Lately, software developers have been baking AI features straight into everyday work tools, operating systems, and browsers. In some cases, they’re genuinely handy. However, their presence introduces specific risks, which means plenty of companies are hesitant to give employees access to these tools. In a previous post, we categorized these unwanted AI systems, looked at how to spot them at the network and endpoint levels, and covered the ultimate universal kill switch: managing OAuth access across major corporate platforms. In this deep dive, we’re getting tactical: breaking down how to disable or restrict the AI built into popular platforms.

A quick heads-up: major software vendors occasionally change the names of their AI settings and tweak how they function. If any of the options mentioned below are missing or aren’t working as expected, a quick web search for the setting’s name will usually point you to its new location or branding.

How to turn off Microsoft 365 Copilot

Detection: you can check actual Copilot usage in the logs by going to Microsoft 365 admin →  Copilot usage report.

Disabling via policies: in the Microsoft 365Admin Center, go to Settings →  Integrated Apps, find Copilot in the Available Apps list, and select Block. More granular configuration policies are available under Customization →  Policy Management. The Policies page here contains over two thousand entries, so you’ll want to filter them by the keyword “Copilot” (detailed guide). Given that Copilot is a paid add-on for Office, another way to block it — and save money by doing so — is to simply avoid assigning users SKUs that include Copilot.

We recommend separately blocking Copilot Chat, which is available in Teams, Edge, Outlook, and several other services. Yes, it’s not Copilot itself. And yes, it has to be blocked separately by following this guide.

Additional layer of protection: you can block the domains copilot.cloud.microsoft and m365.cloud.microsoft/chat at the web filter or NGFW level. However, Microsoft explicitly advises against this, warning that it could break other Microsoft 365 features.

How to turn off Windows Copilot

Beyond the Office version of Copilot, you also need to manage its consumer-facing cousin.

Detection: look through your NGFW or other network logs for traffic hitting copilot.microsoft.com, bing.com/chat, or edgeservices.bing.com.
Disabling via policies: in Windows Group Policy, navigate to Computer Config →  Admin Templates →  Windows Components →  Windows Copilot. In Microsoft 365 Group Policy, go to Admin center →  Block consumer Copilot for organizational accounts.

Additional layer of protection: block the Copilot.exe executable from running entirely.

How to turn off the Copilot sidebar in Edge

Detection: look through your NGFW or other network logs for traffic hitting copilot.microsoft.com, bing.com/chat, or edgeservices.bing.com.

Blocking: configure the following MS Edge Group Policies: HubsSidebarEnabled = false, EdgeShoppingAssistantEnabled = false, CopilotPageContext = Disabled (false), CopilotNewTabPageEnabled = false, Microsoft365CopilotChatIconEnabled = false, GenAILocalFoundationalModelSettings = 1 (note that disabling this unexpectedly requires a 1 instead of a 0).

Second layer of protection: block the domains copilot.cloud.microsoft and m365.cloud.microsoft/chat at the web filter or NGFW level. However, Microsoft explicitly advises against this, warning that it could break other features.

How to turn off the Gemini Assistant in Google Workspace

Detection: check the Workspace Admin Console (admin.google.com), Gemini usage report section.

Blocking via policies: in the Admin Console, navigate to Apps →  Additional Google services → > Gemini app, and set it to OFF. Then, go to Manage Workspace smart feature settings →  Smart features in Google Workspace, and set it to OFF.

Second layer of protection: block network traffic to the domains gemini.google.com, bard.google.com, and aistudio.google.com.

How to turn off Gemini in Google Chrome

Detection: check your Chrome Enterprise reports (Chrome management →  Reports), or look through network traffic logs for connections to the previously mentioned domains.

Blocking via policies: in your Chrome Enterprise policies, configure the following settings: GenAILocalFoundationalModelSettings = 0, HelpMeWriteSettings = 2 (disabled), TabOrganizerSettings = 2, CreateThemesSettings = 2, DevToolsGenAiSettings = 2.

Additional layer of protection: block network traffic to the domains gemini.google.com, bard.google.com, and aistudio.google.com. Additionally, block unauthorized Chrome/Chromium installations (those outside your policy management) with the help of host-based application control tools like EPP/EDR or AppLocker.

How to turn off Apple Intelligence

Detection: on your NGFW and web filters, traffic hitting apple-relay.apple.com and *.apple-cloudkit.com is a clear indicator that Apple Intelligence is active.

