Tag Archives: AI in Cybersecurity

Business

Your Insurance Carrier Is Now Your Auditor

Cyber insurance used to be a safety net. In 2026, it’s also a security exam. And the test is no longer optional.

There was a time when buying cyber insurance was simple.
Fill out a questionnaire. Pay the premium. File the PDF somewhere between your business license and that printer manual nobody has opened since 2019.

Then ransomware happened.
And insurers realized something uncomfortable: companies were buying protection against cyberattacks without necessarily doing much to prevent them. So the questions changed.

Welcome to the new underwriting reality

The 2026 underwriting bar is increasingly specific:

  • Over 90% of applications ask detailed MFA questions, including RDP, VPN, cloud, and privileged accounts. SMS-based MFA is increasingly flagged as insufficient.
  • Over 80% of carriers require EDR or MDR across all endpoints.
  • Immutable backups are becoming a hard requirement, not a nice-to-have.
  • Documented proof is replacing checkbox answers. Some renewals now involve independent audits or evidence reviews.

These figures reflect the underwriting picture in our brief; requirements vary by carrier and policy. The message, however, is clear: saying you have security is no longer enough. You need to prove it.

Continue reading →
Standard
AI, Business

Why Claude’s Code Security Offering Doesn’t Replace Real SMB Cybersecurity

There’s been a lot of noise lately about AI (=Claude Code Security) replacing large chunks of cybersecurity.

Let’s slow down and separate what AI is actually good at from what actually keeps small and mid-sized businesses safe.

AI tools that scan code?
Impressive.

AI that reads configs and flags obvious misconfigurations?
Useful.

AI that can reason over static artifacts and suggest fixes?
Absolutely real progress.

But here’s the uncomfortable truth: most SMBs are not losing sleep over static code scanning.

They’re losing sleep over this:

  • “Why did our Microsoft 365 tenant just send 8,000 phishing emails?”
  • “Why is our bookkeeper’s laptop beaconing to an IP in Eastern Europe?”
  • “Why did our backup silently fail for 12 days?”
  • “Why did we pass compliance last quarter and now suddenly we don’t?”

That’s where EspressoLabs lives.

LLMs are extraordinary pattern recognizers.
They are very good at analyzing text, code, logs — when you give them the data in a clean, structured way. But SMB security isn’t clean. It’s messy, inconsistent, human, political, and operational.

EspressoLabs provides value in places LLMs simply cannot operate — at least not yet:

Continue reading →
Standard