Full Report
Posted by Lyubov Farafonova, Product Manager, Phone by Google; Alberto Pastor Nieto, Sr. Product Manager Google Messages and RCS Spam and Abuse We’ve shared how Android’s proactive, multi-layered scam defenses utilize Google AI to protect users around the world from over 10 billion suspected malicious calls and messages every month1. While that scale is significant, the true impact of these protections is best understood through the stories of the individuals they help keep safe every day. This includes people like Majik B., an IT professional in Sunnyvale, California. Despite his technical background, Majik recently found himself on a call that felt dangerously legitimate. While using his Pixel, he received a call that appeared to be from his bank. The number looked correct, the caller knew his name and his address, and the story about a "suspicious charge" made perfect sense. "I’m usually pretty careful about this stuff," Majik recalled, "but I stayed on the line longer than I normally would. Even knowing how these scams work, it was convincing in the moment." The turning point came when his phone displayed a Scam Detection warning during the call, which provided a critical moment to pause and reflect. Majik hung up, checked his bank app directly, and confirmed there was no fraudulent charge. For Majik, Scam Detection was the intervention he needed: “The warning is what made me pause and avoid a bad situation”. While stories like Majik’s show how our existing protections provide a robust shield against scams, our work isn't done. As scammers evolve their tactics and create more convincing and personalized threats, we’re using the best of Google AI to stay one step ahead. A recent evaluation by Counterpoint Research found that Android smartphones provide the most comprehensive AI-powered protections of any mobile platform. We are committed to building on this foundation by expanding our AI-powered protections to more users and devices, while rolling out new features that utilize on-device AI to defend against increasingly sophisticated threats. Expanding Scam Detection for Calls to Samsung Devices To help protect you during phone calls, Scam Detection alerts you if a caller uses speech patterns commonly associated with fraud. We are bringing these protections to more of our users through new regional expansion and availability on new devices. Scam Detection for phone calls on Google Pixel devices is available in the U.S., Australia, Canada, India, Ireland, and the UK. Scam Detection is already helping millions of users to stay safe from scammers, and we are expanding this feature to more manufacturers, starting with the Samsung Galaxy S26 series in the U.S. We are continuing to work with our partners to bring these industry-leading protections to even more users. Powered by Gemini’s on-device model, Scam Detection provides intelligent protection against scam calls while ensuring that the processing stays on your device. This keeps your conversations private while delivering warnings in real-time. To preserve your privacy, the phone conversation processed by Scam Detection is neither stored on your device, nor shared outside of the device. To ensure you stay in total control of your experience, Scam Detection is turned off by default. When enabled, the feature only applies to calls identified as potential scams and is never used in calls with your contacts. You can easily manage these preferences in your phone settings whenever you choose. Enhanced Protection Against Messaging Scams We want everyone to feel secure when they open their messages, no matter where they are or what language they speak. To make this possible, we’ve now expanded Scam Detection for Google Messages to more than 20 countries. This includes support for several languages including English, Arabic, French, German, Portuguese, and Spanish. Beyond reaching more people, we are also making our protections more intelligent. We are enhancing how Google Messages identifies fraudulent texts by utilizing our Gemini on-device model on the latest Android flagship devices in the US, Canada, and the UK. The added power of Gemini’s on-device model allows for a much more nuanced analysis of complex conversational threats. For example, it can better detect the subtle conversational patterns used in job offer scams or sophisticated romance baiting scams (also known as “pig butchering”), a deceptive tactic where a scammer builds a long-term "relationship" with a potential victim to gain their trust, before tricking them into a fraudulent investment. Because these methods rely on gradual manipulation and don’t present typical warning signs, they need more advanced capabilities to catch them at scale. These advanced protections are now rolling out on Google Pixel 10 series and other select devices, and will be available on the Samsung Galaxy S26 series. Gemini-powered Scam Detection alerts a user to a job offer scam Using the Best of Google AI to Set the Standard in Mobile Scam Protection Android continues to set the standard in mobile scam protections by leveraging advanced AI to identify and intercept threats as they happen. As scammer’s strategies shift, we remain committed to developing equally adaptive and intelligent defenses. Our goal is to provide you with peace of mind so you can continue to connect and communicate with confidence, knowing our multi-layered defenses are there to help protect your financial and personal data against mobile scams. Disclaimers 1: This total comprises all instances where a message or call was proactively blocked or where a user was alerted to potential spam or scam activity.
Analysis Summary
# Best Practices: Implementing Proactive, AI-Powered Scam and Fraud Defenses in Mobile Communications
## Overview
These practices focus on leveraging modern, on-device AI capabilities (like those powered by Google's Gemini models) within mobile operating systems (specifically Android) to provide real-time, multi-layered defenses against sophisticated phone call and messaging scams, ensuring user privacy is maintained through local processing.
## Key Recommendations
### Immediate Actions
1. **Enable Scam Detection Features:** Ensure that all available, user-facing scam and spam detection features within communication apps (Messages and Phone) are actively enabled for all applicable devices, as these are often default-off for privacy reasons initially.
2. **Verify Regional Availability:** Immediately confirm which Scam Detection for Calls features are active in your organization’s primary operating regions based on the latest vendor rollouts (e.g., confirming availability in U.S., Australia, Canada, India, Ireland, UK for phone calls).