Blocking via policies: any managed Apple device allows you to disable individual AI features, though there isn’t a master switch you can flip to shut down “all AI”. In your MDM profile, you need to set the following keys to false (disabled): allowWritingTools, allowMailSummary, allowGenmoji, allowImagePlayground, allowImageWand, allowPersonalizedHandwritingResults, allowExternalIntelligenceIntegrations, allowExternalIntelligenceIntegrationsSignIn, allowNotesTranscription, and allowNotesTranscriptionSummary. Here is a brief configuration example:

<dict>
<key>PayloadType</key>
<string>com.apple.applicationaccess</string>
<key>allowWritingTools</key>
<false/>
<key>allowMailSummary</key>
<false/>
</dict>

Despite Apple’s shift toward declarative device management, these AI features still need to be managed through traditional MDM payload settings.

Second layer of protection: block network traffic to the hosts mentioned above — though the obvious downside for mobile devices is that this won’t work once they leave the corporate network.

According to global research, the market share of highly automated, driverless vehicles is growing rapidly. Analysts estimate that the next 10 to 15 years will mark a major shift from pilot projects to the mass adoption of autonomous transport. The momentum is building worldwide: Europe has already rolled out over 35 autonomous vehicle pilots, while the U.S. and China log more than 450 000 and 250 000 commercial trips per week, respectively. However, the report notes several roadblocks slowing down this progress. One such hurdle is the uncertainty surrounding legal liability and regulation, including in the areas of safety and security. The allocation of responsibility among suppliers, manufacturers, enterprise clients, and end users remains a major point of discussion.

Each market stakeholder sees the issue of ensuring the safety of autonomous vehicles differently. For automakers, it means taking responsibility for how a vehicle behaves on the road and for vetting their suppliers. For the suppliers themselves, it means designing security mechanisms directly into their solution architecture from day one and guaranteeing their adequacy. For insurance companies, it means completely overhauling their risk models to account for not just accidents, but also potential software glitches and cyberattacks. Ultimately, everyone agrees on one fundamental point: security must be a foundational feature of the vehicle — not an optional add-on.

Ensuring vehicle security in the modern era

For years, discussions around automotive safety focused strictly on functional safety. In other words, the goal was to ensure that vehicle systems operated correctly, and that risks associated with potential failures were fully mitigated or reduced to an acceptable level. The ISO 26262 standard “Road vehicles — Functional safety” helps address this very challenge, and serves as the baseline for the automotive industry.

However, the modern connected vehicle is a complex cyberphysical system that stores and processes massive amounts of data, including sensitive information. And this leads to the emergence of new basic needs. To draw an analogy with two levels of Maslow’s hierarchy of needs, a modern vehicle must:

• Satisfy the need for “esteem” — meaning it must securely and reliably store user profile data, such as account credentials, biometric data, payment details, and more.
• Satisfy the user’s cognitive needs — meaning it must provide secure internet connectivity, transmit vehicle telemetry, and send reminders for scheduled or emergency maintenance.

All of this means equipping vehicles with a wide array of interfaces — telematics, Bluetooth, Wi-Fi, cellular connectivity, OTA updates, and V2X — which opens the door to remote attacks. Therefore, it becomes necessary to ensure not only the functional security, but also the information security of the vehicle. As a result, specialized industry standards that help address automotive cybersecurity challenges have emerged in most countries. The key international standards are ISO/SAE 21434 “Road vehicles — Cybersecurity engineering”, UNECE R155, and UNECE R156.

China’s regulations are evolving too. In 2024, the country published the national standard GB 44495-2024 “Technical Requirements for Vehicle Cybersecurity”, which went into effect on January 1, 2026. The document introduces mandatory cybersecurity requirements for vehicles, including communications protection, security event management, threat monitoring, and secure vehicle interaction with external infrastructure.

Understanding and applying these standards is becoming absolutely critical. Research shows that cybersecurity risks are escalating daily, and their impact on functional safety can sometimes trigger far more dangerous incidents than an internal system failure. What happens if an attacker gains access to a self-driving truck’s remote-control system, or manages to reflash a critical electronic control unit during an unauthorized diagnostic session?

One of the key components for mitigating these scenarios is a security gateway, which isolates the vehicle’s architecture into different domains based on criticality, while providing secure routing, filtering, and traffic control. Developing this type of software solution is precisely what our team focuses on as we build the Kaspersky Automotive Secure Gateway based on KasperskyOS.

Why Kaspersky Automotive Secure Gateway?

The primary purpose of Kaspersky Automotive Secure Gateway (KASG) is to secure the vehicle’s CAN domain, since the CAN bus is used to transmit a vast number of critical control commands. This impacts nearly 80% of the electronic control units inside the car, which handle engine management, braking, body electronics, and more. Because of this, we utilize the Safety-Aware Cybersecurity approach — a unified architecture that accounts for both functional safety and cybersecurity requirements.

