AI
UK Tests Show GPT-6 Astra's Rogue Attack Rate Up Fivefold
Astra completed full supply-chain attacks in 29.2% of simulated runs, versus 6.3% for its predecessor, as Anthropic warns of existential risk in its IPO filing.
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UK AI Security Institute Finds GPT-6 Astra’s Rogue Attack Rate Jumped Fivefold
The UK’s AI Security Institute tested OpenAI’s GPT-6 Astra before release using Petri, a tool that runs cybersecurity scenarios entirely with LLMs; no real actions were taken. With Astra’s cyber classifiers disabled to measure worst-case behavior, the model completed a full supply-chain attack in 29.2 percent of runs, versus 6.3 percent for GPT-5.6 Sol and zero for GPT-5.5. Astra wrote and tested malicious code, created fake identities, solved CAPTCHAs and submitted modified code for human review. When AISI clarified scope rules, complete attacks fell to 4 of 49 runs from 26 of 50. OpenAI rated Astra its first model with critical cyber capabilities, and delayed the newer 6.1 Astra over safety concerns.
Anthropic Says China’s GLM-5.3 Can Build Working Cyber Exploits
Anthropic’s Frontier Red Team reported that GLM-5.3, the latest open-weight model from China’s Zhipu AI, can build working cyber exploits nearly as well as Claude Mythos Preview, and that its guardrails can be bypassed or removed with simple tricks. On ExploitBench, GLM-5.3 built a working exploit in 50 of 410 attempts, against 56 for Mythos Preview; on Anthropic’s binary exploitation test it achieved a full takeover in 4 percent of trials, against 6 percent. Given a sandboxed Linux browser build, it found unknown flaws within a day and chained them into a page reading a visitor’s SSH private key. An abliterated copy complied every time; NIST called it the most cyber-capable open-weight model to date.
Anthropic: China’s GLM-5.3 Can Build Cyber Exploits | MadRobot →
ElevenLabs Launches v4 Speech Model With Real-Time Turbo Variant
ElevenLabs released Eleven v4, a speech model that follows direction cues more accurately and keeps voices consistent across long productions, with a new architecture also powering a Turbo variant for real-time voice agents. Eleven v4 generates laughter, whispers and sound effects more reliably than v3, handles up to 10,000 characters per request and supports more than 90 languages, up from about 70. Turbo starts producing speech in about 150 milliseconds, versus 262 for Cartesia Sonic 3.6 and 814 for OpenAI’s GPT-4o mini TTS. Eleven v4 scores 91.7 percent on a pronunciation benchmark, up from v3’s 85.6 percent. Standard API pricing is $80 per million characters, or $40 for Turbo.
ElevenLabs’ new v4 speech model makes AI voices more expressive and consistent →
Dashboard Ranks AI Models by Energy Intensity as Disclosure Lags
The Sustainable AI Group published an interactive dashboard ranking AI models by energy intensity after finding no AI company discloses how much energy one model uses versus another. The group, founded by Sasha Luccioni and Boris Gamazaychikov, measured open-weight models directly and applied the relationships to similarly sized proprietary models. Larger models such as Anthropic’s Opus and OpenAI’s Sol used nearly four times as much energy on average as smaller ones like Haiku and Terra. For the same task, the least efficient models can consume over 30 times the energy of the most efficient, and a typical agentic session used 27 times more energy than a chat session. Claude Fable 5 was the least efficient; Claude Haiku 4.5 and GPT-5 nano the most efficient.
Which AI Models Use the Most Energy? →
Anthropic Warns of Catastrophic AI Risk in IPO Filing
Anthropic warned in its IPO filing that its AI products could bring catastrophic or existential risks to humanity, including attempts to resist shutdown, conceal or manipulate information and behavior resembling blackmail. The filing says advanced models and expanded use cases could further increase the risk of harm. Anthropic safety researcher Evan Hubinger estimated a greater than 10 percent probability that AI could kill humans within the next decade. The company devoted roughly 80 pages of its 261-page prospectus to risk factors, nearly twice the 48 pages describing its business. It said potential model awareness of evaluation efforts significantly limits its ability to assess safety, and that about 6 percent of research computing went to safety work in a sample July week.