An exposure graph is a model of your environment that maps how assets, identities, vulnerabilities and network paths connect, so you can see the routes an attacker would take. A traditional asset inventory lists what you have. An exposure graph shows how those pieces lead to each other.

Traditional relational databases fall short when modeling the complex, interconnected nature of cybersecurity threats. Here's why Agent Bounty is built on a graph database, Neo4j, and how graph relationships surface insights that flat tables can't.

Why graphs for security?

Cyber attacks are inherently relational. An attacker rarely exploits a single vulnerability in isolation. They chain together misconfigurations, credential leaks, lateral movement paths and privilege escalations into an attack path. Modeling those relationships in a relational database requires dozens of join tables and increasingly brittle queries. In a graph database, the relationships are the data model.

Bottom line: attackers think in paths, and a graph is the data structure that stores paths natively.

How Agent Bounty uses the graph

Every asset, identity, vulnerability and event in your environment becomes a node. Edges represent the relationships between them: runs_on, has_access_to, exploitable_by, communicates_with. That structure lets agents follow multi-hop paths to answer questions like these:

• Blast radius analysis: If this server is compromised, what sensitive data is reachable within three hops?

• Attack path enumeration: What are all the paths from the public internet to the production database?

• Privilege escalation detection: Which service accounts can transitively reach domain admin?

• Dependency mapping: Which applications depend on this vulnerable library, directly or indirectly?

Bottom line: a graph turns "what do we have" into "what can an attacker reach from here."

From static scans to a living threat model

Most threat models are created once and forgotten. Agent Bounty's graph is updated continuously as agents discover new assets, attack paths and dependencies. The result is a living, breathing threat model that reflects your actual security posture as it changes.

Bottom line: the graph stays current because the agents feeding it never stop running.

Graph-powered prioritization

Not all vulnerabilities are created equal. A critical CVE on an isolated test server is far less urgent than a medium-severity issue on a node three hops from your crown jewels. By combining CVSS scores with reachability and the position of each asset in the graph, Agent Bounty prioritizes remediation by actual exploitability as well as severity.

From there, the same path becomes the proof. When an agent confirms a finding is exploitable, the attack path in the graph shows your team exactly how an attacker would get from the entry point to the asset. The fix is then prepared for your team to approve.

Bottom line: a graph shows which findings sit on a real path to something that matters, so those get fixed first.

Frequently asked questions

What is an exposure graph?

An exposure graph is a connected model of your environment showing how assets, identities, vulnerabilities and network paths relate to each other. It lets security teams see the routes an attacker could take through the environment, beyond what a flat list of assets and findings shows.

Why use a graph database for security?

Attacks are chains of relationships: a misconfiguration leads to a credential, which leads to a privileged account, which leads to sensitive data. Graph databases store those relationships directly, so multi-hop questions like blast radius and attack paths can be answered without complex joins.

What is attack path analysis?

Attack path analysis maps the sequence of steps an attacker could take from an entry point, such as an internet-facing system, to a high-value target. It shows which vulnerabilities and misconfigurations actually connect to something important.

How does an exposure graph help prioritize vulnerabilities?

It adds reachability to severity. A vulnerability on a path to critical data or systems moves up the queue, while one on an isolated asset with no path to anything important moves down, regardless of its CVSS score alone.

See how it works

Try the interactive demo to see how Agent Bounty maps your environment, proves which paths are exploitable, and prepares fixes your team approves.