Your Technology Works. What Happens When Someone Uses It for Something You Didn't Intend? │ CLICBrain Weekly Briefing - Issue #26

Compliance Intelligence for Online Businesses.

What Changed. Why It Matters. What to Do Next.

Your Technology Works. What Happens When Someone Uses It for Something You Didn’t Intend?

Operational Compliance Intelligence for Internet Businesses.

Welcome to the CLICBrain Weekly Briefing – operational compliance intelligence for internet businesses from CLIClaw.com.

Each week, we identify significant privacy, AI, advertising, data governance, email marketing, and regulatory developments and focus on what they mean operationally: what systems, workflows, governance controls, and evidence organizations should examine in response.

On October 1, California Attorney General Rob Bonta announced that his office had served an investigative subpoena on OpenAI as part of an ongoing investigation involving cybersecurity incidents and risks associated with the company and its artificial intelligence models.

According to the California Department of Justice, the subpoena is part of a broader inquiry into cybersecurity incidents and risks involving the company and its models. The Attorney General said the inquiry includes concerns about whether frontier AI models may be used to enable cyberattacks during testing, development, or after deployment.

The subpoena is an investigative step. It is not a finding that OpenAI violated the law, and the announcement does not establish a new general cybersecurity requirement for AI developers. Existing California laws may still apply depending on the developer, system, conduct, and facts.

But it raises an operational question that applies well beyond frontier AI: Does your risk assessment consider not only how your technology is supposed to be used, but how it could be misused? Because a system can operate exactly as designed and still create a compliance problem when someone uses its capabilities in an unexpected, abusive, deceptive, or harmful way.

Intended Use Is Only Half of the Risk Assessment.

Organizations spend considerable time determining whether technology works.

Does the feature perform correctly?
Does the model generate the expected output?
Does the API function?
Does the automation execute?
Does the workflow produce the desired result?
Does the system meet its performance specifications?

Those are important questions. But they examine the system primarily from the perspective of an intended user.

A different question is: What could someone do with this capability that we did not intend?

That creates another operational compliance concept: MISUSE READINESS. Misuse readiness asks whether the organization has considered foreseeable ways that a system, product, feature, dataset, API, platform, or automated capability could be used to create harm, and whether controls exist when those risks become meaningful.

A useful starting point is: CAPABILITY → INTENDED USE → FORESEEABLE MISUSE → SIGNAL → CONTROL → RESPONSE

The question is not whether an organization can anticipate every possible misuse. It cannot. The question is whether reasonably foreseeable misuse is part of the governance process at all.

Take One Capability and Ask How Someone Could Misuse It.

Choose one important technology or automated capability.

It might be:

an AI model;
an API;
an automated marketing tool;
a lead-routing system;
an advertising platform;
an account-creation process;
a recommendation engine;
a data export function;
a messaging tool;
a customer-support chatbot;
an affiliate portal; or
another technology-enabled capability.

First ask: What was this designed to let someone do?

Then change perspectives.

Ask: How could someone use the same capability for something we did not intend?

Could it be used to:

impersonate someone?
automate deceptive communications?
obtain information improperly?
evade an existing control?
generate prohibited content?
scale fraudulent activity?
scrape or extract information?
manipulate another system?
create unauthorized accounts?
bypass approval?
exploit a security weakness?
conceal the identity of the real actor?

Then ask: Would we know if that happened?

And: What would happen next?

If your risk documentation describes intended functionality in detail but says little about foreseeable misuse, the risk assessment may be looking at only one side of the system.

California’s Investigation Puts Misuse Risk in Focus.

California’s October 1 announcement concerns an ongoing investigation involving cybersecurity incidents and risks associated with AI models. The Attorney General said frontier AI models can be legitimate tools for cyber defense while also raising concerns about whether those models could perpetrate or enable cyberattacks.

That distinction matters operationally. A capability may have legitimate uses and harmful uses at the same time. Consider an AI system capable of generating or analyzing code.

Its intended uses might include: DEVELOPMENT → DEBUGGING → SECURITY TESTING → CYBER DEFENSE

But some of the same underlying capabilities could potentially be directed toward harmful purposes. The governance question therefore cannot always stop at: Does the capability work? It may need to include: What happens when the capability is deliberately pointed in the wrong direction?

