Introducing The Security Leader’s Operating System

There is one sentence I hear from information security leaders more than almost any other:

“I don’t have time to do what I need to do.”

The problem usually isn’t motivation, discipline, or effort. Security leaders already work hard. The deeper problem is that their ability to handle difficult work attracts more difficult work.

Questions, approvals, exceptions, vendor reviews, audit requests, incidents, meetings, unfinished decisions, and executive concerns all flow toward the person who has demonstrated that they can carry them. Eventually, being able to handle almost anything becomes the reason the leader has time to think about almost nothing.

I wrote The Security Leader’s Operating System to help change that.

Thinking

Security Leaders Don’t Need Another Productivity Trick

Most productivity systems concentrate on organizing work after it has already been accepted.

This field guide starts earlier.

Before deciding where a task belongs, it asks whether that work should exist in its current form at all. It applies the EDSAM mental model:

  • Eliminate work that does not need to happen.
  • Delegate outcomes that do not require the leader’s authority or judgment.
  • Simplify work until it produces the smallest useful result.
  • Automate the predictable parts of the work that remains.
  • Maintain only what must remain under the leader’s direct care.

The objective is not to help security leaders process an endlessly growing queue more quickly. It is to redesign the system so that less work requires the leader in the first place.

Protect the Work Only the Leader Can Do

Some work genuinely belongs with the security leader.

Setting risk appetite, challenging assumptions, translating technical exposure into business decisions, communicating during consequential events, developing people, and accepting residual risk cannot simply be optimized away.

But that work is often crowded out by management exhaust: status collection, repetitive reporting, preventable escalations, meeting preparation, evidence retrieval, routing questions, and processes that exist largely because they have always existed.

The guide introduces practical ways to distinguish leader-only work from work that can be removed, transferred, redesigned, or supported by better systems.

It includes:

  • A Money, Attention, and Time workload scan
  • The Eisenhower Matrix mapped into EDSAM
  • TaskGrid as an example of integrating urgency, importance, agency, commitments, planning horizons, and EDSAM dispositions
  • Information security workload playbooks
  • A recurring operating cadence
  • A 30-day reset
  • Capacity and decision tools
  • Field-ready worksheets and checklists
  • A NIST Cybersecurity Framework 2.0 scope check

AI Can Reduce Work—or Industrialize the Wrong Work

Modern LLMs, GPTs, skills, assistants, and agents make this conversation more urgent.

These tools can retrieve information, summarize evidence, compare documents, prepare decision packets, draft communications, and move bounded work through repeatable processes.

They can also accelerate bad processes, obscure missing context, accumulate excessive authority, and create new infrastructure that someone must maintain.

That is why the guide applies EDSAM before automation.

It explores how to divide work among humans, models, and deterministic systems; how to establish capability levels and autonomy budgets; and how to preserve accountable human judgment when AI-enabled workflows can create real consequences.

The important question is not simply, “Can AI perform this task?”

The better sequence is:

  1. Should this work exist?
  2. Who should own its outcome?
  3. What is the smallest useful result?
  4. Which parts are predictable enough to automate?
  5. What judgment, authority, or relationship must remain human?

A Field Guide, Not a Theory Book

This is intended to be used with the work already in front of you.

Choose one recurring meeting. One report. One approval queue. One source of preventable escalation. One hour of work that only you can perform.

Then apply the system.

A saved hour is useful. A redesigned workflow that prevents the same demand from returning every week is leverage. A clearer decision boundary makes the entire team stronger.

My broader goal is to leave behind a legacy of useful knowledge—methods that other people can test, challenge, improve, and carry forward. I hope this guide becomes part of that working library.

Download the Field Guide

You can download The Security Leader’s Operating System here:

Download The Security Leader’s Operating System

As you work through it, I would be interested to hear what you eliminate, delegate, simplify, automate, or deliberately maintain first.

When the Security Control Plane Fails: Build a Minimum Viable Defensive System

At 2:13 a.m., the SOC receives an alert involving a cloud administrator.

At 2:16, analysts lose access to the SIEM because authentication depends on the identity provider now under investigation.

At 2:19, the incident collaboration channel disappears.

At 2:23, the on-call engineer discovers that the break-glass credentials are stored in the privileged-access platform—which also authenticates through the suspect identity provider.

At 2:27, the cloud console still shows green status indicators, but nobody can establish whether the logs are complete, delayed, or manipulated.

By 2:35, the organization has two incidents.

The first is the security event.

The second is the loss of its ability to respond to the security event.

That second incident is the one most response plans do not adequately address.

3Errors

Incident Response Has a Hidden Assumption

Most incident-response plans assume the defensive machinery will survive the incident.

The identity provider will authenticate responders. The privileged-access system will issue administrative credentials. The cloud management plane will accept containment commands. The SIEM will provide reliable telemetry. The ticketing platform will maintain the timeline. Email, chat, conferencing, and document-sharing systems will allow the response team to coordinate.

Those systems are treated as infrastructure surrounding the incident rather than as potential components of the incident.

That is a dangerous assumption.

In a recent State of Security post, I argued that controls that look separate on an architecture diagram may actually be “branches of the same tree.” They may share an identity provider, administrative tenant, logging pipeline, automation layer, DNS infrastructure, certificate authority, or cloud control plane. When one of those shared foundations fails, several supposedly independent controls can fail with it. (State of Security)

The next question is harder:

What is the smallest defensive system the organization must be able to operate after that tree falls?

This is not conventional disaster recovery. It is not simply a matter of restoring the SIEM, activating a backup tenant, or retrieving an emergency password.

It is degraded-mode security operations.

The Control Plane Can Fail by Lying

Security teams usually test failures as availability problems.

The identity provider is down. The SIEM is unreachable. The ticketing platform will not load. The primary cloud region is unavailable.

Those are relatively clean failures. They are visible, bounded, and easy to describe during a tabletop exercise.

