In this article, we will explore threat intelligence, which plays a key role in data-driven cybersecurity decision-making and enables rapid and accurate threat responses.
Table of Contents
- Article Summary
- Concept and Necessity of Threat Intelligence
- The Four Key Types of Threat Intelligence
- The 6-Stage Cycle of Threat Intelligence
- Current and Future of Threat Intelligence
- FAQ
- Conclusion
Article Summary
- Threat intelligence (TI) is a data-driven approach for making cybersecurity decisions quickly and accurately. By analyzing diverse threat data, organizations can generate and leverage relevant threat intelligence to strengthen their security posture.
- Modern cybersecurity attacks are becoming increasingly sophisticated and diversified. Threat intelligence helps predict and respond to potential cyber threats proactively.
- Threat intelligence can be classified into strategic, tactical, operational, and technical types based on its purpose.
- It is generated and applied through a process that includes planning, collection, processing, analysis, dissemination, and feedback. If conducting all these steps internally is challenging, Cyber Threat Intelligence (CTI) platforms, like Criminal IP, can be used.
- The integration of threat intelligence with AI addresses issues such as data integrity, false positives, and false negatives enabling real-time threat identification and automated crisis response, while also helping to resolve the issue of insufficient security personnel.
Concept and Necessity of Threat Intelligence
What is Threat Intelligence?
Threat intelligence is the cornerstone of data-driven cybersecurity decision-making. It identifies potential threats, including threat actors, attack techniques, Common Vulnerabilities and Exposures (CVEs), exploited IP addresses, phishing sites, and other risks in a security environment. Threat intelligence strengthens an organization’s security posture by collecting and analyzing this data. It supports data-driven security decisions, enabling faster and more accurate threat responses.
The Need for Threat Intelligence
Modern cyberattacks are becoming increasingly sophisticated and diverse. Highly sophisticated and persistent threat actors like Advanced Persistent Threat (APT) continuously target a company’s internal systems and data. Zero-day vulnerabilities and social engineering attacks are also occurring frequently. Furthermore, the more accessible software development environment has introduced a new cyber threat in the form of supply chain attacks. In this context, threat intelligence helps organizations predict and respond to threats in advance, allowing them to select and use industry-specific threat data effectively.
The Four Key Types of Threat Intelligence
Threat intelligence can be categorized into four types: Strategic Intelligence, Tactical Intelligence, Operational Intelligence, and Technical Intelligence. Let’s first look at a table summarizing these types, then dive into each one in more detail.
| Type | Definition | Key Applications | Example Use Cases |
| Strategic Intelligence | Long-term, high-level decision-making support | Policy creation, investment decisions | Industry-specific threat reports |
| Tactical Intelligence | Information about TTPs (Tactics, Techniques, and Procedures) | Defensive strategies for operations teams | Attacker profiling and TTP analysis |
| Operational Intelligence | Real-time threat detection and response support | SOC, incident response | Blocking malicious IPs, detecting C2 servers |
| Technical Intelligence | Detailed technical data (IoC) | Automated system detection and blocking | Updating IoCs in SIEM, malware removal |
Strategic Intelligence
Strategic Intelligence provides long-term threat information to senior executives or decision-makers. It helps develop policies, strategies, and risk management approaches based on an analysis of overall cyber threat trends, technological developments, and threats within specific industries. Threat intelligence is often utilized from a more macro perspective. TI can be used to determine where to prioritize security budget investments, manage risks based on global threat trends, and finally, identify the key cybersecurity threats faced by specific industries (such as finance, healthcare, etc.).
Tactical Intelligence
Tactical Intelligence provides detailed information about attack Techniques, Tactics, and Procedures (TTPs) to help security operations teams respond to specific threats. This includes collecting information about the tools, techniques, and behaviors attackers use, and using this information to train security operations teams on the latest threat trends and defense methods.
Operational Intelligence
Operational Intelligence provides real-time or short-term threat data, helping security teams respond immediately to incidents. It assists in identifying threats and responding to them in real time by analyzing network events and correlating threat data. It is used to strengthen SOC (Security Operation Center) and helps develop response strategies by profiling threat actors or attack campaigns.
Technical Intelligence
Technical Intelligence includes specific threat data such as malware samples, hash values, phishing domain addresses, and malicious IP addresses. It can be directly applied to threat detection systems and automated tools, such as SIEM, IDS/IPS, and firewalls. It is used to block known malicious IPs and phishing domains and for threat assessment of identified assets in attack surface management. It is also used to update the attack indicators of threat actors, enabling preparedness against the latest threats.
