Where AI adoption opens a door, we close it at runtime.
Two ways to read this page. What changes for the business — cost, deployment, and what your team stops having to do — and the ten technical places AI adoption opens a door.
247 documented incidents735 cited sources118 confirmed intrusionsSearch the Threat Ledger →What it stops.
Three classes of AI-driven attack. Ten places they show up. One decision system that reads intent in every direction of exchange.
Familiar tradecraft executed at a speed and scale human defenders cannot match.
Prompt injection and agentic exploitation — attacks aimed at the AI systems your teams now depend on.
Novel, polymorphic payloads written by a model, carrying no prior signature to match.
Find your problem.
Ten use cases, grouped by the question you arrived with. Each card carries its threat class.
Someone outside is steering our AI
The model, the agent, and the tool calls between them are now the asset under attack. These are the interactions no signature has ever seen, because the payload is language, not code.
Our data is leaving through AI
The assistant is the new egress path. It is authenticated, it is trusted, it is unlogged by the controls you already own — and it will summarise anything you give it.
Shadow AI
Surfaced and governed at the point of interaction.Explore →Covert exfiltration
The flow attributed to the process that made it, and neutralized.Explore →Insider threat mitigation
The AI-mediated slice of insider risk, read for intent and neutralized.Explore →Industrial espionage
Collection recognised as collection — and cut off at the source.Explore →Model integrity & sovereignty
Every model in use surfaced, and the unapproved exchange neutralized.Explore →AI is writing the attack
When a model is the author, there is often no prior artifact to match — a payload novel on arrival, whether it compiles or simply persuades.
What it changes for the business.
Prevention is the product. One claim, seen four ways: cost does not move when AI adoption does.
- Cost0No token spendper-token charges, at any volumeSee the engine →
- EconomicsFlatA flat, predictable TCOcost curve as AI adoption scalesWhy Salience Cyber →
- DeploymentDay 1Fast time to deploymentfrom kickoff to comprehensive protectionSee the platform →
- Operations1Awareness and enforcementone product for both planesTour the console →
See. Comprehend. Neutralize.
Ten use cases, one decision path — and the nine dimensions the engine reads at each step. The beats themselves are explained on the home page; what follows is what each one looks at.
- 01
See
DiscoverVisualizeObserve - 02
Comprehend
Human → AIAI → HumanAI → AI - 03
Neutralize
AI-EnhancedAI-NativeAI-Generated
Not a slide deck. Unedited capture.
Four recordings of the platform working across both planes, each one standing behind the use cases named beside it.
Discover every file moving to and from AIStands behind · Insider threat · Industrial espionage
Track the risky files and processes AI createsStands behind · Covert exfiltration · AI-generated malware
See every use of AI on a machineStands behind · Shadow AI · Model integrity & sovereignty
Real-time traffic analysisStands behind · Agentic exploitation · Covert exfiltration