Open-Weight AI Models Now Match Frontier Cyber Skill From Four Months Prior, AISI Finds

Techtimes
Open-weight AI models are catching up to closed‑model cyber capabilities, narrowing the gap to four to seven months and lowering attack costs to under two dollars.

Summary

The UK’s AI Security Institute (AISI) released its first public measurement of the open‑weight cyber capability gap, finding that freely downloadable AI models now trail the top closed systems by only four to seven months on offensive cybersecurity tasks. This represents a significant compression from the six to ten‑month gap measured through most of 2025, and it has immediate operational implications: organizations with networked infrastructure face a shrinking window before near‑frontier AI‑powered cyberattacks become accessible to anyone with modest compute resources. AISI’s July 2026 report evaluated two Chinese open‑weight models—GLM‑5.2 from Z.ai and DeepSeek V4‑Pro—using a suite of 70 narrow cyber tasks and a multi‑step autonomous attack range called "The Last Ones." GLM‑5.2 matched Anthropic’s Opus 4.6 on narrow tasks, placing it roughly four months behind the frontier, while DeepSeek V4‑Pro tracked Opus 4.5, about five months behind. On the autonomous range, GLM‑5.2 reached step 7, a gap of up to seven months, whereas DeepSeek V4‑Pro performed below even sub‑frontier models. The report also highlighted that open‑weight models can be run for a fraction of the cost of closed models: a full 100‑million‑token autonomous attack costs approximately $1.19 on DeepSeek V4‑Pro and $46 on GLM‑5.2, compared to roughly $85 for closed‑model counterparts. Narrow‑task costs were similarly lower, with DeepSeek V4‑Pro at $0.28 per task versus $12.50 for Opus 4.5. AISI noted that open‑weight models lack the safety safeguards of closed APIs; refusal training can be removed, and no central authority can revoke access once weights are distributed. The report also discussed regulatory asymmetries: closed‑model governance can impose export controls and recalls, whereas open‑weight models, already globally distributed, cannot be recalled. AISI identified Kimi K3 from Moonshot AI as the next open‑weight model, slated for release in late July 2026, with 2.8 trillion parameters and a one‑million‑token context window. The findings underscore the urgency for organizations to invest in AI‑enhanced defensive tools and cybersecurity fundamentals, as the preparation window narrows and the cost of autonomous attacks drops to single‑digit dollars.

(Source:Techtimes)

Siasat.com

In search of a flat in Bengaluru, woman lands a job offer

Asianet Newsable

"This Can Only Happen in Bengaluru": Woman's Flat Hunt Turns Into Unexpected Job Offer, Post Goes Viral

Complete Ai Training

LexisNexis opens customer innovation lab to build legal AI with clients

Complete Ai Training

Anthropic legal team leans on AI for contract review and workflow automation

Aitechtrend

10 Best Contract Analytics Tools 2026 | AITechTrend

Pr Sync

Knovos to Showcase Latest Platform Innovations in Data Governance, AI-Assisted Search, and Workflow Automation at ILTACON 2026

Et Now

Bengaluru woman goes flat hunting, ends up meeting legal AI startup founders and gets a job offer after asking questions about their product

Newsbreak

📣 Several High-Paying Sales & Marketing Roles in Palo Alto

Newsbreak

⚖️ Wichita legal & compliance roles with multiple $100K+ options

Newsbreak

💻 Salt Lake City IT Hiring: Multiple Roles From $45/hr to $297K+

Blockchain News

Harvey Launches Tenet, Open-Weight Legal AI Model

Aba Journal

Why the next competitive advantage in the AI era is partnership, not just technology

South China Morning Post

OpenAI-backed legal tech firm pivots to Chinese Kimi K3 open-weight model

News 18

Individual Goes Flat Hunting In Bengaluru, Lands Job Offer After Chatting With Startup Founders

The Nassau Guardian

Before we remove the land, let us first consider what we could build upon it