The 6- Stage Cycle of Threat Intelligence
Threat intelligence is not just about collecting and analyzing data; it is a systematic, iterative process that generates insights through the 6-stage cycle. Let’s first look at the summarized table, then explore each stage in detail.
| Stage | Main Purpose | Use Cases and Tools |
| Planning | Define goals and requirements | Set directions for threat data collection |
| Collection | Gather data from sources | Use OSINT, HUMINT, TECHINT |
| Processing | Organize and convert data | Structure and categorize data |
| Analysis | Identify and evaluate threats | Correlation analysis, risk evaluation, machine learning |
| Dissemination | Share actionable information | Custom reports, real-time sharing via CTI platforms |
| Feedback | Improve process | Effectiveness analysis, strategy adjustments, collaboration feedback |
1. Planning
Goal: Clear objectives for generating threat intelligence and define how data will be collected and analyzed according to the organization’s security needs.
Key activities: Defining information requirements and setting collection plans, such as determining where to gather threat intelligence. Common sources include OSINT (Open Source Intelligence), HUMINT (Human Intelligence), and TECHINT (Technical Intelligence).
2. Collection
Goal: Collect threat data from various sources, which forms the foundational data needed to generate intelligence.
Key activities: Gathering publicly available OSINT, such as exposed vulnerabilities and information about compromised software supply chains, as well as WHOIS data for IP addresses, IoT device information, and phishing site data. TECHINT and HUMINT are also used for technical data collection and intelligence from human networks, respectively.
3. Processing
Goal: Organization and conversion of data collected in the previous stage into usable formats.
Key activities: Removing duplicate or irrelevant data, structuring unstructured data into organized formats like CSV or JSON, and classifying it according to its use case (e.g., malicious IPs, phishing domains, favicon hashes).
4. Analysis
Goal: Analyzation of structured data to generate meaningful intelligence.
Key activities: Identifying threat patterns, profiling threat actors based on their TTPs, correlating network events with threat data, and evaluating the severity and likelihood of a threat. This stage may involve machine learning to analyze large amounts of threat data and connect various data sources to derive threat events.
5. Dissemination
Goal: Distributeintelligence generated within the organization to stakeholders in an actionable format. This allows organizations to prepare and respond to security threats.
Key activities: Providing threat intelligence tailored to an organization’s needs, offering security reports and real-time alerts. When generating internal threat intelligence is difficult, CTI platforms like Criminal IP enable teams to share real-time data and proactively address risks by analyzing exposed assets.
6. Feedback
Goal: Evaluate the results of the previous cycle and identify areas for improvement to be incorporated into the next cycle. This process allows for more tailored threat intelligence to be developed, better suited to the organization’s situation and challenges.
Key activities: Assess the effectiveness of the provided threat intelligence in actual threat detection and response, reviewing and improving the overall process of building, and utilizing threat intelligence. Finally, seek better utilization strategies through feedback from collaborating departments.
Current Challenges in Threat Intelligence
Although threat intelligence is essential for enhancing an organization’s security posture, there are several challenges in its implementation. Representative issues are data quality, lack of skilled analysts and expertise, data overload, and false positives. Let’s review these problems and possible solutions.
1. Data Quality Issues
If collected data is inaccurate, incomplete, or outdated (such as an outdated IoC), it can confuse security teams and lower overall trust in the data. Furthermore, different data sources can lead to inconsistent trust levels, causing false positives and false negatives. To address this, automated processes can be set up to evaluate the timeliness and reliability of data, cross-verify data from multiple sources, and remove outdated IoCs through real-time updates.
2. Lack of Skilled Analysts and Expertise
Organizations often face a shortage of skilled personnel capable of analyzing threat data and generating actionable intelligence, or their in-house security teams may lack the capacity and time to process threat data effectively. In such cases, leveraging threat intelligence platforms like Criminal IP can be a valuable solution. By focusing on utilizing these platforms, organizations can reduce the burden of generating intelligence and address the challenges posed by a lack of analytical and operational resources.
3. Data Overload and False Positives
The abundance of data may result in the inability to identify truly critical threats, while a significant portion of threat detections may lead to false positives, increasing the fatigue of security teams. To address this, organizations can generate actionable threat intelligence that includes the context of threats, attackers’ TTPs (Tactics, Techniques, and Procedures), etc., rather than simply providing IP addresses or hash values. For the issue of false positives, leveraging AI and machine learning models can enhance the reliability of alerts, and cross-validation of data can further mitigate the problem.
