GOVERNANCE

Can GPT-6 Cyber solve OpenAI's safety problem?

Amid mounting concern over AI's impact on cybersecurity following OpenAI's breach of HuggingFace, the lab's latest model is a step in ameliorating the issue.

On Thursday, the company announced GPT-6 Cyber, a model that it claims is "far more reliable" at staying within the boundaries that researchers set. OpenAI claims the model is better at finding and patching vulnerabilities, offering a significant improvement over its predecessor. 

OpenAI said the model is already helping secure real-world software, including finding and validating exploits in "security-critical" codebases. For instance, in Linux, the model developed 948 privilege escalation exploits, or exploits in which someone gains higher levels of control than they are granted. Additionally, it identified 81 previously unknown "high-severity" vulnerabilities in Firefox, and is being used by teams at Cisco, Calif and CodeRabbit for vulnerability research and code review. OpenAI said the model is also being used to secure its own systems. 

The company tested the model on ExploitGym, the benchmark for testing whether a model can exploit a specific software vulnerability that was also involved in July's HuggingFace breach. 

• OpenAI said GPT-6 Cyber scores 48.5% on this evaluation, up from 32.1% on the previous generation, GPT-5.6 Cyber. It also outperforms GPT-6 Astra, OpenAI's most advanced model, in this benchmark, which scored 42.4%. 

• It also noted that GPT-6 Cyber avoided exploiting "out-of-scope services" in 99.93% of tests without a deployment prompt, or additional safety instructions that keep a model in bounds, and in 100% of tests with a deployment prompt. 

• OpenAI noted that alignment was a "central focus" of GPT-6 Cyber, utilizing specialized training to help the model stay within specified boundaries. 

• However, the company is also adding additional protections, including monitoring for misalignment and emerging threats, protecting against stolen credentials and blocking high-risk activity involving critical systems. 

The company said it is releasing the model through the API and Codex to select members of Project Daybreak Red, its program designed for more advanced cybersecurity workflows, and that it intends to expand access over time.  

"Our goal is to dramatically expand Daybreak, bringing advanced security research to organizations of every size, independent researchers, and open-source maintainers," the company said in its announcement.

It's clear that OpenAI wants to atone for the HuggingFace incident in July, with this model specifically improving on staying within containment, even going so far as to test using the same benchmarks that were involved in the incident in the first place. And based on its performance, GPT-6 Cyber does represent a step in the right direction. However, the discussion around model containment and cybersecurity goes hand-in-hand with another hot topic: pacing the development of increasingly powerful frontier AI. The reality is that, in order to stop incidents like these from happening, the development of powerful AI needs to be reined in to allow for cybersecurity defenses to catch up, something that AI researchers and experts have been warning about for months. Though OpenAI has said more than once that the window to secure software is rapidly closing, when frontier labs release new models, they are effectively making that window even smaller. While GPT-6 Cyber could immediately give defenders the ammo they need, these kinds of tools may need to be paired with efforts to slow the pace of development. 

TOGETHER WITH GRANOLA

Our favourite AI notepad can now type for you

Our team already uses Granola to take notes in meetings. Now it can do the typing between them, too.

Our favourite use case for Voice Typing so far: AI prompts.

Instead of typing out a long prompt, press a hotkey and basically brain-dump everything you’re thinking. We’ve found it much easier to get all the context, ideas, and details out quickly, which gives the AI more to work with. That greatly improves the results and value you can get from your AI.

Other Voice Typing use cases we’ve found helpful:

• Voice type longer emails and messages

• Fire off Slack replies in quick succession

• Get thoughts or ideas down in notes quickly without stopping to type.

And because Granola already knows the names and jargon from your meetings, it has context for the way you and your team actually talk. Across our team, we haven’t had to correct a single word it’s transcribed yet, despite a few funky accents.

Try Granola Voice Typing, with unlimited words

RESEARCH

AI's real ROI requires reinventing work

Improving productivity may seem like a logical goal of embedding AI into the enterprise, but that simply won't cut it.

While 81% of enterprises report having used AI to speed up decision-making, only 25% report that it has meaningfully transformed the business, according to Deloitte's State of AI in the Enterprise report, which surveyed 3,500 global business leaders. This gap matters because, as Jim Rowan, head of AI at Deloitte, explains, real ROI for enterprises is only possible when meaningful transformation is achieved. 

"The real ROI comes not only from doing existing work faster, but from redesigning work altogether," Rowan told The Deep View. "The report shows that AI is already helping most companies move faster. The next test is whether they can use that momentum to change how they operate, make decisions, and create value." 

However, many of the companies reported that they have failed to implement AI in more meaningful ways than just productivity gains. Deloitte found that, while 60% of the companies surveyed have redesigned jobs around AI, only 15% reported to have redesigned jobs extensively or completely. Furthermore, only 15% report a significant fundamental shift in decision-making authority as a result of AI. 

The Wharton School of the University of Pennsylvania's fourth annual report on the state of AI found similar results regarding this disconnect in tracking real AI ROI: Around 40% of respondents reported measuring AI returns by hours saved. Net-new revenue was the least utilized metric for success, with 27% reporting that they track this. However, the departments tracking returns by productivity are doing better comparatively. 

Despite the drawbacks, the Deloitte report found revenue gains from AI rose to 28%, up from 20% in the January report. Even though this number is encouraging, Rowan said that it is not a guarantee that returns will compound automatically. Rather, it reemphasizes the need to redesign operations around AI. 

