The Leak Is Already Outside: Build an External Exposure Response Loop

The DLP dashboard is green.

Repository push protection is enabled. The approved file-sharing platform blocks public links. Managed laptops prevent copying sensitive files to removable media. The security team can point to policies, controls, alerts, and training.

Then someone finds a current API key in a public repository.

Or a configuration file in a support forum. A source-code fragment in a paste. An internal hostname in a public issue. A customer data sample in a forgotten cloud share. A credential in a contractor’s fork.

The organization did not see the information leave.

That does not make the exposure less real.

This is the gap between data-loss prevention and external-exposure response. Prevention controls watch selected systems, users, repositories, interfaces, and transfer paths. They are necessary. They are not proof that sensitive information never crossed a path the organization could not see.

The practical lesson is simple:

A data-protection program is incomplete until it can find, neutralize, and learn from sensitive information that is already outside the managed boundary.

SecurityReporting

Prevention Sees the Paths It Controls

Organizations should prevent sensitive data from leaving in the first place.

That includes classifying information, limiting access, using secrets managers, scanning source code, blocking known secret patterns, controlling file sharing, monitoring managed endpoints, and reducing the lifetime and authority of credentials.

The joint CISA and FBI guidance on Product Security Bad Practices identifies hardcoded credentials and secrets in source code as a dangerous practice for products used in critical infrastructure and recommends secrets managers and scanning within the development process.

GitHub provides another useful example. Its secret-security guidance distinguishes push protection, which attempts to stop supported secrets before they enter a repository, from secret scanning and public monitoring, which identify exposures that already exist. GitHub describes public monitoring as visibility into credentials exposed beyond repositories owned by the enterprise.

That distinction matters.

Preventive and detective controls are not interchangeable. One attempts to stop the event. The other assumes prevention can fail and looks for evidence afterward.

Even strong platform controls have scope. GitHub’s own secret-scanning documentation describes supported patterns, pair-matching conditions, legacy-token limitations, large-push conditions, and other cases in which push protection may not detect or block a secret.

That is not an argument against push protection.

It is an argument against treating any point control as proof of absence.

Public repositories are only one possible destination. Sensitive material can also appear in support portals, issue trackers, package artifacts, code forks, shared folders, archived pages, discussion sites, and third-party systems. Some of those channels belong to the organization. Others do not. Some produce useful logs. Others may provide only a timestamp, a URL, and a copy of what was exposed.

The control model must account for both conditions:

  1. Prevent what can be prevented inside managed workflows.
  2. Monitor and respond where prevention cannot provide complete visibility.

Treat External Exposure as Incident Evidence

Finding sensitive material outside the organization is not merely a content-cleanup task.

It may be evidence of an incident.

An exposed credential may still authorize access. A configuration may reveal trust relationships, administrative interfaces, naming conventions, or control gaps. Source code may disclose intellectual property, security assumptions, embedded secrets, or exploitable implementation details. A customer record may trigger privacy, contractual, legal, or regulatory obligations. A seemingly harmless internal identifier may help an attacker improve targeting.

The correct response depends on what the artifact can do, what it reveals, how current it is, and who may have obtained it.

This is why deletion alone is not containment.

Removing a repository, post, attachment, or cached page can reduce continuing exposure. It does not invalidate a credential, erase copies, reverse indexing, identify prior access, or prove that the information was never used.

For secrets, the priority is authority.

The OWASP Secrets Management Cheat Sheet recommends that secrets be revocable, rotated, limited in lifetime and privilege, and supported by lifecycle records that help responders understand who had access and when the secret was used or changed. Stopping the application or deleting the exposed file does not necessarily revoke the credential behind it.

For other data classes, the priority may be different. The organization may need to preserve evidence, restrict further access, notify an owner, assess contractual scope, request removal, investigate misuse, or determine whether the material exists in additional locations.

The external artifact is the beginning of the response question, not the end.

Build the External Exposure Response Loop

A practical external-exposure capability has five stages: discover, classify, neutralize, trace, and learn.

1. Discover: What is visible outside the boundary?

Define the sensitive artifacts the organization cares enough to recognize.

The list may include:

  • Credentials, tokens, private keys, and connection strings.
  • Source code and proprietary algorithms.
  • Device, cloud, application, and network configurations.
  • Internal domains, hostnames, project names, and administrative paths.
  • Customer, employee, regulated, or contractually protected data.
  • Documents carrying distinctive identifiers, watermarks, or structured patterns.

Then define the monitoring scope, frequency, owners, escalation path, and evidence-handling requirements for each class.

No discovery method sees the entire internet. A useful program therefore states its coverage and blind spots explicitly. It distinguishes continuous monitoring from periodic searches, platform-native scanning from broader exposure monitoring, and confirmed findings from possible matches that still require analyst validation.

