Three Findings, or One Attack Path?
Point tools raise a finding for the contractor, a finding for the over-scoped OAuth app, and a finding for the sensitive dataset - and miss that together they’re one exfiltration path. AegisGraph reasons on the graph: it names the toxic combination and floors its risk before any action is allowed.
Illustrative product view
Graph truth before the LLM reasons
AegisGraph compiles a deterministic “graph truth statement” about an action - its actor, its scopes, the data classes it touches, its blast radius - before any language model reasons about it. It matches that against ten named toxic-combination patterns (agent runtime breakout, OAuth-to-sensitive-data, data-exfiltration path, and more). A confirmed combination isn’t a soft score - it forces a hard risk floor of 80, so a cross-domain attack path can’t be reasoned away.
Frequently asked questions
What is a toxic combination?
It is a set of individually-benign conditions that together form an attack path - for example a contractor, an over-scoped OAuth app, and access to a sensitive data class. AegisGraph names the combination and scores it as one path, not three findings.
What does the risk floor do?
A confirmed toxic combination forces a hard minimum risk of 80, so a genuine cross-domain attack path can’t be diluted to a low score by a single-signal model.
How is this different from a SIEM?
A single-signal SIEM sees the three findings separately. AegisGraph compiles a graph-truth statement across identity, cloud, SaaS, and data classes and matches named attack-path patterns before deciding.
Does it block attacks?
It decides and exports evidence in simulation mode - a decision fabric your systems consult. It does not itself actuate production containment.
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