Adversarial failure is different.

A compromised identity provider may continue issuing tokens. A hostile administrator may alter conditional-access policies while leaving the service operational. A logging pipeline may continue displaying data while silently omitting selected events. A collaboration platform may preserve most messages while exposing the incident channel to the attacker. An automation platform may continue executing containment playbooks after its credentials or logic have been subverted.

The system is not down.

It is lying.

That distinction changes the recovery problem. An unavailable system can sometimes be restored. An untrustworthy system must first be excluded from the response path.

NIST’s cyber-resiliency work provides the right foundation for thinking about this. It frames resiliency around four outcomes: anticipating adverse conditions, withstanding them, recovering from them, and adapting afterward. It also applies that thinking to shared services, common infrastructure, and systems of systems—not merely individual applications. (NIST Computer Security Resource Center)

A resilient security program therefore cannot define success only as preventing compromise or restoring systems. It must be able to continue essential defensive operations while some of its own systems are unavailable, degraded, or hostile.

Start With Inversion

The normal planning question is:

How do we keep the security control plane available?

That is necessary, but incomplete.

Invert the problem:

Assume the primary security control plane is unavailable or cannot be trusted. How do we still defend the organization?

Assume that:

  • The primary identity provider cannot be trusted.

  • Existing administrative sessions may belong to the attacker.

  • The privileged-access platform is inaccessible.

  • Centralized telemetry is incomplete.

  • Normal collaboration and ticketing systems are exposed.

  • Managed responder workstations may be under hostile administrative control.

  • Cloud automation may be executing unauthorized changes.

  • DNS, certificate, key-management, or time services may be unreliable.

  • One or more key responders cannot be reached.

Now ask what responders must still be able to do.

Not which products must be restored.

Not which dashboards executives expect to see.

Not which recovery checklist should be opened first.

What capabilities must exist for the organization to remain defensible?

Define the Minimum Viable Defensive System

Minimum Viable Defensive System is the smallest deliberately independent collection of people, authority, identities, devices, communications, telemetry, containment mechanisms, evidence storage, and recovery materials that allows the organization to continue defending itself when its normal security control plane is unavailable or untrusted.

It is not a second full-sized SOC.

It is not a duplicate of every production security tool.

It is not a collection of individually labeled “break-glass” features.

It is a composed operating system for degraded defense.

At minimum, it must provide six capabilities.

Capability Minimum viable state Evidence that it is independent
Authenticate Authorized responders can establish identity and emergency authority using protected credentials and trusted administrative devices. The path does not require the primary identity provider, PAM platform, corporate network, normal endpoint-management plane, or primary email account.
Communicate and coordinate Responders can establish a secure command channel, assign roles, reach critical internal and external parties, and maintain a decision and action log. Accounts, provider, authentication, network path, and recovery information do not depend on the primary collaboration environment.
Observe Responders can obtain trustworthy information from critical systems and identify gaps, delay, or tampering in normal telemetry. Collection, storage, access, keys, and administrative authority do not all share the suspected failure domain.
Contain Responders can revoke access, disable identities, isolate assets, stop dangerous automation, alter routes or policies, and protect critical systems. Emergency containment does not require normal SSO, normal PAM approval, the primary SOAR platform, or access to the normal ticketing workflow.
Preserve evidence Responders can store relevant logs, configuration data, images, exports, notes, and decision records with integrity and provenance. Primary administrators cannot silently alter or delete the evidence, and responders retain access to keys, timestamps, capacity, and custody procedures.
Reconstitute Responders can rebuild roots of trust and restore defensive services from known-good materials in a defined order. Configurations, credentials, keys, backups, tooling, and administrative access do not depend entirely on the environment being rebuilt.

These are capabilities, not products.

A security team may satisfy them through a mixture of cloud-native controls, offline materials, separate accounts, alternative providers, clean devices, manual procedures, direct system access, and preauthorized decision rights.

NIST makes a similar architectural point in its resiliency guidance: survivability comes from combinations of technology, architectural choices, engineering practices, operational procedures, and people—not from one product or control.

Break Glass Is Not an Account

Organizations often point to an emergency administrative account as proof that degraded-mode access has been addressed.

That is only one link in the chain.

Consider an emergency account that:

  • Is stored in the normal PAM platform.

  • Uses the normal identity provider for authentication.

  • Requires a managed laptop that cannot be unlocked without normal SSO.

  • Can be used only from the corporate network.

  • Depends on the normal DNS and certificate infrastructure.

  • Requires an approval recorded in the normal ticketing system.

  • Sends its alerts to the normal SOC mailbox.

The account exists.

The emergency capability does not.

Break glass is not an account. It is an end-to-end operating path.

Microsoft’s emergency-access guidance recommends multiple cloud-only accounts, authentication methods that differ from normal administrative authentication, secure storage, monitoring, and recurring validation. AWS similarly describes pre-created emergency identities and roles, dedicated emergency access arrangements, hardware authentication, and periodic testing for situations in which the centralized identity provider is unavailable or compromised. (Microsoft Learn)

Those are valuable design ingredients. The security program still has to compose them into a functioning response system.

The responder must be able to retrieve the credential, authenticate, use a trusted device, reach the management interface, execute an authorized action, record that action, observe its effect, and preserve the resulting evidence.

Testing only the login proves only the login.

Independence Is a Property of the Whole Path

Two tools can be different and still fail together.

A secondary messaging platform is not independent if it uses the same identity provider.

A backup SIEM is not independent if it receives data through the same collectors.

A separate cloud account is not independent if the compromised organization administrator can assume control over it.

An immutable log store is not useful during the incident if access to its decryption keys depends on the failed key-management plane.

A responder laptop is not clean if it must contact the suspect device-management service before allowing an administrator to sign in.

An alternate network path is not alternate if it converges on the same DNS, certificate, firewall-management, or telecommunications dependency.

