What are the most common mistakes when analyzing threat intelligence data?

1 Mistake 1: Relying on outdated or irrelevant data

One of the biggest challenges of threat intelligence is keeping up with the fast-changing and dynamic nature of cyber threats. Hackers and cybercriminals are constantly evolving their tactics, techniques, and procedures (TTPs) to bypass security measures and exploit new vulnerabilities. Therefore, threat intelligence data must be timely, accurate, and relevant to the specific context and environment of the organization. Using outdated or irrelevant data can lead to false positives, false negatives, or missed opportunities to prevent or mitigate attacks. To avoid this mistake, IT professionals should regularly update their threat intelligence sources, validate their data quality, and filter out the noise and irrelevant information.

2 Mistake 2: Ignoring the human factor

Another common mistake when analyzing threat intelligence data is ignoring the human factor behind the cyber threats. Threat intelligence is not only about technical indicators, such as IP addresses, domain names, or malware signatures. It is also about understanding the motivations, intentions, capabilities, and behaviors of the threat actors. This can help IT professionals anticipate their next moves, assess their risk level, and tailor their response strategies accordingly. To avoid this mistake, IT professionals should use a combination of technical and contextual intelligence, such as open-source intelligence (OSINT), human intelligence (HUMINT), or social media intelligence (SOCMINT).

3 Mistake 3: Overlooking the internal threats

A third common mistake when analyzing threat intelligence data is overlooking the internal threats that can originate from within the organization. Internal threats can be caused by malicious insiders, such as disgruntled employees, contractors, or partners, who intentionally or unintentionally leak, steal, or sabotage sensitive data or systems. They can also be caused by negligent insiders, such as unaware or untrained staff, who fall victim to phishing, social engineering, or other external attacks. To avoid this mistake, IT professionals should monitor and audit their internal network activity, enforce strict access control policies, and educate and train their staff on cybersecurity best practices.

4 Mistake 4: Failing to prioritize and act on the data

A fourth common mistake when analyzing threat intelligence data is failing to prioritize and act on the data. Threat intelligence data can be overwhelming and complex, especially when it comes from multiple sources and formats. IT professionals may struggle to sort out the signal from the noise, identify the most relevant and urgent threats, and translate the data into actionable insights. To avoid this mistake, IT professionals should use a threat intelligence platform (TIP) that can automate the collection, aggregation, normalization, and analysis of the data. They should also use a threat scoring system that can rank the threats based on their severity, impact, and likelihood. Finally, they should communicate and share the results of their analysis with their stakeholders and decision-makers, and implement the appropriate response measures.

5 Mistake 5: Working in silos

A fifth common mistake when analyzing threat intelligence data is working in silos. Threat intelligence is not a one-man show. It requires collaboration and coordination among different teams, departments, and functions within the organization, as well as with external partners, such as industry peers, vendors, or law enforcement agencies. Working in silos can result in duplication of efforts, inconsistency of data, or gaps in coverage. To avoid this mistake, IT professionals should establish a clear and common threat intelligence framework, such as the Cyber Threat Intelligence (CTI) cycle, that defines the roles, responsibilities, processes, and standards for threat intelligence activities. They should also use a secure and centralized platform that can facilitate the sharing and dissemination of threat intelligence data and reports.

7 Here’s what else to consider

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