Cyber threat intelligence is the process of collecting and analyzing information that can help organizations understand and protect against potential cyber threats or malicious activities. Threat intelligence data helps us understand a threat actor’s motives, targets, and behaviors, as well as provide security teams with information about the threat’s context, implications, and advice on how best to deal with it. Threat intelligence feeds also help to identify Common Indicators of Compromise (IOCs) by meticulously scrutinizing things like;
- IP addresses, URLs, and Domain names.
- Email addresses, email subject, links, and attachments.
- Registry keys, filenames and file hashes, and DLLs.
Having such information readily available can help security teams proactively identify and defend against advanced persistent threats, zero-day threats, and other exploits. It enables them to develop better security protocols and strategies by identifying gaps in their existing security measures, and will help to reduce the overall cost of risk management.
Who Benefits from Threat Intelligence?
Threat intelligence can benefit any organization or individual that is concerned about the security of their digital environment. This includes businesses of all sizes, government agencies, educational institutions, healthcare providers, and even individuals who use the internet for personal purposes.
The Cyber Threat Intelligence Lifecycle
The cyber threat intelligence lifecycle includes the following steps:
Requirements: This phase will provide a road-map for specific threat intelligence operations, and will help security teams;
- Understand and prioritize what needs to be protected.
- Identify the threat intelligence needed to protect assets and respond to threats.
- Understand the impact of a cyber breach on their organization.
Collection of data: This phase involves searching for event log data, public data sources, relevant forums, and social media platforms, and subscribing to industry leaders.
Analysis of data: This phase involves conducting an analysis of the collected data to find answers to the questions posed in the requirements phase and develop recommendations for the stakeholders.
Distribution of intelligence: This phase involves translating the analysis into an understandable format and presenting the results to stakeholders. Recommendations should be presented clearly, without confusing jargon, either in a one-page report or a short presentation.
Collection of feedback: This phase involves collecting feedback from stakeholders to determine if any adjustments are needed for future threat intelligence operations. Stakeholders may change their priorities, how often they would like to receive intelligence reports, or how the data is distributed or presented.
Types of Cyber Threat Intelligence
There are three main types of cyber threat intelligence, which include:
Operational threat intelligence: This involves gathering and analyzing data from a variety of sources such as logs, alerts, and other systems, in order to identify and respond to potentially malicious activity, in real time.
Strategic threat intelligence: This involves identifying potential threats in the future and developing a plan to mitigate those threats. Teams must have a comprehensive view of the threat landscape in order to identify emerging threats and anticipate future trends.
Tactical threat intelligence: This involves identifying and responding to threats in the near-term, and can be used to create a tactical response to an immediate threat.
What Should Cyber Threat Intelligence Provide?
Cyber threat intelligence should provide insights that help organizations better understand their attackers, respond faster to incidents, and proactively get ahead of a threat actor’s next move. Threat intelligence requirements are explained in more detail below;
Multi-Source data collection & correlation: Since different perspectives yield different data and insights, data should be aggregated from as many data sources as possible – both internal and external.
Automated analysis & triage: A threat intelligence platform should perform automated analysis, triage, and prioritization of information to ensure analysts see the most important data first.
Data sharing: Threat intelligence data should be kept in a single, centralized system, and should include integrations to automatically distribute data across an organization’s security deployment.
Automation: As cyber threat actors continue to launch new and improved attacks, the use of automation to streamline the analysis and utilization of threat intelligence is crucial if you want to establish a robust data security strategy.
Actionable insights: A threat intelligence platform should provide actionable insights and security recommendations, since knowing that a particular threat exists is not the same as knowing how to respond to it.
How To Select a Threat Intelligence Platform
There are many different threat intelligence platforms and feeds available. However, it’s worth noting that, when it comes to threat intelligence, more is not always better. Subscribing to multiple feeds and attempting to aggregate and correlate them internally can result in a large amount of redundant and low-quality data. Organizations should choose a threat intelligence platform with the following characteristics:
Real-time data: Since many cyber-attacks last only hours or minutes, an effective threat intelligence platform will provide insights based on real-time data.
Extended threat visibility: A threat intelligence platform should provide insights not only on threats targeting a company’s specific industry but also on threats facing the larger market.
Integration with other solutions: A threat intelligence platform should be able to integrate with multiple cyber-security solutions to automatically respond to threats as they are detected.
How Lepide Helps with Threat Intelligence
While the Lepide Data Security Platform doesn’t curate and publish threat intelligence feeds, it does aggregate and correlate event data from a wide range of platforms, including Azure AD, Office 365, Exchange Server, Google Workspace, Amazon S3, and more. It uses machine learning models to differentiate between legitimate user activity and activity that is potentially malicious. It can also generate real-time alerts and detailed reports, and even automate a response to events that match a predefined threshold condition.
If you’d like to see how the Lepide Data Security Platform can help you aggregate and correlate important security information, schedule a demo with one of our engineers or start your free trial today.