This is why fallback design must be scenario-specific. Nothing is universally independent. It is independent only relative to a defined failure.

NIST’s guidance on diversity and redundancy warns that apparent alternatives can converge on the same underlying foundation. It specifically treats diversity of command, control, and communications paths—including out-of-band paths—as a resiliency technique, and notes that redundancy can be undermined when duplicated capabilities share common resources or homogeneous components.

CISA guidance has likewise emphasized out-of-band incident communications, separate management paths, and logging aggregated into protected out-of-band locations. These practices reduce the chance that the compromised environment can blind or isolate the response team. (CISA)

Again, those mechanisms are necessary.

They are not sufficient until they work together.

Restore Capabilities, Not Products

During a compound failure, organizations tend to restore whatever system has the most visible outage, the loudest executive sponsor, or the clearest recovery runbook.

That can produce the wrong order.

The goal is not to make the security stack look normal as quickly as possible. The goal is to restore trustworthy defensive agency.

A practical priority sequence looks like this.

1. Establish trusted command

The organization needs an incident commander, an emergency authority model, authenticated responders, a protected communications channel, and a functioning decision record.

Without trusted command, every subsequent action is debatable. Responders do not know who is authorized, which instructions are legitimate, or whether the attacker is participating in the response.

This layer should also provide access to an offline or separately protected contact roster covering executives, legal counsel, insurers, outside responders, critical vendors, law enforcement contacts, and communications personnel.

2. Establish a trustworthy view

Responders must determine what they can still observe and which sources remain credible.

This does not require immediately rebuilding the entire SIEM. It may involve direct access to native audit sources, an independently protected log archive, network telemetry, cloud snapshots, system exports, or read-only queries through emergency accounts.

The first question is not, “Are logs arriving?”

It is, “What evidence do we have that these logs are complete, current, and resistant to alteration by the suspected adversary?”

Evidence preservation begins here. Observation and preservation should not be separated into distant phases. The data available during the first hour may not remain available later.

3. Regain safe containment capability

Once responders have enough confidence to act, they need a limited but reliable way to constrain the event.

That may include:

  • Revoking sessions and tokens.

  • Disabling identities.

  • Isolating accounts, workloads, subscriptions, or network segments.

  • Blocking known infrastructure.

  • Suspending compromised automation.

  • Protecting backups and logging repositories.

  • Restricting administrative paths.

  • Moving critical services into a predefined defensive posture.

Containment paths should be narrow, preauthorized, observable, and reversible where practical.

They should not depend on the same orchestration layer whose trust is in question.

4. Reconstitute roots of trust

Only after responders have trusted command, sufficient visibility, and safe agency should they begin rebuilding the normal control plane.

Reconstitution must follow dependency order.

Identity may need to be restored before PAM. Key management may need to be restored before protected logging. Trusted administrative endpoints may need to be rebuilt before cloud policy is changed. Logging may need to be reestablished before production workloads are reconnected.

Restoring dependent tools before their foundations are trustworthy creates the appearance of recovery without its substance.

This is a priority model, not a waterfall. Observation, evidence preservation, and containment will often proceed in parallel. The point is to prevent teams from restoring familiar products while critical defensive capabilities remain absent.

Measure Time to Defensible State

Traditional recovery planning uses recovery-time objectives to express how long a system can remain in recovery before unacceptable harm occurs. That is useful for determining when an identity platform, logging service, or collaboration system must return. (NIST Computer Security Resource Center)

It does not answer what defenders can do while those systems remain unavailable.

A security program should add another measure:

Time to Defensible State

Time to Defensible State is the elapsed time between declaring the primary defensive control plane unavailable or untrustworthy and validating that the Minimum Viable Defensive System is operating through independent paths.

A defensible state might require proof that:

  • Emergency authority has been invoked.

  • Required responders have authenticated independently.

  • A secure command channel is operating.

  • A decision and action record is being maintained.

  • At least one trustworthy telemetry path is available.

  • Responders can execute and verify an emergency containment action.

  • Evidence can be deposited into an independently protected repository.

  • The team understands which normal services remain prohibited.

“Someone successfully logged in” is not a defensible state.

“We opened the backup chat room” is not a defensible state.

The state is reached only when the capabilities operate together.

Organizations should measure the component times as well:

  • Time to recognize and declare control-plane degradation.

  • Time to establish trusted responder identity.

  • Time to establish out-of-band command.

  • Time to obtain the first trustworthy telemetry.

  • Time to execute the first validated containment action.

  • Time to preserve the first evidentiary artifact.

  • Time to begin controlled reconstitution.

  • Maximum duration the degraded system can operate.

That last measure matters.

A fallback that works for 20 minutes but cannot support a twelve-hour investigation is not sufficient. Capacity, credential lifetime, battery life, communications access, evidence-storage volume, staffing, vendor support, and shift turnover are all part of the design.

Test Compound Failure, Not Components

Most organizations test their emergency mechanisms one at a time.

The emergency administrator logs in.

The backup conference bridge works.

The log archive accepts a test event.

The incident-response binder opens.

The cloud backup restores.

Every component passes.

Then the system fails during the exercise because nobody can retrieve the emergency credential without the PAM system, the clean laptop requires the unavailable identity provider, and the alternate communications channel does not include legal counsel or the cloud team.

Component success is not system success.

A meaningful exercise should begin with a compound condition such as:

The identity provider is suspected of compromise. Existing administrative sessions cannot be trusted. The centralized logging query plane is unavailable, although some collection continues. Normal email, chat, ticketing, and PAM systems are prohibited. The cloud management environment may contain unauthorized policy changes.

Then make the team perform the work.

Retrieve the emergency materials using the real custody process.

Start the designated administrative devices.

Use the actual alternate network path.

Authenticate to the necessary systems.

Generate a known event and prove it appears in the independent telemetry path.

Contain a sacrificial asset.