For organizations developing or deploying higher-risk technology, that can create a broader lifecycle: DESIGN → TEST → DEPLOY → OBSERVE → IDENTIFY MISUSE → CONSTRAIN → INVESTIGATE → ADAPT

The exact controls will vary dramatically depending on the technology and risk. But the governance principle is transferable.

The Operational Problem: Risk Testing Assumes a Cooperative User.

Imagine a company launches an automated service.

The product team tests whether legitimate customers can use it.
Engineering tests performance.
Security performs vulnerability testing.
Compliance reviews disclosures.
Legal reviews terms.
The product launches.

Everything works. But the testing model assumes users will behave approximately as expected.

Nobody asks:

What if someone creates hundreds of accounts?
What if the feature is automated at scale?
What if someone deliberately combines capabilities in an unexpected way?
What if legitimate functionality is used to facilitate fraud?
What if users discover a workaround to a restriction?
What if someone repeatedly tests the boundary of a safety control?
What if an API enables activity much faster than a human-operated interface?
What if a capability becomes more dangerous when connected to another system?

The organization tested: CAN THE USER DO WHAT WE INTENDED?

It did not test: WHAT ELSE CAN THE USER DO?

Those are different questions. And they may require different evidence.

1. Connecticut Privacy Amendments Took Effect October 1 – But Key Data-Broker Duties Phase In Later. Public Act 26-64 took effect October 1, 2026, introducing or amending requirements involving facial-recognition technology, direct-to-consumer genetic testing, surveillance pricing, precise geolocation data, profiling, publicly available information, and data brokers. The act created a data-broker registration framework, but the prohibition on selling or licensing brokered personal data without active registration begins January 1, 2027. Additional data-broker duties, including participation in the state’s centralized deletion mechanism, phase in later.

The centralized deletion mechanism must be established by July 1, 2028, and registered brokers generally begin checking and processing requests through it on October 1, 2028.

2. FTC and States Challenge Lens.com’s Online Pricing and Subscription Practices. October 2, the Federal Trade Commission, State of Nevada, and Utah Division of Consumer Protection filed a complaint against Lens.com and related defendants alleging deceptive pricing and subscription practices.

According to the complaint, Lens.com advertised low contact-lens prices in sponsored search advertisements and on its website but later imposed substantial mandatory charges labeled “Taxes & fees.” The regulators also allege problems involving the company’s AutoRefill subscription disclosures and cancellation information. These are allegations in pending litigation, not established findings.

The matter is nevertheless useful for internet businesses because it connects several parts of the consumer journey: SEARCH AD → PRODUCT PAGE → CHECKOUT → MANDATORY FEE → SUBSCRIPTION → CANCELLATION. Pricing compliance should not be reviewed one screen at a time. The consumer experiences the entire path.

3. New National Do Not Call Registry Fees Took Effect October 1. Fiscal Year 2027 fees for access to the National Do Not Call Registry became effective October 1. The annual fee is now $85 per area code after the first five area codes, which remain free. The maximum charge for nationwide access is $23,425, and the fee for adding an area code during the second half of an annual subscription period is $43.

For organizations conducting covered telemarketing, this is primarily an administrative compliance update. But it is also a useful reminder to confirm that Registry access, subscriptions, suppression processes, responsible personnel, and supporting documentation remain current.

CLICBrain’s Operational Framework.

Misuse Readiness Is Not the Same as Testing.

This distinction matters.

TESTING asks: Does the control or system actually work?
MONITORING asks: Can we see what is happening after deployment?
ESCALATION asks: What happens when monitoring identifies meaningful risk?
MISUSE READINESS asks: Have we considered what someone might deliberately do with the capability that we did not intend?

A system can pass every ordinary functional test and still perform exactly as instructed for someone using it improperly. Consider:

ACCOUNT CREATION:

Intended use → Create a legitimate customer account.

Possible misuse → Create large numbers of accounts for fraud or evasion.

LEAD PLATFORM:

Intended use → Route legitimate consumer inquiries.

Possible misuse → Inject fabricated or improperly sourced leads at scale.

