Your purple team is not purple – just red and blue in the same room

The network defense at 2:00 a.m. looks like this: The analyst copies the hash from the PDF and pastes it into the SIEM query. The red team’s script has been manually rewritten for use by the blue team. The patch is awaiting a change approval period that is longer than the exploitation period itself.

There is no incompetent person in that chain. All humans are doing their jobs correctly. The problem is the system, its workflow, and the cumbersome handoff.

In contrast, the attacker’s clock is almost gone.

In 2024, the average time for an exploit to work after a CVE was published was 56 days. In 2025, it will be reduced to 23 days. So far in 2026, it has hovered around 10 hours across 3,532 CVE exploit pairs from CISA KEV, VulnCheck KEV, and ExploitDB.

Figure 1. Windows exploit vulnerabilities now reach 10 hours

The bit of good news is that the defender’s clock has sped up to the point where it runs out in a matter of hours. The really bad news is that it now jumps the attacker’s clock and runs in seconds. It’s far from a fair fight.

For a decade, the security industry has referred to the practice of bridging this gap as “purple teaming.” That’s the correct answer. Until now, this has not been practical.

What is purple teaming in practice?

The concept of purple teaming is simple.

Red finds the path an attacker would take. Blue validates whether detection is triggered and prevention is enabled. they repeat it. The red output becomes the blue input. Blue’s output becomes red’s next input. This loop reinforces the organization’s posture on an ongoing basis rather than quarterly.

That’s the idea, and again, it’s a solid idea. Sadly, it’s at the execution that it all comes crashing down.

3 Reasons Why Traditional Purple Teaming Is Not Operationalized

Reason 1: Human purple teaming has too much friction.

Very few people do purple teaming as an actual loop. Teams don’t talk often enough, and when they do, people wind up in long meetings, detailed reports, long post-mortems, and family emergencies. In the most general sense, the bottleneck is almost always human.

Look at where a defender’s time is actually spent.

It was launched, not inside EDR. There was a correlation, not within the SIEM. It had a CVE built into it, not inside the scanner.

Faster response time during transfer. Unread Slack messages. Copied and pasted hash. The PDF was emailed to you for review. Tickets waiting for attention or approval. The red team’s scripts have been manually rebuilt for the blue team. This is spaghetti delivery. Once you recognize an inefficiency or point of failure, you cannot ignore it.

Reason 2: Team and tool alignment is the real bottleneck

The network team owns the firewall. SOC consumes alerts. Red performs the exercise. Blue builds detection. VM tracks CVEs. IT operations personnel apply the patch.

Each group operates one or more tools. Each tool produces artifacts (findings, alerts, reports, tickets) that are captured, reinterpreted, and delivered. What these teams collectively create represents a service, a security posture that is continuously verified. In reality, it’s usually a jury-rigged mess, stuck with overburdened humans typing into Jira with blurred vision at night.

So purple teaming remains an aspiration. Cool ideas for vendor decks. Probably a quarterly exercise. It almost never works. It’s definitely not easy to use.

Reason 3: Traditional purple teaming can’t keep up with AI-powered opponents.

Here are the changes: The attacker obtained an LLM. Defender is still filling out the Jira ticket.

In most organizations, the change approval process alone was longer than the exploitation period.

An AI-powered attacker can compromise your system in under 73 seconds. Defenders typically take at least 24 hours to deploy fixes, working through a standard handoff chain between the SOC, red team, blue team, and IT.

Figure 2. Spaghetti handoff between teams

Quarterly Purple Team exercises, and even monthly exercises, are no longer loops, but checkboxes, snapshots of battles that have already taken place, and usually wasted exercises.

Enter Autonomous Purple Teaming

The same technology that compresses the attacker’s clock can also compress the defender’s clock.

Fortunately, autonomous purple teaming is, by its very nature, exactly the kind of workflow that AI is good at. That is, a strict, well-defined loop between two specialized functions, where the bottleneck was always the human handoff and knowledge transfer, rather than the work itself.

When the autonomous agent performs the handoff, the loop eventually closes at machine speed.

Red findings automatically become blue tests. Blue’s gap will be Red’s next practice. No coffee breaks, no kids coming home from school, no holiday breaks.

The system that people have been describing for a decade can finally be implemented as an ongoing methodology rather than a calendar event.

This is not “AI for security” in the sense of generating YARA rules, summarizing alerts, and creating tickets, as most vendors have been touting for the last year. These are task automations. Convenient and gradually helpful. But true autonomy is something else. This means that the agent executes the entire loop end-to-end and each step is auditable, allowing for overrides, readjustments, and rollbacks.

And it’s a dial, not a cliff. Crawl is manual. Walks are scheduled with AI assistance. Execution is end-to-end, with human review only when necessary.

Autonomous Purple Teaming in action: BAS, automated penetration testing, and AI-powered mobilization

Effective autonomous purple teaming requires three components that work as a system rather than separate tools.

Automated Penetration Testing is a red question that continues to be answered. Given today’s exposures and today’s controls, can attackers reach the goldmine in your environment?

Breach and Attack Simulation (BAS) is Blue’s answer. Did the firewall block it, did the EDR catch it, did the SIEM rule fire, did the response execute as described in the runbook?

Figure 3. BAS and automated penetration testing give you the big picture.

AI-powered mobilization, once a human input into Jira, is now performed by a series of specialized agents. A CISA alert is issued. The CTI agent enforces it against the environment. Baseliner agents determine that threats are relevant and obtain current posture from BAS, penetration testing, and exposure data. Red and blue agents run simulation and validation in parallel. The Mobilizer agent automatically deploys low-risk fixes, opens tickets for medium fixes, and flags remaining fixes for human review. Reporter agents create one executive view for leadership and one technical view for SOC.

There are no analysts in the chain. All steps will still be visible on the operator console. There are no black boxes, just no humans at the table typing into Jira.

The output is not 50,000 CVEs ranked by CVSS. This is one continuous action queue that spans red and blue. That is, what is actually exploitable today for real control and what should be done about it before the exploitation period closes.

It’s not just automation, it’s purple teaming. This is the loop the industry has been dreaming of, finally running at the pace that AI-powered threats now demand.

See it in action inside a real company

Continuous loop is the correct answer. But “continuous” still means that humans are pacing things. When attackers operate at machine speeds, the problem is not the gap between seeing and detecting. It’s between detecting and proving it early enough that an AI-driven attacker can’t discover it in the first place.

This is where validation goes from continuous to autonomous. AI agents read alerts, scope tests, run simulations, push fixes, and generate reports. SOC, on the other hand, focuses on the big picture and ideally gets you the sleep you need.

Note: This article was written by Sıla Özeren Hacıoğlu, Security Research Engineer at Picus Security.