~/category/adversarial-ai
Attacks on and with AI — prompt injection, model red teaming, AI-driven offense and defense.
30 articles
The serious attack surface is no longer the chatbot. It is the agent's toolbelt: retrieval, memory, skills, CI pipelines, credentials, and every renderer or proxy trusted to move data. A field analysis of EchoLeak, malicious agent skills, coding-agent compromise, state-scale campaigns, and data poisoning, separating confirmed incidents from research demonstrations, with the containment architecture that actually holds up.
Muse, Amazon Quick, Hermes Agent and OpenClaw all promise to do more than chat. That is roughly where the similarities end. A practical comparison of four very different bets (hosted convenience, governed workplace AI, a self-improving runtime, and a local-first gateway), plus a security lens on each: where the lethal trifecta lives, and how to harden the two you run yourself.
Black Hat and DEF CON land in the same week in Las Vegas every year, and every year one story ends up getting told in the hallways more than the others. Usually it takes a couple of days to sort out which story won. This year, it took about a morning.
A balanced cybersecurity review of Moonshot's Kimi K3 and the multi-agent K3 Swarm. Not "is it smart" but the question a red team actually asks: does an open, self-hostable, agentic model make you more effective on an engagement, and what does it give you that Claude and GPT cannot? Data that stays in the room, no vendor holding your engagement hostage, cost at scale, and a swarm that fits the work, weighed honestly against where the closed frontier models still win.
AI automation quietly became critical infrastructure that security never signed off on. A deep look at where automation actually is in 2026, the real differences between Zapier, Make, and n8n, when to reach for each, and why every one of them is a beautiful new attack surface: standing credentials, unauthenticated webhooks, shadow automation, and prompt injection into agents that hold tools.
From the PolinRider DPRK supply chain drama to the JadePuffer agentic ransomware debate, the security community is having big conversations this week. Here's the pulse from r/netsec, r/cybersecurity,
AI agents are being weaponized in the wild — from crypto-stealing prompt injections to fully autonomous ransomware. Here's what the AI attack surface looks like in July 2026, and why your security tea
Artificial intelligence is quickly becoming part of everyday business workflows. We use AI to summarize emails, write reports, analyze logs, review documents, generate code, support customers, and automate tasks.That sounds great.It also means we are building systems where one AI may talk to another
Written by Anthony Giandomenicohttps://www.linkedin.com/in/anthonygiandomenico/The Shift: Not New, But Moving FastAgentic AI is not a new concept. At this point, most people in the industry have heard about it, and many have been experimenting with it in different forms. The idea of systems that can
Click here to listen on SoundCloud: https://soundcloud.com/drchaos-podcast/project-glasswing-podcastIn this week's episode of the Dr. Chaos Podcast, hosts Anthony Giandomenico (Tony G) and Aamir Lakhani (Dr. Chaos) dive deep into the rapidly evolving landscape of AI in cybersecurity. We are official
1. Model and AI Pipeline SecurityThe first area is what I’d call model and AI pipeline security.This is where a lot of the early focus has been — making sure the model itself, the data feeding it, and the overall pipeline are secure before anything ever gets deployed.These solutions are looking for
Human friendly Until It Isn'tAt first, they sounded perfectly human.Two AI agents exchanging polite, helpful sentences about booking a hotel. Dates. Cities. Room types. Small talk in clean, predictable English. Nothing unusual. Nothing alarming.And then something changed.A subtle handshake. A quiet