Observed arrival · 2026-10-14
Defending AI Agents: security as statistics
A course in preparation teaches data scientists and ML engineers to build defenses for AI agents and reason about their behavior at scale.
○Open
⊠Login
$Paid
†Ads
✦Pretty
●Pro
◎Niche
◉Human
⚑Risk
ƒJS
- For
- Data scientists, statisticians and ML engineers
- Worth noticing
- One example scales a detector measured at 40 milliseconds per call into an estimate of roughly 23 continuously busy cores at 50 million calls a day.
Field notes
The outline moves from a small tool-calling agent and its failure modes to gateways, detectors, memory provenance, privacy, credentials, policy controls and incident response. A stated constraint is that learners build with general-purpose open tools rather than being taught a commercial or open-source security product. The page also says each module ends with a measurement learners produce and defend; the full course is still in preparation.
Observed signals
Read the marks
Editorial observations of this landing page, not a rating.
○OpenPublic substance visible
$PaidCommerce or pricing visible
✦PrettyNotable craft visible
●ProPolished or operationally mature
One card from the complete issue