GENERATIVE AI:

Intended use → Assist with content, analysis, coding, or research.

Possible misuse → Generate or automate harmful activity.

AFFILIATE PORTAL:

Intended use → Give approved publishers campaign materials.

Possible misuse → Use those materials in prohibited campaigns or redistribute access.

DATA EXPORT:

Intended use → Allow authorized business use of information.

Possible misuse → Extract information beyond the legitimate purpose.

The legal consequences will depend on the facts and applicable law. The operational question comes first: Have we mapped the misuse scenario at all?

“That’s Not What the Feature Was Designed For.”

That may be completely true. But design intent does not necessarily describe actual use.

Once technology is deployed, users may:

combine features;
automate activity;
discover workarounds;
exploit scale;
share credentials;
create multiple accounts;
connect external tools;
manipulate inputs;
ignore intended workflows; or
deliberately test system boundaries.

The relevant governance question may therefore become: When did the organization become aware that the capability could be used differently from how it was intended?

And then: What did it do with that information?

A credible misuse-readiness process does not require predicting every creative misuse before launch. It requires a way to recognize when assumptions about use are no longer reliable.

✔ CLIClaw Compliance Tip: Document intended use and foreseeable misuse separately. “Not intended” and “not foreseeable” are not necessarily the same thing.

Run One Misuse Scenario.

Do not conduct a company-wide threat-modeling exercise this week. Choose one meaningful capability.

Then document:

What can the system actually do?
INTENDED USER. Who is supposed to use it?
INTENDED PURPOSE. What are they supposed to accomplish?
MISUSE SCENARIO. What is one reasonably foreseeable way someone could use the capability improperly?
Could automation, APIs, multiple accounts, or other technology increase the impact?
What information might indicate that the misuse is occurring?
What could constrain, interrupt, or limit it?
Who evaluates the issue?
What happens if the risk is confirmed?

The resulting workflow looks like: CAPABILITY → INTENDED USE → MISUSE SCENARIO → SIGNAL → CONTROL → OWNER → RESPONSE.

Then ask: Where is this documented? If the answer exists only in the head of an engineer, security analyst, product manager, or compliance officer, the organization may understand the risk without yet having a governance process for it.

Q: How are we supposed to anticipate ways people might misuse a technology we haven’t even seen yet?

CLICBrain: You probably cannot anticipate every misuse. That should not be the objective. Start with capabilities rather than trying to imagine every possible bad actor.

Ask: What can the system do?
Then: Which of those capabilities could create material harm if used for a different purpose, at unusual scale, or by someone with malicious intent?
Next identify what would help the organization recognize that the operating assumptions have changed.

A practical framework is: CAPABILITY → MISUSE SCENARIO → INDICATOR → CONTROL → RESPONSE → LEARNING

The last step matters.

A misuse-readiness program should be able to learn from:

incidents;
attempted abuse;
customer complaints;
security findings;
unusual usage patterns;
employee reports;
external research;
regulator inquiries; and
newly discovered techniques.

Those developments may reveal misuse scenarios that were not reasonably apparent when the system launched. The objective is therefore not: Predict everything. It is: Build a process capable of learning when reality exposes a new risk.

✔ CLIClaw Compliance Tip: A risk assessment should be capable of changing when the organization learns something new about how its technology can actually be used.

Have another compliance question? Ask CLICBrain on CLIClaw.com.

One Question to Take With You.

Choose one powerful capability your organization provides to customers, users, employees, vendors, affiliates, or developers.

You probably know: What was it designed to do?

Now ask: What could someone make it do?

And then: Would we know if they did?

If those questions are difficult to answer, that may be where you would start this week’s review.

CLICBrain Weekly Briefings provide operational compliance intelligence and commentary for internet businesses. Regulatory developments, enforcement activity, and legal requirements discussed herein should be evaluated in the context of your organization’s specific operations, systems, data practices, jurisdictions, and risk profile. This briefing is for informational and educational purposes only and does not constitute legal advice.

Your Technology Works. What Happens When Someone Uses It for Something You Didn’t Intend? │ CLICBrain Weekly Briefing – Issue #26

Compliance Intelligence for Online Businesses.

What Changed. Why It Matters. What to Do Next.

