Risk Management
Identifying, assessing, and mitigating risks in AI operations
Hero Post
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.
Featured Posts
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
The $127M Algorithm: When Smart AI Goes Wrong
When AI appears to think but actually pattern-matches toward desired outcomes, you get sophisticated-looking failure. This fictional crisis demonstrates real research about AI limitations and how to build better systems.
By Adesh Gairola
Shadow Coding: what, so what, now what?
Shadow coding—developers using unauthorized AI tools or code—is creating significant security and compliance risks. Organizations need balanced governance that enables innovation while maintaining security.