"The organizations most likely to scale successful use cases across the enterprise treat AI as a transformation initiative rather than a technology rollout, redesigning workflows, establishing governance structures, and building accountability mechanisms," added Rowan. "Without addressing those challenges, organizations risk reaching a plateau where AI increases activity and spending without producing proportional business value."

The transformation AI is bringing to businesses resembles earlier shifts, like moving to the cloud, installing Wi-Fi, or upgrading employees to laptops. But because AI seems akin to any other software, organizations aren’t taking the precautions they would when handing an employee a new laptop: training them and teaching them how to actually use an unfamiliar technology. Instead, many assume that simply giving employees access to AI is a shortcut to returns. As a result, report after report finds that organizations aren’t unlocking AI’s full potential. This is especially concerning given how much money enterprises are pouring into AI tools and upgrades. If that spending doesn’t start producing a measurable return soon, enterprises may start to pull back on their AI investments, potentially shaking a major pillar of revenue that frontier labs are counting on.

TOGETHER WITH BOX

BoxWorks 2026: Bringing Frontier AI to Business Workflows

AI is changing how we work, and the technology is improving exponentially. But to truly feel the benefits of using AI agents to transform your business, they first need to understand the unique knowledge that lives inside of company content.

BoxWorks 2026 debuted the next generation of enterprise AI innovations designed to harness AI and reimagine business processes, with content and security at the core.

• Box Context Retrieval: Connecting AI agents to crucial company knowledge

• Box Architect: Pair frontier intelligence with enterprise content to reimagine business workflows

• Advanced Threat Detection and Agent Security: Control and govern agent access, actions, and output

Learn more about how Box makes enterprise content more useful at every step, from the first question to the finished work.

CONSUMER

OpenAI's image strategy hinges on virality

For everyone who has ever spent 10 minutes searching for the perfect eye-roll GIF, OpenAI has a solution for you.

On Wednesday, OpenAI launched its next-generation image generation model: Images 2.6. Though the previous generation was already capable of creating realistic images — so realistic that it tricks on average 50% of The Deep View's readers in the "AI or Not" poll at the end of the newsletter every day — this model includes a number of updates, such as quicker use of reference images and creating GIFs from text. 

To create GIFs, users can enter a prompt or image to generate an animated GIF, then customize it by adjusting the speed, editing individual frames, and sharing it The reference image feature seems tailored to marketers, who can insert brand assets, mascots, product visuals, or simple sketches to bring a GIF concept to life—leveraging the potential for social-media virality. 

"Marketers and creators can animate a brand mascot for a campaign, create reactions and memes for social media, or use animated storyboards to explore character movement before video production," said OpenAI in the release. 

The image reference feature lets users save reference images of themselves, pets, and characters to reuse in new creations. Though this seems like an attempt to make its image model more of a mainstay for users in everyday conversations, it also has a practical component for businesses, which can now more easily create new content from brand assets. 

OpenAI also touts that image creation is up to 50% faster than before, and users can refine images with greater precision. Developers also have the option to choose from GPT‑Image‑2.6 Flare and Sunburst, with OpenAI describing the differences as: 

• With quality set to low, Flare can generate images in as little as six seconds.

• GPT‑Image‑2.6 Sunburst is aimed at higher-quality image generation.

• Sunburst also has greater image consistency across edits when quality is set to medium or high.

This release builds on OpenAI's success with image generation, with a billion images per week across ChatGPT, Codex, and the API, or more than half a billion images created per day. In addition to the API, Images 2.6  is also available in ChatGPT and Codex. Ultimately, it's a bet that people will go beyond entertainment and find real productivity use cases. 

"People are using it almost in a productivity-like fashion to create visual diagrams of what they would like to see," said Adam Fry, Consumer Product Lead for ChatGPT at a media event earlier this week. "And I think as it comes down even further, the number of images that people are creating and the number of use cases is going to grow a lot."

It is interesting to see OpenAI double down on image generation, since it is clearly aimed at the general public as well as working professionals. However, with an impending IPO, it would have been reasonable for OpenAI to take a page out of Anthropic's book and double down on enterprise use cases. Still, with image generation, it is catering to one of the most entertaining consumer use cases — despite it being so compute-heavy. My bet is that OpenAI relies on virality because, realistically, every time it launches another advanced image-generation tool, something goes viral. Racking up these moments of virality, OpenAI can try to make ChatGPT Images as synonymous with image generation as ChatGPT already is with the term "chatbot." That level of brand awareness on its own is something you can't really put a price on. 

LINKS

• OpenAI pledges transparency on data center community impacts

• Anthropic CEO Dario Amodei profiled on evolving AI philosophy

• Tech stocks tumble following US midterm election results

• ElevenLabs users can publish AI-generated music directly to SoundCloud

• OpenAI president Greg Brockman says Q1 and Q2 were 'pretty rough'

• METR accuses Anthropic of redacting information from its public reports

• Claude Personal Finance: Connect your accounts to Claude and ask about your money

• Ripple-65B: Ricursive Intelligence's 65B dense LLM pretrained from scratch, in preview

• SWE-2 Flash: Cognition's new fast & efficient coding model

• Moonshot Kimi K3.1 Pro: open weights released

• Notion: ChatGPT, Claude, Muse, and Bot can save what they learn to the same memory and use the same skills in Notion

• Tenex: Applied AI, Engineer & Creator

• AUI: AI Agent Builder

• IBM: Applied AI Specialist-Application Operations

• Edra: AI Research Engineer (New York)

GAMES

POLL RESULTS

Do you generally trust that the outputs of the AI models you use are accurate?

Yes(49%)
No (37%)
Other (14%)