Shared intelligence, both sides

Attackers rarely start from a blank page. They succeed by reusing and sharing information: leaked credentials, breach data, infostealer logs, and known-exploited vulnerabilities that are already circulating. A commodity adversary can buy or download most of it before they touch your surface. Aether AI takes that same dynamic and turns it around, feeding its threat intelligence into both continuous defence and its offensive agents, so validation reflects what an attacker already holds and not only the technical weaknesses on the wire.

Why it matters

Most security tooling looks at your surface in isolation. It scans a host, fingerprints a service, and reports what is technically present. That misses the way real attacks actually begin, which is with information the adversary already has. A valid credential from an infostealer log defeats a login without touching a single vulnerability scanner. A known-exploited CVE gets weaponised the day it lands in a public catalogue.

If your view of exposure ignores that circulating intelligence, your picture of risk is systematically optimistic. Aether AI closes that gap by treating shared attacker information as a first-class input on both sides of the platform.

Both sides of the same feed

Aether AI's threat intelligence lives in Threat Radar, a set of continuous plugins correlated to your attack surface. Each plugin produces a verdict card. The plugins include the Infostealer Monitor (compromised credentials pulled from infostealer and stealer-log feeds) and CISA KEV Watch (known-exploited vulnerabilities), alongside breach, ransomware, dark-web, and supply-chain monitors.

These feeds are deliberately two-way.

• On the defence side they surface exposure as it appears, alert on it, and land it in your Risk Inbox as a finding you can act on. A plugin finding carries a source label such as "Plugin (Infostealer)" so it is clear where it came from.
• On the offence side the same intelligence enriches the picture the offensive agents work from, so their validation reflects circulating attacker knowledge rather than starting cold against a bare host.

The result is a single body of intelligence doing double duty. Nothing has to be discovered twice, and the defensive and offensive views of a given asset stay consistent.

From intelligence to validation

The value of shared intelligence shows up when it changes what gets validated. A leaked credential or a known-exploited vulnerability is not just an alert to file. It reframes the surface: an asset that looked ordinary is now one an attacker has a head start on. That context flows into how Aether AI validates exposure, from the Conventional Attack Surface checks that a commodity adversary would run through to the frontier Autonomous AI Pentest that chains weaknesses and works through authentication.

Because the intelligence is correlated to specific assets in your surface, findings do not float in the abstract. They point at the asset, the provenance, and the evidence, and they feed the same 0 to 100 risk score used across ASM and pentest.

What you see

Shared intelligence is not a separate console. It arrives where the rest of your findings do.

• Threat Radar cards give each intelligence plugin a plain verdict against your surface.
• The Risk Inbox collects those findings alongside ASM and pentest results, with severity, source, and updated filters, so a compromised credential sits in the same queue as a validated exploit.
• Risk scores reflect confirmed, live findings across every source, and drop back when those findings are resolved.

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