Threat Intelligence Combined with AI
AI has significant potential to overcome the limitations of traditional threat intelligence by enhancing data analysis and threat detection capabilities. Let’s explore on threat intelligence combined with AI:
1. Threat Prediction Models
AI can learn from historical data to perform predictive analytics. This allows organizations to proactively respond to upcoming security threats. By analyzing factors such as time, location, and IoC (Indicators of Compromise) patterns, AI can predict the attacks most likely to occur next.
2. Automated Response Capabilities
The generated threat intelligence can be integrated with SOAR (Security Orchestration, Automation, and Response) platforms to update firewall policies, block malicious IP addresses and domains, or take actions such as disabling suspicious accounts.
3. Custom Threat Intelligence Generation
The threat data required varies across different industries. AI utilizes diverse threat data to generate threat intelligence optimized for specific industries and companies. This enables organizations to develop the capability to address unique security threats.
Frequently Asked Questions (FAQs)
What are the differences between major data sources for collecting threat intelligence (OSINT, HUMINT, TECHINT)?
OSINT (Open Source Intelligence): This involves data gathered from publicly available resources, such as IP addresses, websites, social media, news outlets, and public reports. It is cost-effective and easily accessible, but additional effort is required to validate its reliability and accuracy.
HUMINT (Human Intelligence): Information collected through human interactions and networks, such as insights from internal sources, security communities, and online forums. While this type of intelligence is often high-quality, the collection process can be complex and time intensive.
TECHINT (Technical Intelligence): Involves technical data derived from sources like network traffic analysis, malware investigations, and digital forensics. It is particularly effective for real-time threat detection and response but requires specialized technical expertise to analyze and apply.
How is threat intelligence integrated into other security solutions?
Threat intelligence is integrated with various security solutions to strengthen a company’s security posture. It can be integrated into Attack Surface Management (ASM) solutions to conduct threat analysis on the different attack surfaces identified within the company. Integration with firewalls and IDS/IPS systems helps identify and block malicious traffic. On top of that, by combining Security Orchestration, Automation, and Response (SOAR) technologies, the process of threat detection, analysis, and response can be automated, improving overall efficiency in managing security incidents.
How can threat intelligence be used to enhance corporate security?
Threat detection and prevention using threat intelligence play a crucial role in enhancing corporate security.
- Threat Prediction and Proactive Response: Analyzing historical threat data allows organizations to anticipate future attack patterns and take preemptive action to stop attackers before they infiltrate systems.
- Accurate Detection and Blocking: Threat intelligence utilizes databases of known threat data—such as malicious IP addresses, domains, and hashes—to enable rapid identification and mitigation of threats. This is particularly effective against zero-day vulnerabilities and advanced persistent threats (APTs).
- Strengthening Security Policies with Relevant Threat Data: By aligning security policies with actual threats, organizations can adopt a risk-based approach to improve their overall defense mechanisms.
- Real-Time Threat Analysis: Platforms and tools powered by threat intelligence provide real-time data analysis, facilitating the immediate detection of potential threats and enabling swift response to reduce potential damages.
- Continuous Updates and Learning: As threat intelligence continuously incorporates and evaluates new threats, it ensures that security systems remain updated and agile, capable of adapting to increasingly sophisticated cyberattacks.
Conclusion
As businesses accelerate their digital transformation, cross-border cyber threats have become more sophisticated and specialized. threat intelligence aims to provide companies with up-to-date security threat data to help them respond to the ever-increasing cyber threats. Updated threat intelligence is integrated into more advanced security solutions, ultimately protecting businesses from cybersecurity threats.
The threat intelligence search engine Criminal IP aims to provide the latest threat data. It offers a variety of threat intelligence, including malicious IP addresses, IoT devices exposed to the internet, domain information, site code analysis, the latest vulnerability data, and information about recently active hacking groups. Additionally, Criminal IP provides integrated threat intelligence solutions such as Criminal IP ASM proactive cyber threat response and effective threat management, Criminal IP FDS for countering payment fraud and credential stuffing attacks, and Criminal IP CTIDB for downloading the latest threat intelligence to local servers. If you’re interested in the security solutions offered by Criminal IP, click on each solution for more information.
Sources
MWR threat intelligence report (2015)
Ishikawa Tomohisa, Cyber Threat Intelligence(2022)