Independent Analysis: AI, SaaS, and Revenue Growth Strategy

The call the White House did not want publicized has been reported anyway. Administration officials, led by National Cyber Director Sean Cairncross, convened Vice President JD Vance and Treasury Secretary Scott Bessent with the chief executives of major banks and technology companies to discuss one thing: what happens when powerful artificial intelligence tools fall into the wrong hands before the country's software infrastructure is hardened against them.

The public version of this threat is vague. The specific version, the one circulating in the rooms where these calls happen, is considerably more alarming.

The day before the Bessent convening, a coalition of senior security practitioners published a draft framework under the banner of the Cloud Security Alliance, the SANS Institute, the OWASP Generative Artificial Intelligence Security Project, and others. The document, titled "The AI Vulnerability Storm: Building a Mythos-ready Security Program," was authored by the former director of the Cybersecurity and Infrastructure Security Agency, the former National Cyber Director, the chief information security officer of Google, and roughly 80 additional contributors. It puts numbers on the capability shift the administration's public statements have left vague, and it gives CISOs a 90-day action agenda the White House briefings have not.

What 181 vs. 2 Actually Means

The CSA/SANS draft provides the benchmark the White House briefings have not. In internal testing at Anthropic, the Mythos model generated 181 working exploits against Firefox under conditions where Claude Opus 4.6 succeeded only twice. Both models were given the same task, the same constraints, and no human guidance. The difference is not incremental. It represents a step change in autonomy and reliability that the authors describe as distinguishing Mythos on both technological and strategic levels.

Three specific capabilities set Mythos apart, according to the draft. First, it generates working exploits without elaborate scaffolding or agent configuration, accomplishing significantly more from a single prompt. Second, it identifies vulnerabilities that require multiple memory corruption flaws chained together into a single exploit path, the kind of complex combination that previously required highly skilled human researchers. Third, it operates at a speed and scale that outpaces any prior capability, finding thousands of critical vulnerabilities across every major operating system and browser during the Project Glasswing disclosure process. The 72% exploit success rate cited in the document is vendor-supplied and unaudited. The 181 vs. 2 benchmark and the success rate originate with Anthropic's own internal testing, reported through a coalition that includes security vendors with commercial stakes in elevated threat perception. Read with that in mind, the numbers are still striking.

The asymmetry this creates is structural, not temporary. Artificial intelligence lowers the cost and skill floor for discovering and exploiting vulnerabilities faster than organizations can patch them. That gap will not close on its own.

The window between discovery and weaponization has collapsed into hours. Attackers gain disproportionate benefit, and current patch cycles were not built for this environment.

CSA/SANS draft, "The AI Vulnerability Storm," April 12, 2026 — paraphrased from source

The Zero Day Clock Is Not a Metaphor

In March, a data visualization called the Zero Day Clock launched to illustrate a trend that the CSA document quantifies: time-to-exploit has fallen to under one day in 2026. A year ago, the window between a vulnerability being discovered and an attacker weaponizing it was measured in weeks. The operational assumption that a patch will arrive before adversaries exploit a disclosed vulnerability is no longer reliable as a baseline.

The evidence trail the CSA draft assembles makes this concrete. In June 2025, an autonomous offensive security system topped the HackerOne platform's United States leaderboard, becoming the first autonomous system to outperform all human hackers on the platform. In August 2025, Google's Big Sleep project found 20 real zero-day vulnerabilities in open source software, autonomously. In November 2025, Anthropic disclosed that a Chinese state-sponsored group had used Claude Code to autonomously run full attack chains, from reconnaissance through data exfiltration, across roughly 30 global targets. By February 2026, Claude Opus 4.6 had reported more than 500 high-severity vulnerabilities in open source software. A separate tool found 12 OpenSSL zero-days, including one with a critical severity score that had gone undetected since 1998. In the same period, an AI-based attack reached administrator-level access in eight minutes.

The Mythos announcement on April 7, 2026, did not create this trend. It accelerated it into boardrooms.