Preserve an artifact and validate its integrity.

Reach an external participant.

Maintain the incident log.

Operate long enough to perform a shift handoff.

Exit degraded mode, reconcile all emergency actions, rotate credentials, and restore monitoring.

Do not allow the exercise controller to hand the team imaginary access, pretend that a credential was retrieved, or declare a containment action successful without executing a safe equivalent.

Every simulated shortcut conceals a dependency.

NIST’s current incident-response guidance treats preparation, response, and recovery as integrated parts of cybersecurity risk management rather than as a separate binder activated after detection. Compound-failure testing is one way to turn that integration into operational evidence. (NIST Computer Security Resource Center)

The Fallback Creates Its Own Risk

An independent defensive system is powerful.

That also makes it dangerous.

Emergency identities may hold standing privilege. Alternative communications channels may escape normal monitoring. Offline credentials can become stale or be mishandled. Direct administrative paths can bypass approval systems. Separate evidence stores may contain highly sensitive information. Dormant devices may miss critical patches.

The fallback cannot simply be hidden and forgotten.

It requires its own controls:

  • Dual custody for the most powerful emergency materials.

  • Tamper-evident storage and access records.

  • Narrowly scoped emergency roles.

  • Independent monitoring of every activation.

  • Regular credential, key, and device validation.

  • Immediate review and rotation after use.

  • Defined activation and termination authority.

  • Reconciliation of emergency actions into normal records.

  • Periodic review for new shared dependencies.

This is a second-order tradeoff.

The organization creates exceptional access to survive the loss of normal access controls. It must then protect that exceptional access without reconnecting it to the same control plane it was designed to bypass.

There is no product setting that resolves that tension. It must be engineered and governed.

A Practical Design Standard

A security program should not claim degraded-mode readiness until it can produce six things.

1. A declared defensive minimum

The organization has explicitly defined what authentication, communication, observation, containment, evidence preservation, and reconstitution mean in its environment.

2. A dependency topology

Each capability has been traced through its identities, devices, networks, providers, administrators, keys, data sources, and human custodians.

Shared failure domains are visible.

3. Independence claims tied to scenarios

The organization does not say that a system is simply “independent.” It states which failures it is independent from and provides evidence supporting that claim.

4. Activation and exit criteria

Responders know who can declare the primary control plane untrusted, what changes when that declaration occurs, and what evidence is required before normal systems can be used again.

5. Measured recovery of defensive capability

The organization has established a target Time to Defensible State and measured it during an end-to-end exercise.

6. Evidence of sustained operation

The fallback has demonstrated that it can support a realistic incident duration, including staffing changes, evidence growth, credential use, containment actions, external coordination, and eventual reconciliation.

This turns degraded-mode response from a collection of reassuring statements into a testable design standard.

Small. Separate. Boring. Measured.

The Minimum Viable Defensive System should be small enough to understand.

It should be separate enough to survive the named failure.

It should be boring enough to operate under stress.

It should be measured often enough that leadership knows whether it is real.

Centralization is not inherently bad. Modern security programs need centralized identity, logging, administration, orchestration, and collaboration.

But centralized efficiency creates concentrated dependency.

A mature program does not pretend those dependencies will always survive. It plans for the moment when the normal tools are unavailable, the dashboards are questionable, and the attacker may be using the same administrative machinery as the defenders.

The question is no longer:

Do we have break-glass accounts?

The question is:

Can we prove that authorized responders can authenticate, communicate, observe, contain, preserve evidence, and begin reconstitution when the primary security control plane is unavailable or hostile—and can they do it within a measured period?

Until the answer is yes, the organization is resilient only while its assumptions hold.

Security programs must do more than defend the business.

They must remain capable of defending it while their own machinery is failing.


More Information and Assistance

MicroSolved, Inc. can help organizations:

  • Map security-control dependencies and shared failure domains.

  • Define a Minimum Viable Defensive System.

  • Design independent emergency identity, communications, administrative, logging, and evidence paths.

  • Establish degraded-mode activation and recovery procedures.

  • Run compound-failure tabletop and live validation exercises.

  • Define and measure Time to Defensible State.

Contact MicroSolved at info@microsolved.com or +1.614.351.1237. Relax. We’re on watch. 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Passkeys, Not Passcodes: A Practical Enterprise Guide to Moving Beyond Passwords

There is a small terminology problem in the identity world right now, and it matters more than it looks.

passcode or PIN is usually a local unlock secret. It unlocks a phone, a laptop, Windows Hello, an authenticator app, or a hardware security key. A passkey is different. A passkey is the standards-based replacement for passwords, built on FIDO2/WebAuthn. The user unlocks the passkey locally with a fingerprint, face scan, device PIN, pattern, or security key, but the website or application receives cryptographic proof — not a reusable password. FIDO defines passkeys as FIDO authentication credentials based on FIDO standards, tied to an account, and used with the same process the user already uses to unlock a device.

That distinction is not pedantry. It is the difference between a local unlock method and a replacement for one of the most abused controls in the history of computing.

Passwords have had a long run. They also have had a long list of failures: reuse, phishing, spraying, stuffing, database theft, weak reset workflows, help desk abuse, and user fatigue. We have spent decades trying to compensate for those failures with complexity rules, expiration schedules, password managers, SMS codes, mobile push prompts, training campaigns, and detective controls.

Some of those helped. Some just moved the pain around.

Passkeys change the model.

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Rational Security in the AI Era: How Attackers Are Evolving and How We Must Respond

The weaponization of artificial intelligence by cybercriminals and nation-state actors has crossed a critical inflection point. We no longer live in a world where we can rely solely on traditional perimeters; the threat landscape has fundamentally shifted into what we might call “Extremistan,” where the speed and scale of attacks demand a completely new level of resilience.

SadKitty

At MicroSolved, our mission is to provide rational cybersecurity for an irrational world. To do that effectively, we must look unflinchingly at the data.