3. **Update Flagship Devices:** Prioritize updating all organizational flagship Android devices (Pixel 10 series, Samsung Galaxy S26 series, and equivalent models supporting on-device Gemini processing) to the latest operating system and security patches to access enhanced, pattern-analyzing scam detection.
### Short-term Improvements (1-3 months)
1. **Communicate Feature Importance to Users:** Launch an internal communication campaign explaining the value of real-time Scam Detection warnings (e.g., the "critical moment to pause and reflect") and educating users on how these AI features work and why they should heed the warnings.
2. **Expand Messaging Protection Rollout:** If operating internationally, track and enforce the expansion of Scam Detection for Google Messages to all supported languages and the 20+ countries mentioned, ensuring messaging security coverage is maximized across global teams.
3. **Review Contact Exclusion Settings:** For deployed mobile devices, verify that the Scam Detection configuration adheres strictly to the principle of only applying protections to potential scams and not accidentally blocking or analyzing communications with verified, established company contacts.
### Long-term Strategy (3+ months)
1. **Adopt Advanced On-Device Processing Standard:** Mandate the use of communication platforms that utilize on-device AI models (like Gemini) for scam analysis, as this provides superior, nuanced analysis (better for job offer or romance scams) while inherently preserving conversation privacy (data never leaves the device).
2. **Device Refresh Cycle Alignment:** Integrate the requirement for devices capable of running advanced on-device AI security models into future mobile hardware procurement strategies to ensure continuous access to the latest scam defense capabilities.
3. **Continuous Monitoring of Threat Evolution:** Establish a process to monitor official vendor security advisories for updates on new scam tactics (e.g., evolving conversation patterns) that require enhancements to the protective models, ensuring defenses remain adaptive.
## Implementation Guidance
### For Small Organizations
- **Focus on User Education:** Since advanced feature rollout is often automatic via OS updates, the primary action is user awareness. Conduct mandatory, short training sessions detailing *where* users will see the alerts (calls and messages) and the immediate corrective action: **Hang up/Stop interaction and verify independently** (e.g., checking the bank app directly).
### For Medium Organizations
- **Phased Device Rollout:** Target initial deployment of feature activation (if manual) to departments most susceptible to common financial scams (e.g., finance, executive staff) before broader deployment.
- **Policy Integration:** Update Acceptable Use Policies (AUP) to mandate that users comply with AI-driven security warnings issued by the operating system/communication platform.
### For Large Enterprises
- **Conditional Access Review:** Review Conditional Access policies related to mobile devices to ensure that access to sensitive corporate resources is only granted to devices running OS versions that support the latest, comprehensive on-device AI security features.
- **Privacy Assurance Documentation:** Develop internal documentation to explicitly assure employees that processing for Scam Detection—which runs on the device—is neither stored nor shared externally, addressing potential privacy or compliance concerns regarding real-time communication analysis.
## Configuration Examples
*Note: Specific in-app settings might vary by OS version, but the conceptual configurations are:*
1. **Scam Detection for Calls:**
* **Setting Path (Conceptual):** Phone App Settings -> Caller ID & Spam -> Scam Detection (Toggle ON)
* **Verification:** Ensure the feature is set to provide real-time *warnings* during the call, not just blocking.
2. **Scam Detection for Messages:**
* **Setting Path (Conceptual):** Google Messages Settings -> Spam Protection -> Enable Advanced Threat Analysis (Toggle ON, dependent on device capability)
* **Privacy Note:** Confirm feature utilizes on-device processing (Gemini/equivalent).
## Compliance Alignment
The reliance on on-device processing fundamentally supports several compliance objectives:
* **GDPR/CCPA (Privacy):** Processing of communication content for security analysis remains localized ("privacy by design"), reducing data transfer risk and fulfilling data minimization principles for personal communications metadata/content that is analyzed locally.
* **NIST SP 800-53 (SC-13 Communications Protection):** Provides in-transit and near-real-time protection against malicious social engineering attempts leveraging communications channels.
* **ISO 27001 (A.12.1.2 Information Security Control Review):** Utilizes best-in-class technical controls (AI) integrated into endpoint devices for proactive threat mitigation.
## Common Pitfalls to Avoid
1. **Assuming "On" by Default:** Explicitly confirming that the Scam Detection feature is *enabled* by the user, as the source material notes it is "turned off by default."
2. **Ignoring Sophisticated Scams:** Relying only on outdated blacklist/blocklist methods. The deployment must embrace pattern analysis (Gemini-powered) to catch nuanced, long-term manipulation schemes like "pig butchering."
3. **Inconsistent Device Coverage:** Failing to update or replace older devices that cannot run the latest on-device AI models, creating security gaps where defenses are less intelligent or unavailable.
## Resources
1. **Vendor Documentation:** Consult official Android and device manufacturer (e.g., Google, Samsung) support pages for the exact path to enable and manage Scam Detection settings for current OS builds.
2. **AI Security Model Briefings:** Review official releases from mobile platform vendors regarding on-device model capabilities (e.g., Gemini specifics) to understand the depth of analysis being performed locally on communication content.
3. **User Training Materials:** Develop internal FAQs addressing user concerns about *how* the AI is monitoring calls/messages, explicitly citing the non-storage/non-sharing aspects of the on-device processing engine.