What the Government Is Asking and What It Cannot Supply

The administration's ask to the private sector is coherent: help identify weaknesses in government-adjacent systems before adversaries use artificial intelligence against them. Cairncross is convening federal agencies to map vulnerabilities in critical infrastructure. Sriram Krishnan, a senior policy adviser focused on artificial intelligence and a close confidant of White House adviser David Sacks, is coordinating the private sector response. Federal Reserve Chair Jerome Powell attended one of the meetings. The seriousness of the convening is not in question.

The contradiction is.

Anthropic is simultaneously in a legal dispute with the Trump administration over guardrails surrounding artificial intelligence use by the Pentagon. The company the White House is relying on to harden the nation's software is also the company whose relationship with federal agencies is actively contested in court. That friction has a cost measured in weeks, and the CSA authors are clear about how many weeks are available.

The draft projects that Mythos-class offensive capabilities will reach other frontier models within months, and open-weight models available to anyone within six to twelve months. No one can know that timeline precisely. What is not a projection is that comparable capabilities are being developed now by other labs, and that the defensive advantage Project Glasswing's controlled access provides is shrinking. Every week the legal dispute continues is a week that window narrows.

Banks Are Taking This Seriously. That Is Its Own Signal.

The presence of bank chief executives in the Bessent convening, specifically Goldman Sachs's David Solomon, Bank of America's Brian Moynihan, and Wells Fargo's Charlie Scharf, reflects something that does not happen routinely: financial services leadership treating an artificial intelligence security briefing as board-level material. The impromptu nature of the call, described as unusual by people familiar with it, signals that the threat level being communicated in these sessions is higher than what is being said publicly.

Bank of America analysts reinstated coverage of Anthropic with a buy rating in late March, projecting demand for its services is likely to continue growing through at least 2029. That is a procurement signal dressed as equity research.

The CSA document's contributor list is notable for its breadth. Former Cybersecurity and Infrastructure Security Agency Director Jen Easterly, former National Cyber Director Chris Inglis, Google CISO Heather Adkins, former National Security Agency Cybersecurity Director Rob Joyce, and a former Google Cloud chief information security officer are among the contributing authors, alongside roughly 80 reviewers from financial services, critical infrastructure, and government. The document was produced in roughly two weeks and published the day before the White House convening on the same subject.

Glasswing Cannot Cover What It Needs To

Project Glasswing, the coordinated vulnerability disclosure program Anthropic launched alongside Mythos Preview, gave roughly 50 organizations early model access to scan their own infrastructure and open source dependencies. I covered the structure and implications of that program in prior posts. The CSA document adds a constraint the public framing has minimized: the world's exploitable attack surface is vastly larger than what any curated partner ecosystem can cover.

Most organizations that build or maintain critical software will not have early access to Mythos-class capabilities. The patch and disclosure pipeline must keep pace not only with the vulnerabilities Glasswing partners are finding now, but with the wave of similar capabilities that other models will produce in the months ahead. The authors are explicit that Mythos is the first of what will likely be many waves, not the peak.

"There's a massive capacity crunch that's unlike anything I've seen in the nearly five years I've been running this business."

J.J. Kardwell, chief executive, Vultr — Wall Street Journal, April 12, 2026

The Compute Shortage Is the Timeline

Underneath both the policy debate and the security program is a physical constraint that no executive order resolves. Spot-market prices for Nvidia's graphics processing units in data center clouds have risen sharply across the company's entire product line, according to Ornn, a New York-based data provider that structures financial products around graphics processing unit pricing. Renting one of Nvidia's most-advanced Blackwell-generation chips for one hour now costs $4.08, up 48% from $2.75 just two months prior. Those figures are vendor-supplied by Ornn and unaudited.

CoreWeave, one of the largest publicly traded artificial intelligence cloud companies, raised prices by more than 20% and began requiring smaller customers to commit to multi-year supply contracts. That is the market-wide pricing condition. The reliability problem is separate, and specific to individual providers.

