OpenAI launches GPT-5.6-Cyber with reduced refusals, 95% completion on advanced cybersecurity tasks

Earlier today, OpenAI launched GPT-5.6-Cyber, a specialized model designed to perform advanced vulnerability research and exploit development for approved defenders - including categories of work that its general-purpose models will often refuse. GPT-5.6-Cyber is a fine-tuned version of OpenAI's most advanced general model, GPT-5.6 Sol, unveiled back in June, but trained specifically to improve performance on advanced cybersecurity tasks, including finding zero-day vulnerabilities and developing exploit chains. Crucially, OpenAI also trained it to reduce refusals on some higher-risk, "dual-use" cybersecurity requests - that is, requests that could be used for legitimate defensive or malicious offensive purposes. Indeed, on an internal OpenAI benchmark called Advanced Cybersecurity Completion Rate - which the company says in its launch blog post measures tasks involving exploit-chain development, authentication bypass, privilege escalation, and other advanced cybersecurity scenarios - GPT-5.6-Cyber completed 95% compared to just 57.3% from its immediate predecessor model GPT-5.5-Cyber, and just 1.5% with the normal GPT-5.6 Sol model and all its safeguards applied. OpenAI researcher Eric Wallace posted on X, describing GPT-5.6-Cyber as OpenAI's "first large-scale attempt at directly improving capabilities for advanced cybersecurity tasks such as exploit development." Pricing and availability Unfortunately for enterprises, GPT-5.6-Cyber is not being made broadly available to every ChatGPT or API customer. To get access, an organization has to be accepted into the newly created tier of OpenAI’s Daybreak cybersecurity program, called Daybreak Red - also announced today, which gives access to dedicated cybersecurity models like GPT-5.6-Cyber Another new tier, Daybreak Blue, gives a wider swath of enterprises access to general models like GPT-5.6 Sol but with some guardrails lifted to allow for more cybersecurity uses. OpenAI’s documents list pricing for GPT-5.6-Cyber at $12.50 per million input tokens and $75 per million output tokens, with cached input at $1.25 per million tokens. That makes it more expensive than GPT-5.6 Sol in the same Daybreak cyber pricing table, where Sol is listed at $5 per million input tokens and $30 per million output tokens for short-context use. OpenAI does not list long-context pricing for GPT-5.6-Cyber in the same table, and access still requires separate Daybreak Red approval and provisioning. Red vs. Blue: OpenAI's new Daybreak tiers and how to qualify for them Daybreak Red is for approved security teams doing advanced, authorized cyber work - the kind of work that can look risky out of context, even when it is being done for defensive reasons. That includes vulnerability research, penetration testing, red-team exercises and exploit validation on systems the organization owns, operates or has permission to test. In other words, OpenAI is saying GPT-5.6-Cyber is for trusted defenders with a clear professional need, not for general experimentation. Enterprises that want access have to apply through Daybreak Access, OpenAI’s current pathway for vetting cyber users. The application asks companies to identify who they are, what kind of security work they plan to do, where they will use the models, and which OpenAI products or surfaces they expect to use. Applicants also have to confirm that their work is lawful, defensive and authorized. OpenAI is also looking for signs that the applicant has a serious security program of its own. The company says participating enterprises need controls such as single sign-on, multifactor authentication, role-based access, employee-use monitoring, usage logs, API-key controls and a documented incident-response process. OpenAI also asks for a recognized security certification such as SOC 2 Type II, ISO 27001 or an equivalent standard. Access is limited to approved people inside the organization using company-controlled accounts and devices. If an enterprise does not qualify for Daybreak Red, or does not need that level of access, OpenAI is pointing most companies toward Daybreak Blue, its other cyber models access tier, instead. Blue is the broader tier for approved defenders. It does not provide GPT-5.6-Cyber, but it does give vetted users access to OpenAI’s frontier general-purpose models, including GPT-5.6 Sol, with safeguards adjusted for legitimate defensive work. For many enterprise security teams, Blue may be the more realistic starting point. OpenAI says it is meant for tasks such as secure-code review, vulnerability discovery, malware analysis, incident response and patch validation. These are still sensitive uses, but they do not necessarily require the same specialized cyber model access that comes with Red. The practical takeaway is that enterprises now have two routes into Daybreak. Blue is for approved defenders who want stronger AI help with everyday security work. Red is for the smaller