teams can act on it. 

The Threat Intelligence Management Process covers all phases of the cyber threat intelligence lifecycle:

  • Planning
  • Identification and Collection
  • Processing
  • Analysis
  • Sharing
  • Lessons Learned

Typically, cybersecurity analysts use threat intel to help them write detection rules and engage in threat hunting. By managing data gathered from various intelligence tools in a threat intelligence platform, organizations can aggregate data from across various solutions and intelligence tools in a single location, enabling them to mitigate risks more effectively and efficiently.

Understanding the Cyber Threat Intelligence Lifecycle

Using the steps in the threat intelligence life cycle, security teams take raw data, analyze it, and then look for knowledge gaps so that they can build the necessary situational awareness. 

Planning and Direction

With so many data sources, security teams need to focus on what matters most to their organizations. The questions that you ask during the planning stage drive the data that you collect and how you use it. 

At this stage, you want to ask closed-ended questions that include:

  • Who are the attackers?
  • What are their motivations?
  • What is the attack surface?
  • What actions can strengthen defenses?
  • Who will use this report?

The answers to these initial questions will drive the responses to the open-ended questions that help you prioritize activities like:

  • How do the objectives align with the organization’s strategy?
  • How will the information be used?
  • How will the information be delivered?
  • How does the data support the organization’s risk management strategy?

After answering these questions, you can develop a threat intelligence operation roadmap that defines the goals and methodologies. 


Your objectives define the data you collect. When gathering information, you need to consider the various sources that can help you achieve your goals, including:

  • Internal sources: network logs, incident response reports
  • Technical data: indicators of compromise (IoC), vulnerability database information
  • Clear web: blogs, alerts, subject matter expert reports, social media
  • Deep and dark web: leaked data like customer personally identifiable information (PII) or user credentials


During the collection step, you’ll gather structured and unstructured data. To analyze the raw data, you need to:

  • Sort it
  • Apply metatags
  • Eliminate duplicate information
  • Filter out false positive
  • Translate information from foreign sources
  • Decrypt files

Further, with data in various formats, you need a way to normalize it so that you can make correlations between data points. Manually processing and normalizing this data is time-consuming and error prone which is why many companies turn to threat intelligence platforms that automate this step. 


With the data normalized and processed, you can start answering the questions that you prepared during the planning phase. This step is the reason you want to be able to easily correlate data from diverse sources. Consider these pieces of information:

  • Technical data: New vulnerability discovered that affects a device in your stack
  • Clear web: security researchers show how threat actors can exploit the vulnerability
  • Dark web: Infected device market lists a device on your organization’s domain

Individually, each of these data points is a cause for concern. However, when you can correlate three data points, you can turn what would otherwise be “just another risk” into a “high priority risk.”


During this phase, you share the analysis with the relevant parties which may mean providing it in different formats. For example, you might need to share with:

  • Security analysts who need technical information
  • Senior leadership who need high-level risk and impact data

Further, you want to track how people use the information, especially since you may need to follow up on remediation actions later.

Lessons Learned

Finally, you need to review the reports and determine whether they answered the original questions posed and whether those were the right questions to ask. Stakeholders may decide to change their priorities or iterate the processes. Based on this feedback, you start the whole lifecycle all over again to determine the next set of objectives and procedures.

Best Practices for Threat Intelligence Management

To create an efficient threat intelligence management program, you need the people, processes, and threat intelligence platform technology to support it. 

Aggregate Threat Intelligence in a Single Location

Aggregating all threat intelligence data in a single location eliminates the time-consuming and overwhelming task of reviewing every feed and source individually. With everything in a single location you gain at-a-glance visibility into data from the following resources:

By reducing the noise, you optimize your ability to prioritize and act on the biggest risks facing your organization.

Automate Data Processing

To use data effectively, you should automate the data normalization, deduplication, and enrichment processes. With automation you eliminate the time-consuming manual processes associated with spreadsheets while improving your analysis capabilities by:

  • Aggregating data despite divergent formats
  • Reducing noise by eliminating redundant data
  • Removing false positives
  • Scoring IoCs
  • Adding organizational context

Integrate Threat Intelligence with Current Cybersecurity Stack

Normalizing your threat intelligence also enables you to integrate it into your cybersecurity technology stack. By using a threat intelligence platform, you can connect you contextual data to your:

  • Security Information and Event Management (SIEM) 
  • Centralized log management tool
  • Endpoint detection and response solution
  • Firewall tool
  • Intrusion Detection System (IDS)/Intrusion Prevention System (IPS)

Correlating internal and external data enables you to build high-fidelity detection rules that reduce analyst alert fatigue. 

Incorporate into Incident Response 

When disseminating threat intelligence, you should include your incident response team. Threat intelligence gives them the context necessary to investigate incidents faster. For example, threat intelligence can give them insight into the vulnerability that threat actors used to gain initial access. By pointing them in the right direction, they can more rapidly contain threat actors, enabling faster remediation and recovery processes.

Flare: Threat Intelligence Management Made Simple

With Flare’s platform, you can rapidly mature your threat intelligence management program. Our platform enables you to monitor the dark web and illicit telegram channels, gain insight into human error or data leaks, and understand your attack surface. By using Flare’s platform, you can unify the core elements of cyber threat intelligence, digital risk protection, and external attack surface management in a simple, flexible, powerful solution. 

Schedule a demo with us today to get started.

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