Since mid-February, outages across Anthropic systems have become frequent enough that enterprise clients are switching to other model providers. David Hsu, founder and chief executive of software development platform Retool, said he prefers Anthropic's Opus 4.6 model for enterprise artificial intelligence agent work but recently switched to an OpenAI model for one reason: Anthropic has just been going down all the time. The outages are not necessarily caused by the spot-market pricing crunch; the causes are separate. But both problems are landing on enterprise buyers at the same moment. OpenAI is navigating its own version: it scrapped free compute access for its Sora video-generation product to prioritize coding and enterprise workloads, and its chief financial officer Sarah Friar acknowledged publicly that the company is making difficult trade-offs about what its infrastructure can support. Revenue grew from $6 billion to $11 billion annualized by late March, per vendor-supplied figures that are unaudited, but supply is not growing at the same rate.

Vultr's Kardwell summarized the condition that every enterprise buyer is navigating: data center build times are too long, and the compute available through 2026 is largely already spoken for. That constraint shapes what the White House security program can actually accomplish, independent of how many executive calls it convenes.

What the CISO Community Is Actually Telling You to Do

Start using large language model-based vulnerability discovery tools now. Not next quarter. The CSA document is specific that this capability is mature enough to deploy today, beginning with agent-assisted code review. The gap between offensive and defensive artificial intelligence capability is real, but waiting for defensive tooling to catch up is not the strategy. Using the same class of tools attackers are using, pointed at your own code, is.

Harden the basics, and do not apologize for calling them basics. Segmentation, egress filtering, phishing-resistant multifactor authentication, updated asset inventories. The CSA authors are explicit that most organizations have not fully implemented these controls, which means the attack surface Mythos is already finding its way into is larger than it needs to be. Validate these across your internal systems and across your key third-party providers, because the supply chain will be affected when the Glasswing patch wave hits.

Procurement cycles are the hidden bottleneck. Current approval timelines were not designed for an environment where the window between vulnerability discovery and weaponization has collapsed to hours. The framework recommends aligning security, legal, and engineering ahead of time to fast-track defensive technology onboarding, and updating incident response playbooks for simultaneous incidents. Not sequential. The assumption that incidents arrive one at a time is one of the metrics the document says may no longer hold.

On metrics specifically: the document flags that inaccurate risk baselines, including time-to-patch assumptions and incident frequency projections, could affect business reporting and board projections, not just internal security posture. That is a material concern, not a security team concern.

The part of the framework that policy briefings will not mention: the volume of vulnerability disclosures coming from Glasswing and comparable programs will exceed anything security teams have managed before. The CSA document treats team resilience, sustainable workload, mental health support, and retention planning, as a strategic priority on par with the technical response. Security expertise takes years to develop. When the patch wave hits and the team is already running at capacity, the expertise loss from burnout and attrition is not a recoverable position in the short term.

Five Questions to Ask Before Your Next Board Meeting

The CSA framework includes a diagnostic set that is worth running through before a board discussion, because the answers reveal how much room a security organization actually has to move in 90 days. What is your organization's actual stance on artificial intelligence today: allowed, tolerated, restricted, or unknown? Can employees use agentic coding tools in the enterprise right now, with security guardrails in place? What is the fastest your organization has made a security-driven production change in the last year, using a real example, not a policy statement? Are your critical systems explicitly tracked and current, the actual ones that matter most, not the theoretically important list? Does executive leadership have a working definition of urgency, or does everything become a crisis until nothing is?

Most organizations will find at least two of those uncomfortable to answer with specifics. That is the point.

The Reliability Problem Will Not Wait for the Policy Problem

Four nines of uptime, 99.99%, is the standard enterprise software companies commit to for core services. For artificial intelligence inference at current demand levels, that standard is not consistently being met by the platforms the federal government is now depending on for security-critical work.

The administration is coordinating with the private sector. The private sector is working around an infrastructure ceiling no executive call raises. The CISO community published a response framework the day before the White House held its convening. The question worth asking is which of these three is moving fastest.