AI Coding Live News — Real-Time 𝕏/Twitter Updates & Breakthroughs

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OpenAI Launches GPT-6 Cyber: ExploitGym 48.5%, Out-of-Scope Rate Down to 0.07%, Daybreak Red Select Access, Critical Preparedness

On November 5 OpenAI launched GPT-6 Cyber for authorized security research: ExploitGym rose from GPT-5.6 Cyber's 32.1% to 48.5% (about 51% relative), out-of-scope exploitation fell to 0.07% without deployment prompts and 0% with them. The model helped find 81 novel high-severity Firefox bugs and develop exploits for 948 Linux privilege-escalation cases, and OpenAI raised its Preparedness Framework cyber rating from High to Critical. It is initially available via API and Codex to select Daybreak Red customers, with expansion to all Red customers planned.

Key Takeaways

ExploitGym 48.5% vs GPT-5.6 Cyber 32.1% (~51% relative gain; vendor figures)
Scope alignment: 99.93% avoided out-of-scope services without deployment prompts; 100% with them
Real-world: 81 novel high-severity Firefox vulns; 1,724 Linux vulns reproduced, 948 exploits developed
Preparedness raised to Critical; RemoteExploitBench 95% completion (Astra refused 100%)
Select Daybreak Red via API/Codex first; Daybreak Blue alpha for Astra defensive use expanding

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Linked Models & Agents:

⚡ GPT-6 Cyber⚡ GPT-5.6 Cyber ⚡ GPT-6 Astra 🤖 codex 🌐 OpenAI

#OpenAI#GPT-6 Cyber#Daybreak Red#ExploitGym#Cybersecurity#Preparedness Critical

Google DeepMind@GoogleDeepMind·Collected 8d ago

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Google releases Gemini 4 Carbon two weeks after Argon: 59 and first place on the Artificial Analysis Intelligence Index v5, state-of-the-art cybersecurity and long-horizon coding, with early access for cyber defenders in the Fairwind program

Google DeepMind announced Gemini 4 Carbon on Oct 28, calling it its strongest model, just two weeks after Gemini 4 Argon. The official blog says it ranks first on v5.0 of the Artificial Analysis Intelligence Index at 59 and leads three cybersecurity evaluations: 88.2% on SEC-bench Pro for finding vulnerabilities, 54.8% on ExploitGym for exploitation and 71.0% on CWE-bench for patching; it also gains 89 points to rank fourth on WebDev Arena at 1769. Access starts this week for a subset of cyber defenders in the Fairwind program, with developers, businesses and consumers to follow. Introductory pricing matches Argon at $2 per million input tokens and $10 per million output tokens, rising to $4 and $20 afterwards.

Key Takeaways

Positioning: Google calls it its strongest model, aimed at cybersecurity and long-horizon agentic work; internal teams saw it run for days to root-cause and patch subtle bugs across large codebases and low-level systems
Official scores (evaluated without guardrails): 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on Collinear's CWE-bench; 59 and first place on the Artificial Analysis Intelligence Index v5.0; +89 to fourth place on WebDev Arena at 1769
Safety and alignment: successful cheating on Terminal-Bench 4.0 fell to 0.0% with a 0.4% attempt rate, high-severity misalignment alerts in internal live coding dropped by almost 80%, unsupported claims are about half of Argon's, and the Gray Swan indirect prompt injection attack success rate fell from Argon's 0.7% to 0.0%
Internal examples: more than 2x Argon's success rate at generating secure code, and the Chrome team reports more than 10x better high-quality patches than another lab's large frontier model
Rollout: a subset of cyber defenders in the Fairwind program first, alongside the U.S. government's voluntary pre-release testing; no developer API yet; introductory pricing of $2 / $10 per million tokens with cached input 95% off, then $4 / $20

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Linked Models & Agents:

⚡ Gemini 4 Carbon ⚡ Gemini 4 Argon 🌐 Google 🌐 Google DeepMind 🌐 Artificial Analysis

#Google#Gemini#Gemini 4 Carbon#Cybersecurity#long-horizon agents#frontier model