The goal is not to claim universal visibility.

The goal is to reduce the period during which a consequential exposure remains unknown.

2. Classify: What can the artifact enable?

Do not prioritize solely by how embarrassing the artifact looks.

Classify it by authority, sensitivity, current validity, exploitability, reach, and affected business process.

Ask:

  • Is this an active secret, an expired secret, or a string that only resembles one?
  • What systems, data, funds, or actions could it authorize?
  • Is the artifact complete enough to use, or does it become dangerous when combined with other information?
  • Is the exposed copy current, historical, partial, or modified?
  • Does it contain regulated data, customer information, trade secrets, or security architecture details?
  • Is it publicly accessible, indexed, cached, mirrored, or limited to a narrower audience?
  • Who owns the asset and who has authority to contain it?

The fastest path to a good decision is a prepared owner map. Security should not discover during the incident that nobody knows who can rotate the key, suspend the integration, contact the platform, interpret the contract, or decide whether operations can tolerate emergency change.

3. Neutralize: Remove authority before chasing every copy

If an exposed artifact grants access, invalidate that authority first.

Revoke the token. Rotate the key. Terminate sessions. Disable the account. Restrict the affected interface. Replace the certificate. Narrow the permission. Add temporary monitoring or access controls while the permanent change is implemented.

Then address continuing availability of the artifact through the appropriate channel: delete an owned copy, request removal, use an established takedown process, restrict a share, or work with the platform or third party that hosts it.

Containment order matters.

If responders spend hours removing a public page while the exposed credential remains valid, they are reducing visibility without reducing authority. A downloaded copy can still work.

The neutralization plan must also account for dependencies. Rotating one secret may break applications, vendors, automated jobs, recovery processes, or downstream services. That is a reason to engineer revocation and replacement paths before an incident, not a reason to keep exposed authority alive.

4. Trace: How did it get there, and what happened next?

Once the immediate risk is controlled, reconstruct the path.

Determine:

  • Where the artifact originated.
  • Which person, system, process, or third party handled it.
  • When it became exposed and when the organization discovered it.
  • Whether logs show access, authentication, downloading, reuse, or related activity.
  • Whether the same material exists in forks, mirrors, archives, tickets, backups, chat systems, or build artifacts.
  • Whether similar artifacts were created by the same workflow.
  • Whether an attacker could combine the finding with other public information.

NIST SP 800-61 Rev. 3 frames incident response as part of cybersecurity risk management rather than a stand-alone activity and connects preparation, detection, response, and recovery. External-exposure work should follow the same logic. The team needs enough evidence to reduce immediate impact and improve the system that allowed the exposure.

Tracing must remain proportionate. Not every public identifier justifies a full forensic investigation. Not every old credential remains usable. The classification stage should drive the depth of response.

5. Learn: Which control or assumption failed?

The last stage converts a one-time cleanup into program improvement.

An exposure may reveal:

  • A secret embedded in code because the approved retrieval method was too difficult.
  • A repository that did not inherit the organization’s security configuration.
  • A contractor or vendor using an unmanaged development workflow.
  • Sensitive troubleshooting data copied into a support channel.
  • A DLP policy that covered endpoints but not build logs or cloud collaboration.
  • A credential with excessive privilege or no practical rotation process.
  • A data classification rule that employees could not apply to real work.
  • An alert that reached a mailbox nobody owned.

Fix the common cause, not only the visible artifact.

The question is not simply, “Did we remove it?”

The better question is, “What changed so that the same process is less likely to expose the next artifact?”

Prioritize Authority, Exposure, and Business Consequence

External findings need a decision model.

A useful triage approach considers three dimensions.

Authority

What can the artifact authorize or enable?

An active administrative credential, signing key, production token, or remote-access configuration may require immediate containment. A disabled test credential may require documentation and process correction without the same urgency.

Exposure

Who could obtain it, and for how long?

Public, indexed, and mirrored content has a different exposure profile from a restricted ticket available to a small support team. However, restricted does not mean safe. Third-party access, retention, forwarding, and account compromise still matter.

Business consequence

What could happen if the information is used or disclosed?

Consider system control, customer harm, financial movement, service disruption, regulatory scope, intellectual property, safety, contractual commitments, and reputational impact.

These dimensions prevent two common mistakes.

The first is treating every match as a crisis.

The second is treating a small-looking artifact as harmless when it carries substantial authority.

Measure the Response, Not Just the Number of Hits

Raw alert volume is a weak success measure.

