Fewer CVEs, Bigger Risk: AI-Powered Vulnerability Defense

November 2025 delivered a statistic that looks comforting at first glance: only 10 critical, high-impact vulnerabilities were flagged for urgent attention—down 69% from October’s 32. A lot of teams saw that drop and quietly exhaled.

Most companies get this wrong. A lower count doesn’t mean lower risk. It usually means attackers are concentrating on vulnerabilities that offer fast, reliable payoff—especially ones that are internet-facing, easy to weaponize, or chainable into full takeover. When the month’s “Top 10” includes zero-click mobile exploitation, WAF admin-account creation without credentials, and Windows kernel privilege escalation, you’re not looking at a calmer landscape. You’re looking at a more efficient one.

This post is part of our AI in Cybersecurity series, and November’s CVE pattern is a clean example of why AI belongs in vulnerability management and SecOps: when adversaries shift to quality over quantity, defenders need systems that can spot weak signals early, prioritize accurately, and respond automatically—before public proof-of-concept (PoC) code turns into mass exploitation.

The 69% drop is a signal, not a relief

The practical takeaway from November’s CVE landscape is simple: attackers didn’t slow down—they got pickier. Fewer “must-patch-now” CVEs can mean threat actors are spending more time on vulnerabilities that:

• Work reliably across common versions (broad blast radius)
• Sit on the edge (WAFs, gateways, admin panels)
• Bypass authentication or produce immediate privilege escalation
• Come with (or quickly gain) public PoCs, shrinking your patch window

November’s list reinforces that pattern. Seven of ten actively exploited vulnerabilities had public PoC code available. Once PoC hits the open internet, defenders often have days—not weeks—to patch, mitigate, or isolate exposed systems.

Here’s the uncomfortable part I’ve seen repeatedly in incident reviews: many organizations technically patch quickly, but they patch the wrong things first. They prioritize by CVSS severity, vendor reputation, or “what the scanner yells about the loudest.” Meanwhile, attackers prioritize by exploitability, exposure, and operational value. That gap is where AI-driven prioritization earns its keep.

The November 2025 “high-impact” patterns defenders should track

The CVEs from November 2025 cluster around a few weakness types that matter because they map to attacker outcomes—not just abstract severity.

Authentication bypass and missing auth: the fastest path to control

Authentication bypass and missing authentication for critical functions aren’t subtle. They’re “walk through the front door” classes of failure.

• Fortinet FortiWeb (CVE-2025-64446): path traversal plus auth bypass that can allow attackers to create administrative accounts.
• Oracle Identity Manager (CVE-2025-61757): missing authentication for a critical function—exactly the kind of flaw attackers love when it’s exposed or reachable from a compromised internal host.

Why this matters operationally: once an attacker lands in an admin context on a WAF or identity system, they can often pivot into credential access, traffic inspection, session hijacking, and downstream application compromise.

OS command injection: the “turn input into execution” classic

OS command injection (CWE-78) showed up as a top weakness type. It remains popular because it converts a web request into direct server-side execution.

• FortiWeb (CVE-2025-58034)
• CentOS Web Panel (CVE-2025-48703)

These issues are especially dangerous when the affected product is:

• Internet-facing
• Admin-adjacent
• Commonly deployed with weak segmentation

Out-of-bounds write: memory corruption that enables full compromise

Out-of-bounds write (CWE-787) tied as the most common weakness type. Memory corruption bugs are hard to defend with process alone because exploitation can be fast once a reliable chain exists.

• WatchGuard Fireware OS (CVE-2025-9242)
• Samsung Mobile Devices (CVE-2025-21042)

The Samsung case is the headline because it shows where this is going: mobile endpoints are now treated as high-value targets, not secondary devices.

Race condition / double free in the kernel: post-compromise accelerant

Windows kernel privilege escalation (CVE-2025-62215) matters because attackers don’t need remote code execution to win. They need any foothold—phish, stolen creds, exposed service—then a reliable escalation to SYSTEM.

That’s why kernel LPEs are so frequently tied to ransomware playbooks: they shorten the time between initial access and domain-wide damage.

Three vulnerabilities that explain the “quality over quantity” shift

If you only remember three things from November’s CVE list, make it these. They illustrate the attacker logic: gain control quickly, stay stealthy, and scale impact.

1) FortiWeb CVE-2025-64446: “Admin without creds” is an incident

This vulnerability chain combines path traversal and auth-context abuse in CGI handling, enabling attackers to bypass authentication and potentially create admin accounts.

Why it’s a top-tier risk:

• It’s internet-edge (a WAF)
• It’s high-leverage (control the security control)
• It’s operationally quiet (attackers can blend into admin workflows)

Defensive stance I recommend:

• Treat edge admin products like production crown jewels: patch SLAs measured in hours, not weeks.
• Add detections for suspicious API/CGI request patterns and sudden admin account creation.
• If patching is delayed, reduce exposure fast: restrict management interfaces, tighten IP allowlists, and consider temporary isolation.