For example, standard End-to-End Protection (E2E) mechanisms are typically used to mitigate risks associated with dropped, out-of-order, or corrupted CAN messages. However, these mechanisms were not originally designed to counter targeted cyberattacks. If an attacker manages to construct a malicious frame that conforms to the required E2E format, the system may accept it as valid.

This introduces a new factor: it’s critical not only to verify that a message was delivered without errors, but also to ensure that it was actually generated by a trusted electronic control unit (ECU), and was not altered in transit. This is particularly vital for transmitting control commands — such as those sent to the vehicle’s braking system — or for implementing keyless entry (NFC) systems.

To address that challenge, Secure Onboard Communication (SecOC) mechanisms are integrated into the vehicle’s architecture. They use cryptographic methods to verify message authenticity and integrity, protecting the system against message spoofing and replay attacks. KASG successfully implements these mechanisms, which, in addition to message verification, perform the crucial function of centralized key management. This allows encryption keys to be distributed and updated from a single point within the vehicle, reducing both the cost and the processing load on the ECUs involved in SecOC-backed data exchange.

Automotive IDS

However, in complex systems, it’s no longer enough to apply security mechanisms only to individual messages or separate network segments. It’s essential to provide vehicle-wide monitoring and control, tracking behavioral anomalies, unusual cross-domain interactions, and unauthorized tampering attempts. In the IT domain, this is known as an Intrusion Detection System (IDS). These systems have been successfully adopted by the automotive industry as well.

At the same time, it’s important to realize that for a modern vehicle, an IDS is not a single magic point of data collection and analysis; the vehicle requires a distributed monitoring system. Monitoring is carried out at various architectural levels: within domains, at the individual controller level, and at network boundaries.

The security gateway becomes a critical monitoring point because all cross-domain interaction passes through. Additionally, the gateway provides visibility into data exchange across different segments of the vehicle network. Its job is to detect deviations from normal behavior and generate security events.

When it comes to the CAN domain monitoring implemented in KASG, the IDS looks at the following criteria for traffic analysis:

• Alignment of CAN message parameters (CAN ID, DLC) with their descriptions in the DBC specification.
• Frequency and periodicity of CAN messages.
• Allowable ranges for CAN signals.

In practice, however, an important limitation becomes clear: even with an onboard IDS, more context is required to determine the exact characteristics of an attack. Furthermore, when operating highly automated vehicles — where fleet-wide monitoring is essential — such isolated analysis becomes inherently insufficient.

Connecting a vehicle to an SIEM

Multi-object monitoring, data correlation, and data analysis can be efficiently handled externally — specifically in SIEM (Security Information and Event Management) systems, which are traditionally used in corporate and industrial cybersecurity operations centers. Therefore, utilizing a SIEM system fleet-wide is a logical step that makes it possible to:

• Collect security events from multiple vehicles.
• Correlate events over time and across contexts.
• Detect advanced and distributed attacks.
• Provide incident auditing and investigation.
• Respond to individual incidents and manage cyber-risks fleet-wide.

When integrating with external SIEM systems, several critical tasks must be addressed: ensuring a secure connection, tuning the security event transmission process, and establishing baseline rules for event processing and correlation. We are actively working through all of these challenges using our own SIEM system — Kaspersky Unified Monitoring and Analysis Platform — as a blueprint.

There are still many issues ahead that need to be resolved. This article covered only a fraction of the approaches currently used in KASG to ensure vehicle safety and security. Yet even this small part demonstrates that automotive security cannot be achieved by solving a single problem or applying a single mechanism. Achieving it requires an approach that enables methodical architecture development — balancing diverse requirements for vehicle functionality, security, and reliability.

Lawmakers in both houses of Congress are demanding answers from the U.S. Cybersecurity & Infrastructure Security Agency (CISA) after KrebsOnSecurity reported this week that a CISA contractor intentionally published AWS GovCloud keys and a vast trove of other agency secrets on a public GitHub account. The inquiry comes as CISA is still struggling to contain the breach and invalidate the leaked credentials.

On May 18, KrebsOnSecurity reported that a CISA contractor with administrative access to the agency’s code development platform had created a public GitHub profile called “Private-CISA” that included plaintext credentials to dozens of internal CISA systems. Experts who reviewed the exposed secrets said the commit logs for the code repository showed the CISA contractor disabled GitHub’s built-in protection against publishing sensitive credentials in public repos.

CISA acknowledged the leak but has not responded to questions about the duration of the data exposure. However, experts who reviewed the now-defunct Private-CISA archive said it was originally created in November 2025, and that it exhibits a pattern consistent with an individual operator using the repository as a working scratchpad or synchronization mechanism rather than a curated project repository.

