Discovery and classification are now vital steps in a robust data security strategy. The digital era has enabled numerous benefits, but it has also brought about an alarming rise in shadow data. This refers to data that is created, stored, or shared without proper oversight or governance from security teams.
As privacy regulations tighten worldwide, businesses are compelled to take shadow data seriously to ensure compliance. Consequently, many organizations are investing in enhanced discovery and classification solutions. However, a common pitfall occurs when companies focus solely on classifying sensitive data and neglect implementing protective measures for the rest.
Protecting Everything is Imperative Data is typically classified based on its level of sensitivity:
- High sensitivity data: Financial records or intellectual property that, if compromised or destroyed in an unauthorized transaction, could have catastrophic consequences.
- Medium sensitivity data: Internal-use data, such as emails or documents, that do not contain confidential information but could still cause significant harm if compromised or destroyed.
- Low sensitivity data: Publicly available data, including marketing materials or website content.
Many businesses wrongly assume that protecting high and medium sensitivity data is sufficient. They believe low sensitivity data can be disregarded since it’s intended for public use or because the company won’t face penalties if it leaks.
Safe Haven for Hackers This assumption is not only flawed but also dangerous. Consider it akin to securing a house: failing to implement security measures for low-value items while protecting high-value possessions. Leaving the front door open 24/7 but locking away a laptop is an illogical approach. In reality, granting intruders access to the house allows them to scope out valuable items, their storage locations, security controls, and key personnel.
The same concept applies to data. Although low risk data itself may seem harmless, its susceptibility to undetected entry by hackers poses a significant threat. Once inside, cybercriminals have ample time to explore the system, locate high-risk data, study security controls, and identify database administrators (DBAs). With this information, they can launch targeted spear-phishing attacks and steal valuable data undetected.
No Data is Insignificant Paradoxically, prioritizing the protection of low risk data can prove to be a more resourceful approach, especially in the initial stages. There are two primary reasons for this. Firstly, like any IT solution, a new data security tool may cause failures or outages. It’s preferable for these issues to occur with low risk data instead of a critical data store that could paralyze the business if unexpectedly unavailable.
The second, and more critical, reason is that solely safeguarding high-risk data requires impeccable timing to prevent breaches. Hackers don’t linger when they aim to steal sensitive data. They strike swiftly and exit promptly. Conversely, monitoring low risk data provides security leaders with valuable insights, as hackers tend to experiment and probe vulnerabilities to refine their attack strategies.
Anticipating Hackers’ Moves Driven by stricter privacy regulations, the significance of discovery and classification in maintaining compliance has gained prominence globally. While this has addressed specific data security concerns, it is crucial not to conflate regulatory compliance with high-quality data security, especially concerning ‘low risk’ data. Comprehensive data security means leaving no stone unturned, even for data perceived as low risk.
Low risk data serves as a breeding ground where hackers reside, observe, learn, and bide their time until the opportune moment to strike. For businesses prioritizing data security, the objective should not be merely to catch hackers in the act but to identify their presence before they act. The most effective approach is to monitor low risk data with the same diligence as high risk data.