set of approved teams that can justify access to specialized cyber models, including GPT-5.6-Cyber. Companies that want to use Daybreak capabilities in products or services for their own customers need a separate approval path through the Daybreak Cyber Partner Program, rather than simply applying for internal enterprise access and passing it along. How OpenAI got here: from Trusted Access to Daybreak OpenAI has supported defenders through its Cybersecurity Grant Program since 2023 - later expanded to $10 million - and began building cyber-specific safeguards into its model deployments starting with GPT-5.2. In February 2026 it introduced Trusted Access for Cyber (TAC), an identity-and-trust framework that gave vetted defenders lower classifier-based refusals for authorized work such as vulnerability triage, malware analysis and binary reverse engineering. From there, the cadence accelerated. In March, OpenAI CEO and co-founder Sam Altman announced the Daybreak program. In April, OpenAI scaled TAC and released GPT-5.4-Cyber, a version of GPT-5.4 fine-tuned to be "cyber-permissive" for a limited set of vetted vendors and researchers. In May, it followed with GPT-5.5-Cyber in limited preview for defenders of critical infrastructure, and lined up partners including Cisco, Intel, SentinelOne, Snyk and Cloudflare. Notably, OpenAI said at the time that GPT-5.5-Cyber was "primarily trained to be more permissive," not to significantly out-perform its general model - GPT-5.5-Cyber actually scored worse than GPT-5.5 on some evaluations. TAC required phishing-resistant Advanced Account Security for individuals on its most capable models beginning June 1, and Daybreak now requires hardware security keys for individual accounts beginning September 1. OpenAI says GPT-5.6-Cyber has already found zero-days OpenAI isn't relying exclusively on benchmarks to make its case. The company says its researchers used GPT-5.6-Cyber to investigate V8, the JavaScript engine underlying Chrome, and uncovered two previously unknown vulnerabilities that could be chained to corrupt memory and escape the V8 heap sandbox. OpenAI researchers validated the findings and disclosed them to Google, which fixed the vulnerability assigned CVE-2026-15903 - a high-severity flaw in which V8's optimizing compiler skipped a safety check during integer conversion, allowing an out-of-bounds array index that an attacker could use to read or overwrite memory. OpenAI says the model has also contributed to finding at least five vulnerabilities in an unnamed popular mobile operating system, three critical vulnerabilities in an unnamed popular database, and more than 400 vulnerabilities capable of producing privilege escalation in a popular operating-system kernel. Those disclosures are still being coordinated, according to OpenAI. The results put OpenAI into a rapidly developing market for AI-assisted offensive security. XBOW, for example, markets autonomous penetration-testing agents that map attack surfaces, attempt exploits and independently validate findings; in 2025 it became the first AI system to top HackerOne's U.S. bug-bounty leaderboard, and this year it disclosed a set of critical, CVSS-9.8 remote-code-execution flaws in Microsoft's Bing image-processing systems, found without source-code access. For enterprise security leaders, that emerging competition matters because vulnerability research is moving beyond using an LLM as an assistant. Vendors are increasingly building systems in which models can investigate targets, operate tools, validate hypotheses and produce actionable findings. Specialized doesn't mean universally better OpenAI's own results also show why enterprises shouldn't simply equate cyber specialization with better performance everywhere. GPT-5.6-Cyber outperformed GPT-5.6 Sol and GPT-5.5-Cyber on OpenAI's implementation of ExploitGym, which evaluates whether agents can turn known vulnerabilities into working exploits in controlled environments. It also beat Sol on an internal zero-day evaluation. But GPT-5.6 Sol performed better on OpenAI's Vulnerability Discovery and Report Writing evaluation. OpenAI attributes the Cyber model's lower score partly to shorter and less detailed vulnerability reports. Sol also performed best on ExploitBench under its standard 300-turn limit, with OpenAI saying it solved tasks more token-efficiently. Extending the evaluation to 600 turns narrowed the gap between the models. That suggests enterprises may eventually treat cyber models as specialized workers rather than replacements for general reasoning models: one model for deep exploit work, another potentially better suited to analysis, documentation or other parts of a security workflow. SpecterOps CTO Jared Atkinson said GPT-5.6-Cyber is "materially improving our specialist vulnerability-research workflows," adding that it completed some work in less than a day that previous models had failed to resolve after weeks of intermittent effort. The Hugging Face incident hangs over the launch The permissive