Attack

Aether AI attacks your own attack surface the way a real adversary would, so you find out what is genuinely exploitable before someone else does. The offensive half of the platform is not a scanner that flags theoretical weaknesses. It emulates an attacker, works from the intelligence an attacker already holds, and tells you plainly which findings a commodity attacker could reach and which take a more capable, AI-driven one.

Why an adversary spectrum

Attackers are not all the same, and treating them as one blurs the picture that matters most. Aether AI models the offensive side as a spectrum with two ends.

At one end is the conventional attacker: a commodity adversary using generally-available tooling. Most real intrusions start here, so this is the baseline everyone should be able to withstand.

At the other end is the frontier attacker: advanced and AI-driven, able to chain weaknesses together, work through authentication, and find novel and business-logic flaws that off-the-shelf tooling never surfaces.

Aether AI measures both, and it is always explicit about which is which. A finding that a commodity attacker could exploit today is a different conversation from one that needs a frontier adversary, and the platform never collapses the two into a single vague "risk".

The three offensive layers

The offensive side comes together as three layers that build on each other.

Continuous validation (conventional)

The Conventional Attack Surface engine is the commodity baseline. It continuously and non-destructively validates what a commodity adversary could exploit using generally-available tooling. It checks, it does not exploit: no brute force, no state change, no data exfiltration. Findings split into two bands, directly exploitable and weaknesses that ease an attack, and a finding auto-resolves once re-validation no longer observes it. This layer runs on assets set to Monitor Plus.

Autonomous AI pentest (frontier)

The Autonomous AI Pentest is the frontier engine. Autonomous offensive agents chain weaknesses, work through authentication, and find novel and business-logic flaws that commodity tooling cannot reach. This is where AI reasoning is the differentiator. It is far heavier and slower than continuous validation, and it runs only against explicitly authorised scope.

Intelligence that arms both

Attackers succeed largely by reusing and sharing information: leaked credentials, breach data, infostealer logs, known-exploited vulnerabilities. Aether AI's shared intelligence feeds enrich both the defensive side, which alerts you to that exposure, and the offensive agents, so validation reflects what an attacker already holds and not only technical weaknesses. Threat Radar surfaces this intelligence correlated to your surface as verdict cards.

What you get out of it

Every offensive finding lands in one place. The Risk Inbox is a single queue across ASM and pentest, so a directly exploitable conventional finding and a frontier pentest result sit side by side, filterable by severity, source, and when they were updated. Source labels make the origin obvious, including "Aether ASM", "Plugin (Conventional Attack Surface)", and "Plugin (Infostealer)".

Findings feed the asset risk score, a 0 to 100 value computed over an asset's confirmed, live findings and shared across ASM and pentest. It is explainable and drops back to nothing once findings are resolved, so the score tracks real, current exploitability rather than a static tally.

Because the offensive engines run against your production surface, safety is not optional. Continuous validation is non-destructive by design, and the frontier pentest runs only against explicitly authorised scope. The safety model covers how Aether AI keeps offensive work bounded.

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