
S7, E265 - Don’t Trust, Verify: Even Your Update Button Might Be Lying
Autonomy sounds like progress until the system turns your choices against you. We dive into how AI agents change the risk equation, why “don’t trust, verify” now beats “trust but verify,” and what to do when the update button itself becomes the attack vector.
We start with the Ivy League leak tied to Harvard and UPenn, where attackers exposed admissions hold notes that map influence rather than credit cards. That context turns routine records into leverage for extortion, social pressure, and geopolitical targeting. From there, we trace the surge of agentic AI in the workplace as employees paste code, legal docs, and sensitive files into chat interfaces. The real accelerant is MCP, the model context protocol that standardizes connections across Google Drive, Slack, databases, and more. Like USB for AI, MCP makes integration simple and powerful, but a single prompt injection can pivot across everything the agent can reach.
Security gets messier with supply chain compromise. A China‑nexus campaign allegedly hijacked the Notepad++ update mechanism, handing a bespoke backdoor to developers who did the right thing. We unpack how to keep patching while reducing risk: signed updates, independent checksum checks, tight egress policies for updaters, and strong monitoring around update flows. On the policy front, Rhode Island’s vendor transparency rule forces companies to name who buys data. It is a nutrition label for privacy, and it lets users and watchdogs finally connect the dots between friendly interfaces and aggressive brokers.
We close with concrete defenses that raise the floor. Move high‑value accounts to FIDO2 hardware keys or platform passkeys to block phishing at the protocol level. Scope agent permissions narrowly, isolate MCP connectors by function, and require explicit approvals for sensitive actions. Log everything an agent touches and review those trails. Autonomy should be earned, minimal, and observable. If AI is going to act on your behalf, it must prove itself at every step.
If this conversation helps you think differently about agents, influence mapping, and how to lock down your stack, subscribe, share with a teammate, and leave a quick review telling us the one control you plan to implement this week.
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