AI Security
Protecting AI systems from threats, vulnerabilities, and adversarial attacks
Hero Post
By Adesh Gairola
Alignment is a Security Problem, Not an Ethics Problem
Misalignment maps onto vulnerability classes security engineers already operate on: backdoors, defense evasion, privilege escalation, exfiltration. Calling it ethics keeps it off security teams' desks. Reframing it as security decides who owns the work, which budget pays, and which playbook applies.
Featured Posts
By Adesh Gairola
Claude 4.7: Five Layers Blocking Cyber Attacks Before and After
Claude 4.7 doesn't rely on one safety mechanism. It stacks a rulebook, trained refusals, differential capability reduction, two runtime probes, and a live feedback loop. Understanding which layer blocks what matters if you're building on the API.
By Adesh Gairola
BodySnatcher and the Missing Identity Layer
BodySnatcher (CVE-2025-12420) showed how AI agents with aggregated permissions can compromise entire platforms in seconds. Traditional security controls designed for humans don't work at machine speed. Organizations need threat modeling and runtime controls for all three layers: API auth, identity binding, and agent execution.
By Adesh Gairola
Three Regulatory Philosophies, One Global AI Market
The EU (9/10 risk), US (5/10), and Australia (6/10) take vastly different approaches to AI regulation. Build for EU standards globally—the Brussels Effect means you'll need them anyway.
