Blogs
When the Attacker Isn’t Human: What Security Programs Must Change Now
by
Bluewave |
February 14, 2026
Autonomous, or agentic, AI is already reshaping the cyber threat landscape, often faster than security programs are evolving.
Where attacks once followed a predictable, linear kill chain that unfolded over days or weeks, AI driven adversaries now operate in dynamic loops. They probe, learn, and reroute around your defenses in seconds, not hours.‑driven adversaries now operate in dynamic loops. They probe, learn, and reroute around your defenses in seconds, not hours.
Off-the-shelf and custom LLM-based tools can already:‑the‑shelf and custom LLM‑based tools can already:
If your security program still assumes human‑paced attackers, periodic scans, and annual audits, you’re planning for a world that doesn’t really exist anymore.
We recently sat down with Bluewave’s VP of Solution Advisory Tony Scribner and Thrive’s VP of Security Detection & Response to explore how the landscape is shifting and what organizations need to do to keep pace.
For years, we thought about attacks as a linear kill chain:
If any step failed, a human operator had to stop, rethink, and try a different path. That friction slowed everything down.
With agentic AI, you hand the system a natural‑language objective, which can be something as blunt as “Find the fastest way to monetize this environment,” and it will:
The “kill chain” stops being a line and becomes a self‑correcting loop that keeps adjusting until it either finds a way in or runs out of options.
The Impact of “Vibe hacking”: natural language powered cybercrime
Developers now talk about “vibe coding,” which means describing what they want in plain language and letting AI write the code. Attackers are doing the same thing with “vibe hacking.”
Instead of hand‑crafting exploits, manually tuning phishing lures, and running small‑scale campaigns, attackers can now:
The result: more people can launch more sophisticated attacks, at lower cost, with less effort. The marginal cost of one more attack is close to zero. A single operator can point thousands of AI‑driven attack threads at the internet and let the system discover where the weakest doors are.
We’ve discussed before how the time to ransom is shrinking dramatically, which changes the way organizations need to think about attacks.
In the past security teams obsess over dwell time, which is how long an attacker lived undetected in your environment. It was often measured in weeks or months. That picture has changed with autonomous AI because now:
At that speed, there’s almost no dwell time left to optimize. The real question becomes: how quickly can you see and fix an exposure before it’s weaponized? To address this question, organizations need to recognize how the Security Operating Model is changing.
How AI Shifts the Security Operating Model
The reality is you can’t win a machine‑speed fight with a human‑only defense, which is why organizations are looking towards AI-assisted detection and response that can:
Let’s look at how this shifts the security operating model:
| Dimension | Human‑Led, Incident‑Centric Model | AI‑Assisted, Exposure‑Centric Model |
| Primary focus | Incidents and alerts | Exposures, attack paths, and resilience |
| Decision speed | Minutes to hours | Seconds to minutes |
| Scale of analysis | Limited by analyst bandwidth | Telemetry‑wide, continuous |
| Role of automation | Scripts and point playbooks | Autonomous actions within clear guardrails |
| What leaders see | Volume of incidents closed | Reduced exposure windows and business impact |
1. MFA handoffs and fragmented identity policies
We’ve spent years pushing everyone to MFA. The problem now isn’t the lack of MFA; it’s the gaps between systems that create opportunities for autonomous attacks. The typical weak spots we see are:
AI‑driven attackers are very good at testing those seams and finding the one combination of app, network path, and user that lets them in without a second factor.
2. Unpatched edge, API, and IoT surfaces
Digging into patch management there are two challenges: 1) businesses not being diligent about patching their edge and IoT devices and 2) the traditional 30 day patching cycle leaving gaps. These two occurrences often mean the following fall through the cracks:
Each new device or API you connect expands your third‑party risk and attack surface. AI makes it trivial to scan, fingerprint, and match known exploits against that surface at scale. This means patch management must be on your security hygiene list.
3. Identity hygiene and deepfake‑enabled fraud
Identity has always been attractive to attackers and AI makes it easier to impersonate and harder to trust. The idea that you can’t trust what you see or what you hear is an incredible shift.
Here’s what we’re already seeing:
What does this means? We have to move from “Trust but verify” to “Never trust, always verify, especially behavior.” Ways to do this include:
4. Hyper‑personalized phishing and social engineering
If traditional phishing was a net, AI‑driven phishing is a scalpel. We are seeing attackers using AI to:
That means they can afford to send unique messages to each person – your CFO, your AP clerk, your plant supervisor – rather than blasting one generic email to everyone.
Those “get me gift cards” texts? Expect them to sound a lot more like your actual executives.
5. Shadow AI and unintended data leakage
Some of your risk isn’t malicious at all, it’s well‑meaning people trying to get their jobs done faster. The common patterns we see here are:
Without a central, governed AI environment, it’s easy for sensitive data to leave your control and stay accessible to someone else’s models today, and potentially to quantum‑enabled decryption tomorrow.
To answer why incident-centric security doesn’t match AI threats, you must first evolve your view of incidents to continuous flows, not discrete events. Yet traditional tools and processes treat an incident as:
Autonomous AI doesn’t really work that way. Campaigns:
You’re not just putting out a fire; you’re dealing with an arsonist who keeps moving, learning, and trying again.
Annual Audits and Framework Checklists Now Have Limits
Many organizations still anchor their programs to:
In a world where attackers adjust hourly, a point‑in‑time view that’s refreshed once a year is obsolete almost as soon as the ink dries. While frameworks are still useful, they’re minimum bars, not proof of resilience.
