BreachLock

06/05/2026

13% of organizations breached in 2025 had one thing in common: their AI systems were tested like legacy IT infrastructure.

Traditional pentesting was never designed to probe training pipelines, model feedback loops, or adversarial prompt interfaces. Because it shows a snapshot of a point-in-time, any new vulnerability introduced after the engagement goes undetected until the next test or an attacker finds it first.

Agentic pentesting closes that gap by running continuously and simulating multi-step attack chains the way real adversaries operate. Read the blog: https://hubs.ly/Q04kkHvK0

Stop guessing where AI attack paths exist in your environment. Agentic pentesting finds what traditional pentests can't.

06/04/2026

The best pe*******on testers are becoming mission commanders.

AI handles scanning thousands of IPs, brute forcing, and basic lateral movement. That frees humans to focus on the 5% that requires intuition, such as the logic-heavy exploits.

At BreachLock, this is how we think about the future of PTaaS. AI is the force multiplier, while humans drive the strategy.

Is your security team structured to take advantage of that shift? Watch the clip below and catch the full webinar: https://hubs.ly/Q04k4z6-0

06/03/2026

Attackers probe constantly and your attack surface changes daily. Your annual pentest report can't keep up. Here's what happens in between tests:

• New vulnerabilities emerge
• Configurations drift
• Your report captures a moment that no longer exists

Agentic pentesting changes the model entirely. AI agents plan attack paths, execute multi-step exploitation chains, validate what's actually exploitable, and adapt in real time when defenses push back. No calendar invite required.

The teams building continuous validation programs now won't be the ones scrambling later. Read the blog to learn how you can prepare for this shift.
https://hubs.ly/Q04jZSz40

Agentic pentesting uses AI agents to continuously simulate real attacks, validate exposures, and fill in gaps left by point-in-time pentesting. Learn how it works.

06/03/2026

AI is changing the threat landscape faster than most teams can keep up. Our Founder & CEO Seemant Sehgal shares four key insights on what that means for security leaders, now featured in Forbes Technology Council. 👇 Read more: https://hubs.ly/Q04jY5G20

06/02/2026

In 2018, the median time to exploit a vulnerability was 767 days.

By 2024, it was 4 hours.

By 2025, the majority of exploits were weaponized before the CVE was ever published.

That shift exposes the real security gap. Speed of discovery is only as valuable as the validation speed to match it.

The most effective security programs are shifting investment to the validation side of the equation.

Get the complete CISO guide to closing the validation gap that frontier AI models like Mythos exposed. https://hubs.ly/Q04jLKDk0

06/01/2026

AI is accelerating cyberattacks, and most organizations are nowhere near ready.

Our Founder & CEO Seemant Sehgal was featured in Forbes Technology Council, noting that frontier AI models are making it increasingly easy for bad actors to exploit connected devices. Closing that gap requires faster patch cycles, automated deployment, and real user education before the next wave hits.

Read the article: https://hubs.ly/Q04jzrX20

06/01/2026

Your compliance deadline doesn't care about your pentest backlog. Neither do attackers.

That's why BreachLock built a platform where asset discovery, continuous exposure monitoring, and agentic AI-accelerated pentesting operate as one, drastically shortening the gap between finding a vulnerability and fixing it.

It’s Day 1 of the Gartner Security & Risk Management Summit! Come see our unified platform live at Booth #242 and find out how we accelerate your timeline from discovery to remediation.

Seemant Sehgal, Christopher Clark, and Russ Gleber are on-site and ready to walk you through it.

👉 Book your one-on-one demo: https://hubs.ly/Q04jyV0h0

05/29/2026

Many security programs were built to protect infrastructure, but AI models introduce an entirely different attack surface.

The question is no longer whether your organization uses AI. It is whether your security program is actually testing the risks that come with it. Prompt injection, data poisoning, and excessive agency aren't theoretical risks anymore.

The organizations making the most progress are the ones adapting their security testing strategies to account for how AI systems actually behave.

Read the breakdown on what to test for and how to benchmark AI model risk:

https://hubs.ly/Q04jmS7m0

AI model security starts with adversarial testing. Learn what to test for and which frameworks help CISOs benchmark and reduce AI model risk.

05/27/2026

You built the vulnerability management program, hired the team, and deployed the scanners. Last quarter, your team found 1,000 vulnerabilities. This quarter, AI found 4,000.

The problem? Remediation timelines are still human-paced.

Frontier AI models can now chain attacks autonomously and compress months of adversary work into hours. Meanwhile, remediation backlogs keep growing, with critical vulnerabilities already sitting unpatched for too long.

Faster discovery without faster validation just creates more noise at scale. The teams getting ahead are focused on a different question:

👀 ➡️ Which exposures are actually reachable and exploitable right now?

That shift from endless discovery to continuous validation is essential today. Read our guide to understand what actually changed with Mythos and how to respond.

👉 Get your copy: https://hubs.ly/Q04j3SyZ0