2) Samsung CVE-2025-21042: zero-click is now an enterprise risk

The LANDFALL spyware campaign weaponized an image processing flaw for zero-click Android attacks—delivered via weaponized image files in messaging workflows.

Why enterprises should care (even outside the Middle East targeting described):

• Executives, legal, finance, and engineering leaders all carry sensitive conversations on mobile.
• Mobile compromise bypasses many traditional endpoint controls.
• A single compromised device can become a pipeline into email, MFA fatigue opportunities, and internal apps.

The stance that works:

• Treat mobile like endpoints with real threat models: enforce rapid OS/security update compliance, and monitor high-risk apps and media handling paths.
• Assume “no click required” attacks will increase in 2026 because they produce clean access with low user dependency.

3) Windows CVE-2025-62215: the ransomware-friendly escalation

A kernel race condition/double free class issue enabling SYSTEM-level privilege escalation is exactly what attackers chain after initial access.

What helps in the real world:

• Patch quickly, yes—but also reduce the value of SYSTEM by hardening credentials and lateral movement paths.
• Use application control for common exploit-tool execution patterns.
• Make local admin less common, rotate secrets, and ensure privileged access is audited.

Where AI actually helps: from CVE lists to operational decisions

AI in cybersecurity shouldn’t be treated like a magic box that “finds threats.” It’s most valuable when it reduces decision latency and human overload in the moments that matter.

AI-driven vulnerability prioritization beats severity scoring

Severity is a starting point. Exploitability in the wild is the real priority. For November, all 10 vulnerabilities were actively exploited, and 70% had public PoCs. That combination should trigger immediate reprioritization.

AI-driven vulnerability management systems can:

• Correlate CVEs with real-world exploitation signals
• Cross-reference your asset inventory and exposure (internet-facing vs internal)
• Predict which vulnerabilities are likely to be weaponized next based on attacker behavior patterns
• Recommend patch order that matches attacker economics

A simple rule that’s surprisingly effective when automated:

If a vulnerability is actively exploited and you have an exposed instance, it outranks everything else—no matter what your backlog says.

AI-powered anomaly detection catches the “quiet” exploitation style

Quality-based campaigns often look like normal admin activity:

• An unexpected admin account appears
• Configuration changes happen at odd times
• A device starts beaconing with low-volume encrypted traffic
• Kernel-level behavior changes after a low-privilege process runs

AI-based anomaly detection works best when it’s trained on your baselines (your admin hours, your update cycles, your normal API usage). It won’t replace rules; it fills the gaps when the attacker avoids the obvious signatures.

Automated response buys you time when PoCs go public

When PoC code is public, the timeline compresses:

• Disclosure → PoC → scanning → exploitation → monetization

You can’t staff your way out of that. Automation is how you keep pace:

1. Auto-create tickets with asset owners and SLA tied to exposure
2. Auto-enforce compensating controls (WAF rules, IP restrictions, segmentation)
3. Auto-trigger targeted hunts (specific endpoints, logs, suspicious requests)
4. Auto-validate patching via authenticated scans or configuration checks

The goal isn’t “full autopilot.” It’s removing the dead time between knowing and doing.

A practical 7-day playbook for the next “low-volume, high-impact” month

If your team wants something concrete, here’s a short plan I’d run whenever the CVE count drops but exploitation remains intense.

Day 1–2: Triage by exposure and exploit status

• Identify internet-facing assets tied to actively exploited CVEs
• Rank by: exposed edge systems → identity/security controls → widely deployed endpoints
• Confirm which business units own patching and change windows

Day 3–4: Put compensating controls in place

• Restrict management interfaces (allowlist, VPN-only access)
• Add detections for known suspicious request patterns and admin account creation
• Increase logging retention for the specific affected components

Day 5–6: Hunt for signs of exploitation

• Look for new privileged accounts and unusual admin actions
• Review endpoint telemetry for privilege escalation indicators
• On mobile fleets, audit patch compliance and investigate suspicious media artifacts

Day 7: Verify and measure

• Validate patch deployment and configuration changes
• Measure time-to-mitigate for exposed assets (hours matter)
• Document what slowed you down (ownership gaps, tooling gaps, approvals)

That last step is where AI initiatives should focus: remove friction from the steps that repeatedly cost you days.

The real question November raises for 2026

November 2025’s 69% drop in high-impact vulnerabilities didn’t reduce defender workload. It concentrated it. When attackers choose fewer targets, they choose targets that pay. That’s why edge security products, identity systems, mobile image pipelines, and kernel escalation bugs keep showing up in “actively exploited” lists.

If you’re investing in AI in cybersecurity, aim it at the boring-but-critical problems: prioritization, exposure mapping, anomaly detection, and automated response. Those are the areas where “quality over quantity” attackers get stopped.

The forward-looking question for your next security planning cycle is straightforward: If next month has only 8 critical CVEs—but all 8 are actively exploited with public PoCs—can your team identify exposure and mitigate within 24–72 hours? If the honest answer is no, AI-enabled operations isn’t a nice-to-have. It’s the only way to keep the math in your favor.