Shifting from alert volume to exposure and resilience
Most SOC dashboards still highlight:
In an AI‑driven landscape, leadership needs to see:
That shift forces a move from “How many fires did we put out?” to “How flammable is the environment, and how quickly can we remove fuel?”
Assumptions to change immediately
In the next 90 days, explicitly retire assumptions like:
Replace them with:
Quick wins: identity, edge, and legacy OS remediation
Start where risk is high and progress is realistic.
1. Identity & access
2. Edge, APIs, and IoT
3. Legacy OS and technical debt
4. Foundations for AI‑assisted defense
At the same time, start laying the groundwork for AI‑enabled security operations:
These steps position you to add deeper continuous exposure and response capabilities over the next 6–18 months, without a disruptive “big bang” change.
Translating gaps into downtime, revenue, and brand impact
Executives don’t wake up thinking about CVEs, EDR policies, or SIEM rules. They think about:
So shift the conversation from:
To:
Use the same framing for data theft and extortion: what would it cost in cash, customers, and credibility?
Making risk everyone’s KPI, not just security’s
Your risk profile changes with every new:
Security can’t own all of that alone. Make risk part of everyone’s KPI by:
Funding innovation vs. just compliance
If your entire security budget is tied up in 1) Framework adherence, 2) Audit prep, and 3) Mandatory compliance controls, you’ll have little left to modernize how you detect, respond, and manage exposure—exactly where AI is changing the ground under your feet.
Security leaders should push for a dedicated innovation slice of budget and time to:
What to Stop Doing (and What to Consolidate)
Every new point solution you add without integration:
Focus on:
Compliance frameworks are important. But they are minimum bars, not badges of invincibility.
Avoid the trap of:
Instead, track and report on:
That’s the story your board ultimately cares about.
Legacy operating systems and apps that are no longer supported or patchable are:
If you have to keep them for a short period:
Treat them as ticking time bombs, not background noise.
Bluewave is an advisory and sourcing partner that helps organizations of all sizes acquire and manage technology solutions across cloud, network, security, and CX. We work alongside IT and security leaders, acting as an extension of your team to bring clarity and confidence to complex technology decisions.
Independent advisory on security architecture and vendors
Our team of technology experts and analysts works with a broad ecosystem of cloud, network, and security providers to help you:
Because we’re vendor‑agnostic, the recommendations focus on what’s right for your environment, constraints, and risk profile—not on forcing a particular product.
Security Assessments and Rapid Assessments
Bluewave offers Security Assessments and Rapid Assessments designed to quickly surface where you’re exposed and where you can improve.
Typical focus areas include:
You leave with prioritized, actionable recommendations, tied back to business impact and feasibility.
Building a roadmap for continuous exposure management
Beyond one‑time assessments, we help you:
Q1. Is autonomous AI already being used in real attacks or is this still theoretical?
A1. We’re already seeing pieces of autonomy—AI‑assisted reconnaissance, exploit generation, and phishing—in live attacks. Full end‑to‑end autonomy is still emerging, but the building blocks are here now. It’s wise to design your program assuming more automation and more scale on the attacker’s side over the next few years.
Q2. Does this mean traditional controls like firewalls and EDR are obsolete?
A2. Not at all. Firewalls, EDR, and other traditional controls are still necessary. They’re just no longer sufficient on their own. They need to sit inside an architecture that also includes behavioral analytics, strong identity controls, continuous exposure management, and AI‑assisted detection and response.
Q3. What’s the difference between continuous exposure management and vulnerability management?
A3. Vulnerability management usually means periodic scans for CVEs and ticketing the results. Continuous exposure management looks more broadly at assets, configurations, identities, and attack paths, continuously discovering, prioritizing, and validating what an attacker could realistically exploit—and then driving remediation.
Q4. How should we think about quantum risk today if quantum computers aren’t mainstream yet?
A4. Adversaries are already collecting and storing encrypted data today, planning to decrypt it later when quantum computing matures. Data you assume is safe now may become readable in the future. It’s smart to start inventorying where you use cryptography, planning for quantum‑resistant algorithms, and designing systems to be crypto‑agile.
Q5. Can user training keep up with AI‑enhanced phishing and social engineering?
A5. Training still matters, but it’s not enough on its own. AI makes phishing more personalized, timely, and convincing. You need a combination of technical controls (email filtering, browser isolation, identity analytics), strong processes (out‑of‑band checks for high‑risk requests), and a culture where employees feel safe slowing down and questioning unusual demands.
Q6. How do I know if our current operating model is too “incident‑centric”?
A6. Warning signs include: success defined by “incidents closed”, vulnerability scans run monthly or quarterly, strategy anchored to passing audits, and little measurement of exposure windows or time to remediate exposures. If that sounds familiar, it’s time to look at a more continuous, exposure‑driven approach.
Q7. Where should smaller IT and security teams start?
A7. Start where impact and practicality intersect: clean up identity hygiene, make MFA consistent, patch internet‑facing systems, and catalog legacy OS. From there, look to trusted partners and managed services to scale your capabilities instead of trying to build everything yourself.
Q8. How can Bluewave help if we already have tools but struggle with strategy and integration?
A8. Many organizations have plenty of tools but lack a cohesive architecture and operating model. Bluewave can help you assess what you have, rationalize your stack, align it to a continuous exposure management approach, and source any missing capabilities—with an eye toward maximizing your existing investments.
You don’t have to rebuild your security program from scratch—but standing still is not an option.
Over the next few weeks:
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