In a written statement, CISA said “there is no indication that any sensitive data was compromised as a result of the incident.” But in a May 19 a letter (PDF) to CISA’s Acting Director Nick Andersen, Sen. Maggie Hassan (D-NH) said the credential leak raises serious questions about how such a security lapse could occur at the very agency charged with helping to prevent cyber breaches.

“This reporting raises serious concerns regarding CISA’s internal policies and procedures at a time of significant cybersecurity threats against U.S. critical infrastructure,” Sen. Hassan wrote.

Sen. Hassan noted that the incident occurred against the backdrop of major disruptions internally at CISA, which lost more than a third of it workforce and almost all of its senior leaders after the Trump administration forced a series of early retirements, buyouts, and resignations across the agency’s various divisions.

Rep. Bennie Thompson (D-MS), the ranking member on the House Homeland Security Committee, echoed the senator’s concerns.

“We are concerned that this incident reflects a diminished security culture and/or an inability for CISA to adequately manage its contract support,” Thompson wrote in a May 19 letter to the acting CISA chief that was co-signed by Rep. Delia Ramirez (D-Ill), the ranking member of the panel’s Subcommittee on Cybersecurity and Infrastructure Protection. “It’s no secret that our adversaries — like China, Russia, and Iran — seek to gain access to and persistence on federal networks. The files contained in the ‘Private-CISA’ repository provided the information, access, and roadmap to do just that.”

KrebsOnSecurity has learned that more a week after CISA was first notified of the data leak by the security firm GitGuardian, the agency is still working to invalidate and replace many of the exposed keys and secrets.

On May 20, KrebsOnSecurity heard from Dylan Ayrey, the creator of TruffleHog, an open-source tool for discovering private keys and other secrets buried in code hosted at GitHub and other public platforms. Ayrey said CISA still hadn’t invalidated an RSA private key exposed in the Private-CISA repo that granted access to a GitHub app which is owned by the CISA enterprise account and installed on the CISA-IT GitHub organization with full access to all code repositories.

“An attacker with this key can read source code from every repository in the CISA-IT organization, including private repos, register rogue self-hosted runners to hijack CI/CD pipelines and access repository secrets, and modify repository admin settings including branch protection rules, webhooks, and deploy keys,” Ayrey told KrebsOnSecurity. CI/CD stands for Continuous Integration and Continuous Delivery, and it refers to a set of practices used to automate the building, testing and deployment of software.

KrebsOnSecurity notified CISA about Ayrey’s findings on May 20. Ayrey said CISA appears to have invalidated the exposed RSA private key sometime after that notification. But he noted that CISA still hasn’t rotated leaked credentials tied to other critical security technologies that are deployed across the agency’s technology portfolio (KrebsOnSecurity is not naming those technologies publicly for the time being).

CISA responded with a brief written statement in response to questions about Ayrey’s findings, saying “CISA is actively responding and coordinating with the appropriate parties and vendors to ensure any identified leaked credentials are rotated and rendered invalid and will continue to take appropriate steps to protect the security of our systems.”

Ayrey said his company Truffle Security monitors GitHub and a number of other code platforms for exposed keys, and attempts to alert affected accounts to the sensitive data exposure(s). They can do this easily on GitHub because the platform publishes a live feed which includes a record of all commits and changes to public code repositories. But he said cybercriminal actors also monitor these public feeds, and are often quick to pounce on API or SSH keys that get inadvertently published in code commits.

In practical terms, it is likely that cybercrime groups or foreign adversaries also noticed the publication of these CISA secrets, the most egregious of which appears to have happened in late April 2026, Ayrey said.

“We monitor that firehose of data for keys, and we have tools to try to figure out whose they are,” he said. “We have evidence attackers monitor that firehose as well. Anyone monitoring GitHub events could be sitting on this information.”

James Wilson, the enterprise technology editor for the Risky Business security podcast, said organizations using GitHub to manage code projects can set top-down policies that prevent employees from disabling GitHub’s protections against publishing secret keys and credentials. But Wilson’s co-host Adam Boileau said it’s not clear that any technology could stop employees from opening their own personal GitHub account and using it to store sensitive and proprietary information.

“Ultimately, this is a thing you can’t solve with a technical control,” Boileau said on this week’s podcast. “This is a human problem where you’ve hired a contractor to do this work and they have decided of their own volition to use GitHub to synchronize content from a work machine to a home machine. I don’t know what technical controls you could put in place given that this is being done presumably outside of anything CISA managed or even had visibility on.”

Update, 3:05 p.m. ET: Added statement from CISA. Corrected a date in the story (Truffle Security said it found the repo gained some of its most sensitive secrets in late April 2026, not 2025).