The Problem and the Metrics

The numbers tell a stark story of industrialization at machine speed. According to recent threat reports, AI-enabled adversaries increased their attack volume by 89% year-over-year. More concerning is the velocity: the average eCrime breakout time has collapsed to just 29 minutes, with the fastest recorded intrusion moving from initial access to lateral movement in a staggering 27 seconds.

The financial impact is equally severe. The FBI IC3 recorded over 22,000 AI-related complaints with adjusted losses exceeding $893 million in 2025 alone, including tens of millions lost to AI-enabled Business Email Compromise (BEC). AI is accelerating attack speeds by 4x, making human-speed incident response no longer viable.

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The Evidence Supply Chain: How CISOs Build a Cyber Materiality Data Plane Before the Incident

A ransomware incident does not wait for the organization chart to catch up.

At 8:17 a.m., the SOC sees encryption activity on a file server. At 8:31, operations says the plant is still running. At 8:44, finance says revenue recognition may be affected if order processing stays down past noon. At 9:02, legal asks whether customer data was accessed. At 9:18, the forensic team says it is too early to tell. At 9:23, a vendor says the outage may have started in their environment. At 9:41, communications asks whether they should prepare a holding statement.

By hour two, everyone is working hard.

But they are not necessarily working from the same reality.

That is the problem.

Cyber materiality is often discussed as a decision problem. When does a cyber event become a board-level business event? When does it become reportable? When does it become material to investors, customers, regulators, lenders, or strategic partners?

Those are important questions. Public companies, for example, must disclose material cybersecurity incidents on Form 8-K within four business days after determining materiality, including the material aspects of the incident’s nature, scope, timing, and impact or reasonably likely impact.

But underneath that decision sits a deeper problem:

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AI Agents Are Already Working for You. Who’s Managing Them?

AI Agents Are Not Applications. They Are Digital Workers.

Most organizations are adopting AI agents faster than they are learning how to govern them.

That is the problem.

A chatbot that answers questions is one thing. An AI agent that can access business data, use tools, trigger workflows, generate artifacts, make recommendations, or alter enterprise state is something else entirely.

At that point, the organization is no longer just deploying software.

It is introducing a new kind of operational actor.

That actor needs identity.

It needs boundaries.

It needs oversight.

It needs evidence.

It needs a human owner.

It needs a kill switch.

In other words, AI agents must be managed more like digital workers than ordinary applications.

AIAgentBanner

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Rethinking Account Lockouts: Why 15 Minutes Isn’t a Strategy

There’s a moment in almost every security program where someone asks a deceptively simple question:

“Is 15 minutes a standard account lockout duration?”

The short answer? No.
The more honest answer? It’s common—but often wrong for the environment it’s deployed in.

And I’ve seen more than a few organizations learn that the hard way.

3Errors


The Myth of the “Standard” Lockout

If you go looking for authoritative guidance—from Center for Internet SecurityFFIEC, or CISA—you’ll notice something interesting:

They don’t tell you what number to use.

Instead, they consistently emphasize:

  • Risk-based decision making
  • Balancing usability and security
  • Detecting and responding to threats—not just blocking them

That’s not an accident. It’s an acknowledgment that static controls like lockouts are blunt instruments in a very dynamic threat landscape.


What We Actually See in the Real World

Across environments—financial services, healthcare, SaaS, manufacturing—the patterns are pretty consistent:

Setting Typical Range
Failed attempts before lockout 3–10
Lockout duration 5–30 minutes
Most common default 10–15 minutes

So yes, 15 minutes sits comfortably in the middle.

But “common” and “effective” are not the same thing.


Where 15 Minutes Breaks Down

1. It Punishes Users More Than Attackers

A 15-minute lockout sounds reasonable—until you multiply it.

  • A clinician locked out mid-shift
  • A call center agent missing SLAs
  • A trader unable to access systems during market hours

Now multiply that by repeated lockouts from cached credentials, mobile devices, or service accounts.

You don’t just have a security control—you have an operational problem.


2. It Doesn’t Stop Modern Attacks

Attackers have evolved. Most environments haven’t.

Today’s common attack patterns:

  • Password spraying (low-and-slow, avoids thresholds)
  • Credential stuffing (valid credentials, no lockout triggered)

A longer lockout duration doesn’t meaningfully impact either.

If anything, it gives a false sense of security while the real attack path goes untouched.


What Actually Works: A Layered Approach

This is where the conversation needs to shift—from “what’s the right number?” to “what’s the right strategy?”

1. Lockouts Are Supporting Controls—Not Primary Defenses

If you’re relying on lockouts as your main protection, you’re already behind.

At a minimum, you should be pairing with:

  • MFA everywhere it’s technically feasible
  • Conditional access (device, location, behavior)
  • Authentication throttling and smart detection

2. Tune for Risk, Not Defaults

A more balanced configuration tends to look like:

  • 5–10 failed attempts
  • 5–10 minute lockout
  • Reset counter after a defined cooldown window

This reduces user friction while still slowing down brute-force attempts.

More importantly—it acknowledges that lockouts are a speed bump, not a wall.


3. Progressive Delays Beat Hard Lockouts

One of the most underutilized strategies is progressive delay:

  • Attempts 1–2 → no delay
  • Attempts 3–5 → 30–60 second delay
  • Continued attempts → increasing delay

This approach:

  • Degrades attacker efficiency
  • Preserves user productivity
  • Avoids helpdesk spikes

It’s a far more surgical control than a blanket 15-minute lockout.


4. Detection Over Punishment

Modern security programs don’t just block—they observe.

You should be:

  • Logging all failed authentication attempts
  • Alerting on patterns (spraying, geographic anomalies)
  • Correlating identity signals across systems

Lockouts should be one signal among many—not the primary response.


Implementing This in Active Directory

Let’s get practical.

In on-prem Active Directory, you’re working primarily with Group Policy.

