If you’re a CTO, CISO, or engineering leader, here’s what you need to know right now:
- The traditional pentest-report-remediate cycle is becoming obsolete. The velocity of vulnerability discovery is about to outpace any episodic approach.
- Security must become a continuous function embedded in development, not a periodic checkpoint. Vulnerabilities need to be found and fixed as code is written.
- Invest in AI-powered remediation, not just AI-powered discovery. When AI can find vulnerabilities at scale, you need AI to fix them at scale. Human teams alone cannot keep pace.
- Start now. The companies that build defensive AI infrastructure today will have a 12-month head start over those that wait.
This isn’t speculation. This is why we built what we built.
What Just Happened
In the span of one week, the cybersecurity landscape shifted permanently.
On April 7th, Anthropic launched Claude Mythos Preview, a model that found thousands of zero-day vulnerabilities across every major operating system and browser. Some had gone undetected for 27 years. The model is so capable at finding and exploiting flaws that Anthropic refused to release it publicly, restricting access to 40 handpicked organizations under Project Glasswing. Over 99% of what Mythos found remains unpatched.
One week later, OpenAI responded with GPT-5.4-Cyber, a model fine-tuned for binary reverse engineering, vulnerability scanning, and exploit development. Their CTF benchmarks jumped from 27% to 76% in three months.
Both companies are now planning as if the next generation of models will autonomously discover and exploit zero-days in well-defended systems. They estimate this will happen within 12 months.
Jamie Dimon confirmed JPMorgan is already testing Mythos. Treasury Secretary Scott Bessent called an emergency meeting with bank CEOs to discuss the implications. The UK’s AI Security Institute confirmed Mythos can execute multi-stage attacks that would take human professionals days.
The industry panicked about the finding. But the real crisis is the fixing.
As Tal Kollender, founder of Remedio, put it: an AI that finds thousands of vulnerabilities per minute is “an incredibly expensive alarm” if you can’t remediate at the same pace. Anthropic’s own numbers prove the point — 99% unpatched.
Finding risk faster than you can fix it doesn’t make you more secure. It makes you more aware of how exposed you are.
What We Built
At OliveX Security, we’ve been tracking these advances since December 2025. While the industry debated whether AI would change cybersecurity, we were building the system to respond to it.
The result is an end-to-end autonomous security pipeline that discovers vulnerabilities, generates verified fixes, performs retroactive codebase analysis, and delivers production-ready remediation, in under 24 hours.
Not a scanner. Not a report. A pipeline that closes the loop from finding to fixing.
Discovery: Agents That Think Like Pentesters
Our discovery layer isn’t a general-purpose LLM with a security prompt. It’s a set of specialized agents built on an architecture designed for offensive security research, trained with the methodology behind 1,200+ responsibly disclosed vulnerabilities across Apple, Microsoft, Meta, Visa, and Disney.
These agents reason about code the way an experienced penetration tester does: data flows, authentication boundaries, trust assumptions, and the subtle logic flaws that automated scanners consistently miss.
Analysis + Fix Generation: From Finding to Code
When a vulnerability is identified, the pipeline doesn’t stop at a CVSS score and a Jira ticket. A second layer of agents evaluates real-world exploitability and blast radius, then generates a verified fix.
Not a recommendation. Not a paragraph in a PDF. Actual code changes that address the root cause, respect the codebase’s conventions, maintain backward compatibility, and are ready for review.
Retroactive Sweep: Fix the Disease, Not the Symptom
This is where most security programs fail. They patch the bug and move on.
Our pipeline treats every finding as an indicator of a systemic issue. Once a vulnerability pattern is identified, agents sweep the entire codebase and repository history looking for the same class of flaw, the same anti-pattern, the same trust boundary violation. Every instance gets a fix.
The difference between putting out fires and fireproofing the building.
Delivery: Production-Ready in 24 Hours
The output is a set of pull requests, each containing:
- The vulnerability and its real-world impact
- The verified code fix with full context
- Testing methodology and verification results
- Retroactive findings across the codebase
- Prioritization based on actual exploitability, not just CVSS
Ready for your engineering team to review and ship to production. The entire cycle targets 24 hours from discovery to deployable fix.
0xHunter: Where Everything Comes Together
The entire pipeline runs through 0xHunter, our centralized platform that acts as the command center for the full security operation.
0xHunter aggregates:
- Autonomous AI agents — the offensive discovery engine
- Manual pentest findings — from our human research team
- External feeds — CVEs, advisories, zero-day disclosures
- Third-party scanners and client-reported issues — integrating with existing security stacks
- Domain-specific agents — trained on fintech, API security, and cloud infrastructure patterns
The traditional remediation workflow requires a vulnerability researcher, a security engineer for triage, a developer to understand the codebase, another to write the fix, QA to test it, and a PM to track it. Six roles, multiple handoffs, weeks of elapsed time — per vulnerability.
0xHunter compresses this into a coordinated agent pipeline. Humans provide oversight, risk judgment, and final approval. The agents handle everything else.
Why This Matters Now — Especially in Fintech
Financial services operate under PCI DSS, SOC 2, regulatory audits, and constant fraud risk. A vulnerability in production isn’t just a security incident, it’s a regulatory violation, a trust breach with financial partners, and a direct path to monetary loss.
When AI models can scan an entire codebase and find critical vulnerabilities in hours, companies still running quarterly security cycles are operating with known-exploitable code for months. In fintech, that’s not a risk. It’s an exposure that regulators, partners, and attackers will all find.
The Window Is 12 Months
Both OpenAI and Anthropic have been explicit. The capabilities currently restricted to 40 organizations under Project Glasswing will eventually become widely available. When that happens, attackers will have the same AI tools that today require an invitation from Anthropic or a verified identity check from OpenAI.
The companies that embed continuous, AI-powered security into their development lifecycle today will be ready. The ones that wait will be catching up, in the worst possible environment to be behind.
We’ve spent 15 years in offensive security. We know how attackers think because we’ve been doing their job, responsibly, since before AI could write a line of code. Now we’re building the defensive infrastructure the industry needs.
The era where finding vulnerabilities was the hard part is over. The hard part now is fixing them faster than they can be exploited.
That’s exactly what we built.
Damian Gambacorta is the Founder & CEO of OliveX Security, a boutique offensive security consultancy specializing in AI-powered vulnerability discovery and remediation for fintech and enterprise clients. HackerOne’s #1 ranked researcher in Argentina, with 1,200+ vulnerabilities responsibly disclosed to Apple, Microsoft, Meta, Visa, Disney, and others.
Learn more about 0xHunter at olivex.io