Beyond AI-Driven Detection: Where Mainframe Risk Still Hides and What Mythos Doesn't See

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2 min. read

AI just collapsed the time between a vulnerability and an exploit

When Anthropic announced it would restrict access to its most capable model, Mythos, the reason was blunt: the system was powerful enough that it could be used to find and exploit security gaps in computer networks at a speed defenders have never had to reckon with. Mythos was pointed at open-source software — scanning source code, then chaining seemingly minor issues into full system-takeover vulnerabilities.

Image of mythos webinar.
Tim Hill, VP of Software Engineering at Rocket Software, joins CIO.com's Tom Schmidt to unpack what AI-driven detection misses on the mainframe, and what a complete security strategy requires. 

The mainframe wasn't the target. But that's exactly why it became the story.

As Tim Hill, VP of Software Engineering at Rocket Software, puts it, the Mythos event was a wake-up call that reached even the closed, proprietary world of the mainframe:

Everyone is acutely aware now that AI can really exploit vulnerabilities faster than skills and legacy tools can keep up.

Tim Hill VP Software Engineering at Rocket Software

The security challenge facing enterprises has fundamentally changed. The mainframe is not exempt — and treating it as if it were is the mistake this moment exposes.

Where the risk actually hides

Mythos starts from source code. But source code isn't available for most deployed mainframe products, so the risk that matters most lives exactly where source-code scanning can't reach:

  • Assembled binaries — the closed-source, proprietary code that runs your mainframe, with no source to scan.
  • Closed-source vendor software — the products you deploy but don't own the code to.
  • Runtime behavior — race conditions and other realities that only surface when code is actually running, exactly where serious exploits live.

 

The numbers that raise the stakes

90%

of the top 100 banks run on mainframes

$3trillion

in activity flows through mainframes every day

That scale is why regulators have stopped granting mainframe exceptions — and why the era when mainframe teams could simply tell auditors to trust them is over.

 

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Mythos is a real step forward, but it's an improvement on one piece of the story, not the whole story. What a complete, modern mainframe security strategy actually looks like, from scanning code in real time to governing patches from discovery to deployment to staying audit-ready, is where the conversation really opens up.

Watch more in the full webinar, where Tim Hill and Tom Schmidt walk through what it takes to close the gaps AI-driven detection leaves wide open.

 

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