Open-Source Intelligence (OSINT) has proven itself critical to effective cybersecurity in recent years. It offers fairly reliable threat intelligence along with low operational costs, minimal hardware requirements, and near universal accessibility. In fact, some OSINT tools currently on the market perform better than their proprietary counterparts. But despite its many advantages, OSINT does have limitations.
Due to those limitations, an OSINT investigation platform might be best combined with more traditional intelligence gathering strategies when organizations can afford it. Otherwise, an organization relying exclusively on OSINT tools needs to be prepared for the fact that there will be some gaps.
Access to Restricted Data
DarkOwl, a leading provider of dark web OSINT investigation tools, says that one of the biggest challenges of going with the open source model is having limited or no access to restricted data. One of the strengths of the OSINT model is cost effectiveness due to its reliability on publicly available data. But sometimes investigators need restricted data to complete their investigations.
Private accounts, closed forums, and any other data sources that are hidden behind paywalls are out of bounds for OSINT tools. There could be valuable information hiding behind those paywalls. Without access to it, a security team might not have the complete picture.
Data Might Not Be So Reliable
Another OSINT strength is that data comes directly from targeted sources in real time. But even this advantage comes with limitations. Real time information gleaned from a social media site, for example, might not necessarily be reliable. More importantly, threat actors aware of how dark web OSINT tools work could very easily post misinformation designed to throw investigators off their tracks.
Purposely spreading false information to mislead both cybersecurity investigators and the general public is fairly common in dark web circles. So any and all data gleaned from questionable sources needs to be taken with a grain of salt.
Potential Data Overload
Where more traditional intelligence gathering strategies tend to be target-specific and narrow in scope, OSINT investigation tools generally take a broader approach. They gather as much data as they can find. Later on, data is analyzed and parsed.
One of the implications of such broad-based data gathering is the potential for data overload. OSINT produces unimaginable amounts of data by default. Much of that data will prove irrelevant or misleading to ongoing investigations. Analysts are forced to spend time filtering out the noise in order to get at data they can actually use.
Gathered Data Has to Be Verified
Verification and validation are two more limits inherent to the dark web OSINT investigation model. More traditional intelligence gathering strategies, particularly those involving classified intelligence, produce data that has already been verified. That is not the case with OSINT.
All OSINT data must be cross-checked and validated for verification purposes. Otherwise, it cannot be trusted implicitly. This can add significantly to the security team’s workload. But with experience, analysts should learn how to quickly verify and validate information.
Imperfect but Still Very Good
OSINT is by no means perfect. It has its strengths and weaknesses. But all things considered, it is still a very good option for conducting threat intelligence without investing the time and resources in more traditional intelligence gathering practices.
That said, organizations able to combine more traditional practices with OSINT get the best of both worlds. The strengths of one counteract the weaknesses of the other and vice versa. In an ideal scenario, organizations would have access to every intelligence gathering tool and strategy on the market. But when that is not the case, OSINT is a tool worth utilizing.