Your Technology Works. What Happens When Someone Uses It for Something You Didn’t Intend?

Operational Compliance Intelligence for Internet Businesses.

Welcome to the CLICBrain Weekly Briefing – operational compliance intelligence for internet businesses from CLIClaw.com.

Each week, we identify significant privacy, AI, advertising, data governance, email marketing, and regulatory developments and focus on what they mean operationally: what systems, workflows, governance controls, and evidence organizations should examine in response.

On October 1, California Attorney General Rob Bonta announced that his office had served an investigative subpoena on OpenAI as part of an ongoing investigation involving cybersecurity incidents and risks associated with the company and its artificial intelligence models.

The subpoena is an investigative step. It is not a finding that OpenAI violated the law, and the announcement does not establish a new general cybersecurity requirement for AI developers. Existing California laws may still apply depending on the developer, system, conduct, and facts.

Intended Use Is Only Half of the Risk Assessment.

Organizations spend considerable time determining whether technology works.

Does the feature perform correctly?

Does the model generate the expected output?

Does the API function?

Does the automation execute?

Does the workflow produce the desired result?

Does the system meet its performance specifications?

Those are important questions. But they examine the system primarily from the perspective of an intended user.

A different question is: What could someone do with this capability that we did not intend?

A useful starting point is: CAPABILITY → INTENDED USE → FORESEEABLE MISUSE → SIGNAL → CONTROL → RESPONSE

The question is not whether an organization can anticipate every possible misuse. It cannot. The question is whether reasonably foreseeable misuse is part of the governance process at all.

Take One Capability and Ask How Someone Could Misuse It.

Choose one important technology or automated capability.

It might be:

an AI model;

an API;

an automated marketing tool;

a lead-routing system;

an advertising platform;

an account-creation process;

a recommendation engine;

a data export function;

a messaging tool;

a customer-support chatbot;

an affiliate portal; or

another technology-enabled capability.

First ask: What was this designed to let someone do?

Then change perspectives.

Ask: How could someone use the same capability for something we did not intend?

Could it be used to:

impersonate someone?

automate deceptive communications?

obtain information improperly?

evade an existing control?

generate prohibited content?

scale fraudulent activity?

scrape or extract information?

manipulate another system?

create unauthorized accounts?

bypass approval?

exploit a security weakness?

conceal the identity of the real actor?

Then ask: Would we know if that happened?

And: What would happen next?

If your risk documentation describes intended functionality in detail but says little about foreseeable misuse, the risk assessment may be looking at only one side of the system.

California’s Investigation Puts Misuse Risk in Focus.

That distinction matters operationally. A capability may have legitimate uses and harmful uses at the same time. Consider an AI system capable of generating or analyzing code.

Its intended uses might include: DEVELOPMENT → DEBUGGING → SECURITY TESTING → CYBER DEFENSE

But some of the same underlying capabilities could potentially be directed toward harmful purposes. The governance question therefore cannot always stop at: Does the capability work? It may need to include: What happens when the capability is deliberately pointed in the wrong direction?

For organizations developing or deploying higher-risk technology, that can create a broader lifecycle: DESIGN → TEST → DEPLOY → OBSERVE → IDENTIFY MISUSE → CONSTRAIN → INVESTIGATE → ADAPT

The exact controls will vary dramatically depending on the technology and risk. But the governance principle is transferable.

The Operational Problem: Risk Testing Assumes a Cooperative User.

Imagine a company launches an automated service.

The product team tests whether legitimate customers can use it.

Engineering tests performance.

Security performs vulnerability testing.

Compliance reviews disclosures.

Legal reviews terms.

The product launches.

Everything works. But the testing model assumes users will behave approximately as expected.

Nobody asks:

What if someone creates hundreds of accounts?

What if the feature is automated at scale?

What if someone deliberately combines capabilities in an unexpected way?

What if legitimate functionality is used to facilitate fraud?

What if users discover a workaround to a restriction?

What if someone repeatedly tests the boundary of a safety control?

What if an API enables activity much faster than a human-operated interface?

What if a capability becomes more dangerous when connected to another system?

The organization tested: CAN THE USER DO WHAT WE INTENDED?