Recommended Baseline

In your domain or fine-grained password policy:

  • Account lockout threshold: 5–10 attempts
  • Account lockout duration: 5–10 minutes
  • Reset account lockout counter after: 10–15 minutes

Where to Configure

  • Group Policy Management Console (GPMC)
    • Computer Configuration → Policies → Windows Settings → Security Settings → Account Policies → Account Lockout Policy

Advanced Considerations

  • Use Fine-Grained Password Policies (FGPP) for high-risk accounts (admins, service accounts)
  • Monitor Event IDs:
    • 4625 (failed logon)
    • 4740 (account locked out)
  • Feed logs into your SIEM for correlation and alerting

Implementing This in Microsoft 365

In Microsoft 365, the model shifts significantly.

You don’t directly control “lockout duration” in the same way—because the platform is already applying smart lockout behavior.

Smart Lockout (Azure AD / Entra ID)

  • Automatically tracks failed attempts
  • Uses adaptive thresholds
  • Differentiates between familiar and unfamiliar locations

What You Should Do Instead

1. Enable and Enforce MFA

  • Conditional Access → Require MFA for all users (with staged rollout if needed)

2. Configure Conditional Access Policies

  • Block legacy authentication
  • Require compliant devices
  • Apply geographic restrictions where appropriate

3. Monitor Identity Signals

  • Azure AD Sign-in logs
  • Risky sign-ins and users
  • Integration with Defender for Identity / Sentinel

4. Tune Smart Lockout (if needed)

  • Default threshold is typically sufficient
  • Adjust only if you have a strong operational reason

The Bottom Line

A 15-minute lockout isn’t wrong.

It’s just incomplete.

  • ✔️ It’s common
  • ❌ It’s not a standard
  • ⚠️ It can create more operational pain than security value

The real shift is this:

Stop treating account lockouts as a primary control. Start treating them as part of a layered identity defense strategy.

Because in today’s environment, the goal isn’t just to block access.

It’s to understand it.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Update on PromptDefense Suite and AI Security Research

Last week, I discussed why and some of how we built the new PromptDefense Suite

This week, we are discussing the product’s future internally and how we might go to market. This is mainly due to two new capabilities we have built into the product. 

The first is an API and workflow automation mechanism. This allows organizations to stand up a single instance of PromptDefense and then use it to protect multiple AI/agent workflows. The code no longer has to be embedded directly in the project; instead, all defensive capabilities and logging can be accessed via an API instance. The API is robust and supports API key restrictions that tie into a rules engine, so that different workflows can have different trust models and actions pre-assigned in an audit-friendly way. 

Secondly, we have developed a licensing mechanism that covers protected workflows and skips the per-seat, per-token models that seemed too confusing for most firms looking for these kinds of tools. They told us they wanted a simpler licensing approach, and we developed a new licensing mechanism to make it easy, manageable, and auditable. Our testers have been calling it a win! 

As we continue with the beta-testing process and lock down our decisions about where the product is going, the news that drove us to create it continues to flow in. More of our clients are working on agents and AI-integrated workflows, which require this level of protection. While we continue to develop PromptDefender, we are also working to develop and release extended frameworks for AI model, agent, and product management, along with policies, procedures, and vendor risk assessment tools for these frameworks, for our vCISO clients. We’re also busy researching ongoing compliance implementation for AI workflows and agents, and should have more on that shortly. 

In the meantime, if you want to discuss AI or agent security, risk management, or other relevant topics, please reach out. We would love to talk with you and help align our modernization capabilities with your emerging needs. You can always email us at info@microsolved.com or call us at +1-614-351-1237. 

As always, thanks for reading. Stay safe out there, and stay tuned for more updates. 

From Alert Volume to Signal Yield: An Economic Framework for Measuring SOC Effectiveness

Six months after a major alert-reduction initiative, a SOC director proudly reports a 42% decrease in daily alerts. The dashboards look cleaner. The queue is shorter. Analysts are no longer drowning.

Leadership applauds the efficiency gains.

Then reality intervenes.

A lateral movement campaign goes undetected for weeks. Analyst burnout hasn’t meaningfully declined. The cost per incident response remains stubbornly flat. And when the board asks a simple question — “Are we more secure now?” — the answer becomes uncomfortable.

Because while alert volume decreased, risk exposure may not have.

This is the uncomfortable truth: alert volume is a throughput metric. It tells you how much work flows through the system. It does not tell you how much value the system produces.

If we want to mature security operations beyond operational tuning, we need to move from counting alerts to measuring signal yield. And to do that, we need to treat detection engineering not as a technical discipline — but as an economic system.

AppSec


The Core Problem: Alert Volume Is a Misleading Metric

At its core, an alert is three things:

  1. A probabilistic signal.

  2. A consumption of analyst time.

  3. A capital allocation decision.

Every alert consumes finite investigative capacity. That capacity is a constrained resource. When you generate an alert, you are implicitly allocating analyst capital to investigate it.

And yet, most SOCs measure success by reducing the number of alerts generated.

The second-order consequence? You optimize for less work, not more value.

When organizations focus on alert reduction alone, they may unintentionally optimize for:

  • Lower detection sensitivity

  • Reduced telemetry coverage

  • Suppressed edge-case detection

  • Hidden risk accumulation

Alert reduction is not inherently wrong. But it exists on a tradeoff curve. Lower volume can mean higher efficiency — or it can mean blind spots.

The mistake is treating volume reduction as an unqualified win.

If alerts are investments of investigative time, then the right question isn’t “How many alerts do we have?”

It’s:

What is the return on investigative time (ROIT)?

That is the shift from operations to economics.


Introducing Signal Yield: A Pareto Model of Detection Value

In most mature SOCs, alert value follows a Pareto distribution.

  • Roughly 20% of alert types generate 80% of confirmed incidents.

  • A small subset of detections produce nearly all high-severity findings.