More useful measures include:

  • Time from external publication to discovery.
  • Time from discovery to owner acknowledgement.
  • Time to invalidate active authority.
  • Time to determine the affected systems and data.
  • Percentage of high-impact secrets with a tested emergency rotation path.
  • Percentage of material findings with preserved evidence and documented disposition.
  • Recurrence rate by workflow, business unit, vendor, repository, or artifact type.
  • Percentage of monitoring patterns with a named owner and review date.
  • Number of findings that produced a control, process, or architecture improvement.
  • Percentage of high-risk exposures for which misuse could be assessed from available logs.

One metric deserves special attention:

How long does it take to make a discovered artifact harmless?

Discovery creates the opportunity to respond.

Neutralization changes the risk.

Where ClawBack Fits

MicroSolved currently positions ClawBack™ as a data-leak detection capability supporting exposure monitoring, advisory retainers, and vCISO relationships, with evidence that can support response conversations.

That is the right place for external-exposure monitoring in the operating model.

Its job is not to replace DLP, repository controls, secrets management, identity governance, incident response, or legal and privacy review. It helps close the visibility gap between what internal controls observed and what may be visible outside the organization.

The value of a finding depends on the process around it:

  • What classes of information are in scope?
  • Which sources and channels are monitored?
  • How are possible matches validated?
  • Who owns each artifact class?
  • What evidence is preserved?
  • What requires immediate escalation?
  • How will credentials be revoked, files removed, and downstream impact assessed?
  • How will lessons feed back into prevention?

ClawBack should therefore be treated as part of an exposure-response capability, not as an isolated alert feed.

What Security Leaders Should Do This Week

Choose one artifact class with meaningful business consequence: production API keys, administrative credentials, network configurations, source code, customer records, or another clearly owned data set.

Then run this exercise:

  1. Define what a recognizable exposure looks like. Identify patterns, identifiers, owners, and likely external channels.
  2. Document current coverage. Record which preventive and detective controls can see the artifact, and which paths remain outside their scope.
  3. Prepare the owner map. Name the people who can classify the finding, revoke authority, approve operational impact, preserve evidence, request removal, and assess notification obligations.
  4. Test neutralization. Measure how long it takes to revoke or replace the artifact without creating uncontrolled business disruption.
  5. Simulate one discovery. Walk the finding through discover, classify, neutralize, trace, and learn.
  6. Verify the logs. Confirm that responders can determine whether the artifact was used and which systems were affected.
  7. Close one recurring path. Improve the workflow most likely to produce the same exposure again.

Data-loss prevention is important.

Secret scanning is important.

Repository protection is important.

None of them can prove that sensitive information is absent from every external place the organization does not control.

Build the response loop for the moment the leak is already outside.


Put External Exposure Monitoring Into the Security Program

MicroSolved, Inc. can help organizations:

  • Define external-exposure monitoring requirements for credentials, source code, configurations, and other sensitive artifacts.
  • Integrate ClawBack findings into vCISO, advisory, and incident-response workflows.
  • Build artifact classification, ownership, escalation, and evidence-handling processes.
  • Test credential revocation, session termination, takedown, and downstream-impact procedures.
  • Review DLP, repository, secrets-management, vendor, and cloud-collaboration control gaps.
  • Turn recurring exposures into practical control and process improvements.

To discuss ClawBack or an external-exposure response review, 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.

 

Authentication Is Not the Finish Line: Secure the Token Lifecycle

A user signs in with a passkey. The authentication is phishing-resistant. The identity provider records a successful challenge. Every dashboard says the login worked as designed.

Hours later, an attacker reuses a stolen session token.

No password is entered. No push notification appears. No new authentication ceremony occurs. The application sees a valid artifact and accepts it.

Both facts can be true at the same time: the authentication was strong, and the session was compromised.

That is the identity problem security programs need to address next.

Passkeys, hardware security keys, conditional access, and stronger account recovery are essential. They protect the process of establishing identity. But modern applications rarely ask a person or workload to prove identity again for every action. They rely on tokens and assertions that carry the result of an earlier decision across applications, APIs, clouds, and sessions.

The security boundary therefore does not end at login. It moves with the token.

NIST and CISA made that point operational in the final September 2026 release of NIST IR 8587, Protecting Tokens and Assertions from Forgery, Theft, and Misuse. The report addresses the keys that create trust, the systems that validate it, the lifetime of tokens, session monitoring, revocation, workload identity, and the division of responsibility between cloud providers and their customers.

The practical lesson is straightforward:

Treat every token as a live authorization decision, not as a receipt proving that authentication once succeeded.

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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.

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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.

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Incident Response Has a Hidden Assumption

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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.

A 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.

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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.

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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.

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The Myth of the “Standard” Lockout

If you go looking for authoritative guidance—from Center for Internet Security, FFIEC, 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.