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Damian K. — Penetration Tester / Offensive Security Engineer
🛡️ Everyone talks about AI detecting vulnerabilities.
The real shift begins when AI understands runtime attack chains.
Recently, Anthropic previewed Mythos — an AI system capable of not only identifying vulnerabilities, but chaining low-level primitives into working Proof-of-Concept exploits.
That is a major milestone for offensive security automation.
But it also highlights something important:
The future likely won’t belong to “AI scanners”.
It will belong to runtime offensive intelligence systems.
Most platforms still operate like this:
Target → Scan → Vulnerability → Report
Modern attack surfaces no longer behave that way.
Real-world exploitation is increasingly about:
• identity propagation
• runtime telemetry
• session continuity
• topology correlation
• temporal drift
• chained authorization failures
• evidence lineage
• adaptive continuation paths
This is one of the core ideas behind RedNode.
Not just detecting a vulnerability.
But understanding:
“How does this weakness evolve through the runtime ecosystem?”
For example:
JWT → IDOR → Enumeration → Cross-table Pivot → Full Data Correlation
Individually:
low/medium findings.
Combined:
critical runtime exposure.
That is where offensive cognition becomes more important than isolated CVEs.
The long-term direction is not:
“AI that writes exploits.”
The long-term direction is:
runtime-aware offensive intelligence systems capable of reasoning about attack topology, execution flow, telemetry, governance, and evolving target behavior.
We are entering an era where cybersecurity tools stop behaving like scanners…
and start behaving more like operational intelligence systems.
#CyberSecurity #AI #RedTeam #OffensiveSecurity #RuntimeSecurity #AppSec #BugBounty #RedNode #CyberThreatIntelligence #SecurityResearch
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Topics: #bugbounty, #cyberthreatintelligence, #offensivesecurity, #ai, #rednode, #appsec, #securityresearch, #redteam, #cybersecurity, #runtimesecurity