  • Entire alert families generate near-zero confirmed outcomes.

Yet we often treat every alert as operationally equivalent.

They are not.

To move forward, we introduce a new measurement model: Signal Yield.

1. Signal Yield Rate (SYR)

SYR = Confirmed Incidents / Total Alerts (per detection family)

This measures the percentage of alerts that produce validated findings.

A detection with a 12% SYR is fundamentally different from one with 0.3%.

2. High-Severity Yield

Critical incidents / Alert type

This isolates which detection logic produces material risk reduction — not just activity.

3. Signal-to-Time Ratio

Confirmed impact per analyst hour consumed.

This reframes alerts in terms of labor economics.

4. Marginal Yield

Additional confirmed incidents per incremental alert volume.

This helps determine where the yield curve flattens.


The Signal Yield Curve

Imagine a curve:

  • X-axis: Alert volume

  • Y-axis: Confirmed incident value

At first, as coverage expands, yield increases sharply. Then it begins to flatten. Eventually, additional alerts add minimal incremental value.

Most SOCs operate blindly on this curve.

Signal yield modeling reveals where that flattening begins — and where engineering effort should be concentrated.

This is not theoretical. It is portfolio optimization.


The Economic Layer: Cost Per Confirmed Incident

Operational metrics tell you activity.

Economic metrics tell you efficiency.

Consider:

Cost per Validated Incident (CVI)
Total SOC operating cost / Confirmed incidents

This introduces a critical reframing: security operations produce validated outcomes.

But CVI alone is incomplete. Not all incidents are equal.

So we introduce:

Weighted CVI
Total SOC operating cost / Severity-weighted incidents

Now the system reflects actual risk reduction.

At this point, detection engineering becomes capital allocation.

Each detection family resembles a financial asset:

  • Some generate consistent high returns.

  • Some generate noise.

  • Some consume disproportionate capital for negligible yield.

If a detection consumes 30% of investigative time but produces 2% of validated findings, it is an underperforming asset.

Yet many SOCs retain such detections indefinitely.

Not because they produce value — but because no one measures them economically.


The Detection Portfolio Matrix

To operationalize this, we introduce a 2×2 model:

  High Yield Low Yield
High Volume Core Assets Noise Risk
Low Volume Precision Signals Monitoring Candidates

Core Assets

High-volume, high-yield detections. These are foundational. Optimize, maintain, and defend them.

Noise Risk

High-volume, low-yield detections. These are capital drains. Redesign or retire.

Precision Signals

Low-volume, high-yield detections. These are strategic. Stress test for blind spots and ensure telemetry quality.

Monitoring Candidates

Low-volume, low-yield. Watch for drift or evolving relevance.

This model forces discipline.

Before building a new detection, ask:

  • What detection cluster does this belong to?

  • What is its expected yield?

  • What is its expected investigation cost?

  • What is its marginal ROI?

Detection engineering becomes intentional investment, not reactive expansion.


Implementation: Transitioning from Volume to Yield

This transformation does not require new tooling. It requires new categorization and measurement discipline.

Step 1 – Categorize Detection Families

Group alerts by logical family (identity misuse, endpoint anomaly, privilege escalation, etc.). Avoid measuring at individual rule granularity — measure at strategic clusters.

Step 2 – Attach Investigation Cost

Estimate average analyst time per alert category. Even approximations create clarity.

Time is the true currency of the SOC.

Step 3 – Calculate Yield

For each family:

  • Signal Yield Rate

  • Severity-weighted yield

  • Time-adjusted yield

Step 4 – Plot the Yield Curve

Identify:

  • Where volume produces diminishing returns

  • Which families dominate investigative capacity

  • Where engineering effort should concentrate

Step 5 – Reallocate Engineering Investment

Focus on:

  • Improving high-impact detections

  • Eliminating flat-return clusters

  • Re-tuning threshold-heavy anomaly models

  • Investing in telemetry that increases high-yield signal density

This is not about eliminating alerts.

It is about increasing return per alert.


A Real-World Application Example

Consider a SOC performing yield analysis.

They discover:

  • Credential misuse detection: 18% yield

  • Endpoint anomaly detection: 0.4% yield

  • Endpoint anomaly consumes 40% of analyst time

Under a volume-centric model, anomaly detection appears productive because it generates activity.

Under a yield model, it is a capital drain.

The decision:

  • Re-engineer anomaly thresholds

  • Improve identity telemetry depth

  • Increase focus on high-yield credential signals

Six months later:

  • Confirmed incident discovery increases

  • Analyst workload becomes strategically focused

  • Weighted CVI decreases

  • Burnout declines

The SOC didn’t reduce alerts blindly.

It increased signal density.


Third-Order Consequences

When SOCs optimize for signal yield instead of alert volume, several systemic changes occur:

  1. Board reporting becomes defensible.
    You can quantify risk reduction efficiency.

  2. Budget conversations mature.
    Funding becomes tied to economic return, not fear narratives.

  3. “Alert theater” declines.
    Activity is no longer mistaken for effectiveness.

  4. Detection quality compounds.
    Engineering effort concentrates where marginal ROI is highest.

Over time, this shifts the SOC from reactive operations to disciplined capital allocation.

Security becomes measurable in economic terms.

And that changes everything.


The Larger Shift

We are entering an era where AI will dramatically expand alert generation capacity. Detection logic will become cheaper to create. Telemetry will grow.

If we continue to measure success by volume reduction alone, we will drown more efficiently.

Signal yield is the architectural evolution.

It creates a common language between:

  • SOC leaders

  • CISOs

  • Finance

  • Boards

And it elevates detection engineering from operational tuning to strategic asset management.

Alert reduction was Phase One.

Signal economics is Phase Two.

The SOC of the future will not be measured by how quiet it is.

It will be measured by how much validated risk reduction it produces per unit of capital consumed.

