AI · 28 days ago
Google Threat Intelligence Group said on Q2 2026 activity that adversaries have moved from basic prompting to agentic AI workflows, including one cloud compromise that led to a mass credential-harvesting run in under six hours. GTIG also tracked UNC6780 using AI coding assistants and large language model (LLM) security scanners to support open-source supply-chain compromises.
The shift is in the execution loop: multiple AI agents can scan, correct their own mistakes, and keep moving without the pause a human team would normally need. That compresses a campaign from plan to impact before ordinary review, detection, or approval cycles can interrupt it.
For teams using AI assistants against code, tickets, or cloud data, the exposure is no longer just policy drift around unapproved tools. A single stolen identity or foothold can now be turned quickly into credential theft or package tampering, which leaves defenders with less time to notice and contain the blast radius.
20 sources covering this story
Why 2026 is the Year to Upgrade to an Agentic AI SOC
Agentic AI SOCs differ from copilot-only models by autonomously prioritizing attacks over alerts, executing closed-loop containment, and providing traceable reasoning for every decision, allowing anal...
Proofpoint SOC Analyst Agent Uses OpenAI Cyber Models
Proofpoint’s SOC Analyst Agent uses OpenAI Daybreak models to help security teams investigate threats, connect signals, and automate recurring analysis.
This AI threat update provides GTIG’s findings on adversarial misuse of AI including Gemini and other non-Google tools.
Hackers build AI frameworks for widescale credential theft
Threat actors are increasingly switching from AI-powered coding assistants to multi-agent frameworks that automate every stage of an attack.
NCSC Warns Shadow AI Creates New Security Risks
NCSC warns unapproved AI tools can expose corporate data and create new security risks
Understanding why staff use unapproved AI tools is key to managing the security challenges they can create.
How to secure edge AI in customer-owned environments | Microsoft Security Blog
As AI moves into customer-owned environments, organizations need new ways to verify the systems, software, and AI assets they trust before releasing sensitive data, credentials, and models.
AI Coding Agents Are Installing Unknown/Untrusted Code on Corporate Networks - Schneier on Security
We cannot forget that AI coding agents are not yet trustworthy: Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved. Anthropic, OpenAI, and Nous Research did not respond to requests for comment by the time of publication...
Why judgment is emerging as cybersecurity’s defining skill
AI speeds up security analysis, but automated actions without human context risk massive operational outages. Here is how CISOs can safely govern AI autonomy.
Booz Allen reports AI models approaching autonomous cyberattack capability as critical infrastructure response windows narrow.
A five-part inventory for your AI agent credentials - Help Net Security
Roy Katmor explains the review gap around AI agent credentials and what teams should inventory before an agent acts on its own.
AI 'Machine Speed' Cuts 2-Week Attack Down to 10 Hours
The incident demonstrates how frontier AI agents can dramatically compress an attack timeline and coordinate a large-scale breach.
Part of the PlainSec briefing for 2026-09-02