All postsStart free
Cyber Threats6 min read

When AI Writes Exploits in Hours: The Patch Gap Just Collapsed

SC

Sarah Chen

Head of Security Research · June 16, 2026

Illustration of an AI model generating an exploit from a security patch

New research shows frontier models, including Claude Mythos, can autonomously generate functional exploits for freshly patched vulnerabilities, sometimes kernel-level, within hours of a fix being published. The traditional patch gap, the window between a fix shipping and attackers weaponizing it, has effectively collapsed. For mobile teams, slow update adoption is now a critical exposure.

Why N-day just became as dangerous as zero-day

Defenders used to count on days or weeks between a public patch and a working exploit. When an AI can read a code diff and produce an exploit before lunch, every unpatched dependency in your app is live ammunition.

Mobile apps are especially exposed: users update on their own schedule, and an outdated SDK or library can sit vulnerable on millions of devices long after a fix exists.

Where the risk hides in a mobile app

The exposure is almost always in what you bundle and how fast you can ship a fix.

  • Outdated third-party SDKs and native libraries with known CVEs
  • Pinned dependency versions that never get bumped after launch
  • No inventory of what is actually compiled into the shipped binary
  • Slow release cadence that leaves patched fixes stuck in review

How RASMISER shortens your exposure window

RASMISER inventories the components compiled into your build and flags dependencies with known vulnerabilities, scored by severity so you patch the dangerous ones first. You see exactly what an AI-assisted attacker could target.

Running in CI, the scan turns dependency hygiene into an automatic gate, so a known-vulnerable library fails the build instead of shipping to users who may not update for weeks.

The takeaway

If AI can weaponize a patch in hours, your only defense is knowing what you ship and fixing it fast. Continuous dependency scanning is now table stakes, not a nice-to-have.

Scan your app free

Keep reading

Illustration of an AI model generating personalised phishing messages targeting employees on mobile devices
Cyber Threats

AI-Generated Phishing: Why Every Employee Is Now a High-Value Target

LLMs can now write flawless, hyper-personalised phishing messages at industrial scale. The generic mass-phish is dead — what replaced it is far harder to spot and your app is the delivery mechanism.

Illustration of an AI malware strand mutating its code to bypass antivirus detection layers
Cyber Threats

Autonomous AI Malware: The Threat That Rewrites Itself to Escape Detection

A new class of AI-driven malware can observe its environment, modify its own payload, and wait for the ideal conditions to strike. Static signatures are no longer enough, and your app binary is a target.