 Protecting Our Systems with Intelligence |
How Block builds AI protectors that shift left, manage context, and continuously evolve to keep systems aligned with their world model |
| Safeguarding VS Code against prompt injections |
When a chat conversation is poisoned by indirect prompt injection, it can result in the exposure of GitHub tokens, confidential files, or even the execution of arbitrary code without the user's explicit consent |
| Threat modeling agentic AI: a scenario-driven approach |
A practical workflow for threat modeling agentic AI systems: use a five-zone navigation lens to trace attack paths, formalize them as attack trees, and map to OWASP's threat taxonomy and playbooks |
| Marco Lancini My Claude Code Setup (2026 Edition) |
A walkthrough of my Claude Code setup across a multi-project monorepo: global settings, safety guardrails, a context/plan/code workflow, subagents and plugins, and the StarCraft-themed customisations that make the terminal feel like mine |
| Marco Lancini Automating Security Operations with AI: Triaging Renovate PR |
A Claude Code Routine that triages every Renovate PR by risk, flags dead deps, and catches deprecated framework configs before I touch the diff |
| Three Ways to Give an AI Agent an Identity |
This post compares three AI agent identity models: acting as the user (simple but single-player), service account tokens (common in production but insecure), and SPIFFE-based workload identity (best but costly to implement) |
| Solving the Identity Crisis for AI Agents |
Uber extended its Zero Trust architecture to assign SPIRE-backed cryptographic identities to AI agents, issuing short-lived, single-hop JWTs via a Security Token Service. Full actor chains (user to agent to tool) propagate across multi-agent MCP calls, enabling end-to-end auditability with sub-40ms P99 token exchange latency. |
| Build your own vulnerability harness |
Cloudflare details a model-agnostic, multi-stage vulnerability discovery harness and triage system covering 128+ repos. It uses separate models for discovery vs. validation, adversarial agents, SQLite-backed persistence, cross-repo dependency tracing, and automated patching with mandatory human sign-off. |
| Zero Trust for AI Agents |
Anthropic eBook applying Zero Trust principles to enterprise autonomous AI agents, covering threat taxonomy (prompt injection, tool/MCP hijacking, memory poisoning, supply chain risks), tiered controls (Foundation/Enterprise/Advanced) for identity, least-privilege, observability, and AI-accelerated defensive operations. |
| How we contain Claude across products |
Anthropic details agent containment across claude.ai (ephemeral gVisor containers), Claude Code (OS-level sandboxes with approval fatigue mitigations), and Claude Cowork (local VMs) |