Ransomware Threat Intelligence

What is Threat Intelligence?

Nearly every industry is today reliant on digital technologies. Automation and the greater connectivity they offer have transformed the world’s cultural and economic institutions. But cyberattacks are also a risk. Threat intelligence is information that helps you prevent or mitigate these attacks. Threat intelligence is rooted in data and provides context. It helps you make informed security decisions.

“Threat intelligence” is evidence-based information that includes context, mechanisms, and indicators. It also provides advice on how to respond to a threat or hazard. This intelligence can be used for decision-making regarding the subject’s response .” – Gartner

You can find more information in the sections titled “The Threat Intelligence Lifecycle” and “The Types of Threat Intelligence” of this overview.

What is Threat Intelligence?

The cybersecurity sector faces many challenges today. These include persistent and devious threat agents, an increasing number of false alarms and extraneous data across multiple security systems, and a severe shortage of skilled professionals.

Many organizations attempt to integrate threat feeds into the network but don’t know how to handle all the extra data. Analysts may feel overwhelmed by the additional data and struggle to decide which data to prioritize or ignore.

Each of these problems can be addressed by a cyber threat intelligence solution. Machine learning is used to automate data collection, processing, integration with existing solutions, and take in unstructured information from different sources. Then connect the dots by providing context and information on indicators of compromise (IoCs), and the tactics techniques and procedures (TTP), of threat actors.

It is possible to take action on threat intelligence if it is timely and provides context.

Who can benefit from Threat Intelligence?

Everyone! Cyber threat intelligence is often thought to be the exclusive domain of elite analysts. It adds value to all security functions of organizations, regardless of their size.

Threat intelligence is often treated as an additional function in a larger security paradigm and not as an essential component that augments all other functions. This results in many people who would be the most benefit from it not having access when they need it.

Security operations teams are often unable to process alerts received. Threat intelligence integrates with security solutions that you already use, helping to automatically prioritize and filter alerts. With threat intelligence, vulnerability management teams can prioritize the most critical vulnerabilities more accurately. Threat intelligence gives us a better understanding of the threat landscape, which includes key insights about threat actors, their techniques, tactics, and procedures.

For a deeper understanding of how threat intelligence can be used to benefit security roles, take a look at the section below on use cases.

The Threat Intelligence Lifecycle

How does cyber threat intelligence come to be? Cyber threat intelligence is not raw data. It is produced through a six-part process of data collection, processing, and analysis. This is a continuous process because as intelligence develops, new questions and gaps in our knowledge are discovered. New collection requirements are created. A good intelligence program is iterative and becomes more refined with time.

It is crucial that you first identify your use case and then define your objectives to maximize the value of any threat intelligence you produce.

1. Planning and Direction

Asking the right questions is the first step in producing actionable threat intelligence.

Actionable threat intelligence is best created by narrowing down the questions. Broad, open-ended questions are usually avoided.

Prioritize intelligence goals based on factors such as how closely they align with your organization’s core values and how important the decision will be for your organization.

At this stage, it is important to understand who will use and benefit from the final product. Will the intelligence be used by technical analysts who just need to report on a new exploit or executive who wants to see a general overview of trends that will help them make security investment decisions for the next quarter.

2. Collection

Next, gather the raw data necessary to fulfill the requirements of the first stage. It is best to gather data from multiple sources, including internal sources like network event logs, records of past incidents, and external sources such as the dark web, open web, and technical.

Threat data can be thought of as a list of IoCs such as malicious domains and IP addresses. However, vulnerability information may also include personally identifiable information such as customers’ personal information, raw code from paste websites, and text from news sources and social media.

3. Processing

After all, data has been collected, it is time to organize it using metadata tags.

Even small businesses collect millions of log events every day and hundreds of thousands more indicators each day. This data is too large for human analysts to efficiently process. Data collection and processing must be automated to make sense of it.

SIEMs, which make it easy to organize data using correlation rules for a variety of use cases, is a great place to start. However, they can only handle a small number of data types.

You will need a stronger solution if you are collecting unstructured data across multiple sources (internal and external). Recorded Future employs machine learning and natural-language processing to extract text from millions of unstructured documents in seven languages. It then classifies them using language-independent ontologies and events. This allows analysts to perform intuitive and powerful searches beyond simple correlation rules.

4. Analysis

Next, we need to understand the data. Analyses are designed to identify security problems and notify relevant teams.

There are many types of threat intelligence, depending on the original objectives and the intended audience. However, the goal is to present the data in a way that the audience can understand. These can be anything from simple threat lists to peer-reviewed reports.

5. Dissemination

The product is then distributed directly to the intended customers. To be useful, threat intelligence must reach the right people at the right times.

It is also important to track it so there is continuity between each intelligence cycle. This will ensure that the learning does not get lost. Integrate your ticketing systems with other security systems to track every step of the intelligence process. Each time an intelligence request is received, tickets can be submitted, completed, reviewed, and then fulfilled by multiple individuals from different teams.

6. Feedback

This is the final stage of the intelligence cycle. It closely relates to the initial planning phase and direction phase. The final step is when the intelligence product has been received. Whoever made the initial request reviews the product and decides if their questions have been answered. This is where the objectives and procedures for the next intelligence cycle are determined. Again, documentation and continuity are essential.

The Types Of Threat Intelligence

The threat intelligence lifecycle shows that the final product may look different depending upon the initial intelligence requirements, information sources, and intended audience. These criteria can help you to divide threat intelligence into several categories.

Three subcategories are often used to break down threat intelligence:

  • Strategic — These are broad trends that are meant for non-technical audiences.
  • Tactical – Outlines of tactics, techniques, and procedures of threat agents for a technical audience
  • Operational – Technical details about specific attacks or campaigns