In “A Tacky Graph and Listless Defenders: Looking Beneath the Attack Surface,” JupiterOne researchers expand upon the 2022 State of Cyber Assets Report analysis to better understand the attack surface and attack paths.
The team analyzed more than 272 million nodes from 2,285 organizations, and was guided by a few questions as they performed this research:
- Where are defenders in the most dire need of graph-based security techniques?
- How dynamic are attack surfaces and paths?
- What do 880m triplets* reveal about attack surfaces and paths?
- What do connectivity and local and global risk exposure reveal about control coverage?
*A triplet is defined as “a unique occurrence of two nodes and one edge.”
Initial findings related to attack paths and the average attack surface
This research into attack surfaces is ongoing, but this preliminary research phase revealed key findings in the following areas:
- The percentage of the attack surface with a first-degree relationship to the public internet
- How the attack path to critical assets differs from the path to non-critical assets
- The difference in attack path variety between critical and non-critical assets
- What asset connectedness implies in terms of control coverage
- Whether local and global risk exposure correlated with asset connectivity
Our research team concluded that although defenders are racking up some big wins, there is still a lot defenders don’t understand about attack surfaces. While security basics like MFA and database encryption can greatly reduce your attack surface, there are attack paths that defenders simply cannot discover without understanding the relationships between their assets. These relationships often cannot be recognized without applying a graph-based model.
Lists vs. graphs: Why it matters
John Lambert, a well-known, distinguished engineer at Microsoft, famously said, “Defenders think in lists. Attackers think in graphs. As long as this is true, attackers win.”
For many security practitioners, this quote represents the first moment they realized the value of using graphs to visualize data. It highlights how their reliance on alerts and logs from tools that spit out spreadsheets doesn’t provide a holistic view of their systems and interconnectedness.
This research intends to clarify when a graph-based versus list-based attack surface analysis is most effective.
By understanding just how connected and complex the average attack surface is, security practitioners can make more intentional decisions about what kind of actions they should take to reduce their organization’s attack surface.
Download the paper
This 15-page paper expands on these topics and presents the early findings from JupiterOne’s ongoing attack surface research. You can download your copy anytime, here.