That is the metric that survives scrutiny.

And it is the metric worth building toward.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Hidden Cost of Compliance: Why “Checkbox Security” Fails Modern Organizations

In today’s threat landscape, simply “checking the boxes” isn’t enough. Organizations invest enormous time and money to satisfy regulatory frameworks like PCI DSS, HIPAA, ISO 27001, GDPR, and NIS2—but too often they stop there. The result? A false sense of cybersecurity readiness that leaves critical vulnerabilities unaddressed and attackers unchallenged.

Compliance should be a foundation—not a finish line. Let’s unpack why checkbox compliance consistently fails modern enterprises and how forward-looking security leaders can close the gap with truly risk-based strategies.


Compliance vs. Security: Two Sides of the Same Coin?

Compliance and security are related—but they are emphatically not the same thing.

  • Compliance is about adherence to external mandates, standards, and audits.

  • Security is about reducing risk, defending against threats, and protecting data, systems, and business continuity.

Expecting compliance alone to prevent breaches is like believing that owning a fire extinguisher will stop every fire. The checklists in PCI DSS, HIPAA, or ISO standards are minimum controls designed to reduce loss—not exhaustive defenses against every attacker tactic.

“Compliance is not security.” — Security thought leaders have said this many times, and it rings true as organizations equate audit success with risk reduction. 


Checkbox Security: Why It Fails

A compliance mindset often devolves into a checkbox mentality—complete documentation, filled-in forms, and green lights from auditors. But this approach contains several fundamental flaws:

1. Compliance Standards Lag Behind Evolving Threats

Most regulatory frameworks are reactive, built around known threats and past incidents. Cyber threats evolve constantly; sticking strictly to compliance means protecting against yesterday’s risks, not today’s or tomorrow’s. 

2. Checklists Lack Contextual Risk Prioritization

Compliance is binary—yes/no answers. But not all controls have equal impact. A firewall might be present (box ticked), yet the organization might ignore the most actively exploited vulnerabilities like unpatched software or phishing risk. 

3. Audit Success Doesn’t Equal Real-World Security

Auditors assess documentation and evidence of controls; they rarely test adversarial resilience. A compliant organization can still suffer devastating breaches because compliance assessments aren’t adversarial and don’t simulate real attacks.


Real-World Proof: Breaches Despite Compliance

Arguments against checkbox compliance sound theoretical—until you look at real breaches. Examples of organizations meeting compliance requirements yet being breached are widespread:

PCI DSS Compliance Breaches

Despite strict PCI requirements for safeguarding cardholder data, many breached organizations were technically compliant at the time of compromise. Researchers even note that no fully compliant organization examined was breach-free, and compliance fines or gaps didn’t prevent attackers from exploiting weak links in implementation. 

Healthcare Data Risks Despite HIPAA

Even with stringent HIPAA requirements, healthcare breaches are rampant. Reports show thousands of HIPAA violations and data exposures annually, demonstrating that merely having compliance frameworks doesn’t stop attackers. 


The Hidden Costs of Compliance-Only Security

When organizations chase compliance without aligning to deeper risk strategy, the costs go far beyond audit efforts.

1. Opportunity Cost

Security teams spend incredible hours on documentation, standard operating procedure updates, and audit response—hours that could otherwise support vulnerability remediation, threat hunting, and continuous monitoring. 

2. False Sense of Security

Executives and boards often equate compliance with safety. But compliance doesn’t guarantee resilience. That false confidence can delay investments in deeper controls until it’s too late.

3. Breach Fallout

When conformity fails, consequences extend far beyond compliance fines. Reputational damage, customer churn, supply chain impacts, and board-level accountability can dwarf regulatory penalties. 


Beyond Checkboxes: What Modern Security Needs

To turn compliance from checkbox security into business-aligned risk reduction, organizations should consider the following advanced practices:

1. Continuous Risk Measurement

Shift from periodic compliance assessments to continuous risk evaluation tied to real business outcomes. Tools that quantify risk exposure in financial and operational terms help prioritize investments where they matter most.

2. Threat Modeling & Adversary Emulation

Map attacker tactics relevant to your business context, then test controls against them. Frameworks like MITRE ATT&CK can help organizations think like attackers, not auditors.

3. Metrics That Measure Security Effectiveness

Move away from compliance metrics (“% of controls implemented”) to outcome metrics (“time to detect/respond to threats,” “reduction in high-risk exposures,” etc.). These demonstrate real improvements versus checkbox completion.

4. Integration of Security and Compliance

Security leaders should leverage compliance requirements as part of broader risk strategy—not substitutes. GRC (Governance, Risk, and Compliance) platforms can tie compliance evidence to risk dashboards for a unified view.


How MicroSolved Can Help

At MicroSolved, we’ve seen these pitfalls firsthand. Organizations often approach compliance automation or external consultants expecting silver bullets—but without continuous risk measurement and business context, security controls still fall short.

MicroSolved’s approach focuses on:

  • Risk-based security program development

  • Ongoing threat modeling and adversary testing

  • Metrics and dashboards tied to business outcomes

  • Integration of compliance frameworks like PCI, HIPAA, ISO 27001 with enterprise risk strategies

If your team is struggling to move beyond checkbox compliance, we’re here to help align your cybersecurity program with real-world risk reduction—not just regulatory requirements.

➡️ Learn more about how MicroSolved can help bridge the gap between compliance and true security effectiveness.


Conclusion: Compliance Is the Floor, Not the Ceiling

Regulatory frameworks remain essential—they set the minimum expectations for protecting data and privacy. But in a world of rapidly evolving threats, compliance alone can’t be the endpoint of your cybersecurity efforts.

Checkbox security gives boards comfort, but attackers don’t check boxes—they exploit gaps.

Security leaders who integrate risk measurement, continuous validation, and business alignment into their compliance programs not only strengthen defenses—they elevate security into a source of competitive advantage.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.