Last year, we wrote about why a memory safety strategy that focuses on vulnerability prevention in new code quickly yields durable and compounding gains. This year we look at how this approach isn’t just fixing things, but helping us move faster.
The 2025 data continues to validate the approach, with memory safety vulnerabilities falling below 20% of total vulnerabilities for the first time.
Updated data for 2025. This data covers first-party and third-party (open source) code changes to the Android platform across C, C++, Java, Kotlin, and Rust. This post is published a couple of months before the end of 2025, but Android’s industry-standard 90-day patch window means that these results are very likely close to final. We can and will accelerate patching when necessary.
We adopted Rust for its security and are seeing a 1000x reduction in memory safety vulnerability density compared to Android’s C and C++ code. But the biggest surprise was Rust's impact on software delivery. With Rust changes having a 4x lower rollback rate and spending 25% less time in code review, the safer path is now also the faster one.
In this post, we dig into the data behind this shift and also cover:
Developing an operating system requires the low-level control and predictability of systems programming languages like C, C++, and Rust. While Java and Kotlin are important for Android platform development, their role is complementary to the systems languages rather than interchangeable. We introduced Rust into Android as a direct alternative to C and C++, offering a similar level of control but without many of their risks. We focus this analysis on new and actively developed code because our data shows this to be an effective approach.
When we look at development in systems languages (excluding Java and Kotlin), two trends emerge: a steep rise in Rust usage and a slower but steady decline in new C++.
Net lines of code added: Rust vs. C++, first-party Android code.This chart focuses on first-party (Google-developed) code (unlike the previous chart that included all first-party and third-party code in Android.) We only include systems languages, C/C++ (which is primarily C++), and Rust.
The chart shows that the volume of new Rust code now rivals that of C++, enabling reliable comparisons of software development process metrics. To measure this, we use the DORA1 framework, a decade-long research program that has become the industry standard for evaluating software engineering team performance. DORA metrics focus on:
Cross-language comparisons can be challenging. We use several techniques to ensure the comparisons are reliable.
Code review is a time-consuming and high-latency part of the development process. Reworking code is a primary source of these costly delays. Data shows that Rust code requires fewer revisions. This trend has been consistent since 2023. Rust changes of a similar size need about 20% fewer revisions than their C++ counterparts.
In addition, Rust changes currently spend about 25% less time in code review compared to C++. We speculate that the significant change in favor of Rust between 2023 and 2024 is due to increased Rust expertise on the Android team.
While less rework and faster code reviews offer modest productivity gains, the most significant improvements are in the stability and quality of the changes.
Stable and high-quality changes differentiate Rust. DORA uses rollback rate for evaluating change stability. Rust's rollback rate is very low and continues to decrease, even as its adoption in Android surpasses C++.
For medium and large changes, the rollback rate of Rust changes in Android is ~4x lower than C++. This low rollback rate doesn't just indicate stability; it actively improves overall development throughput. Rollbacks are highly disruptive to productivity, introducing organizational friction and mobilizing resources far beyond the developer who submitted the faulty change. Rollbacks necessitate rework and more code reviews, can also lead to build respins, postmortems, and blockage of other teams. Resulting postmortems often introduce new safeguards that add even more development overhead.
In a self-reported survey from 2022, Google software engineers reported that Rust is both easier to review and more likely to be correct. The hard data on rollback rates and review times validates those impressions.
Historically, security improvements often came at a cost. More security meant more process, slower performance, or delayed features, forcing trade-offs between security and other product goals. The shift to Rust is different: we are significantly improving security and key development efficiency and product stability metrics.
With Rust support now mature for building Android system services and libraries, we are focused on bringing its security and productivity advantages elsewhere.
These examples highlight Rust's role in reducing security risks, but memory-safe languages are only one part of a comprehensive memory safety strategy. We continue to employ a defense-in-depth approach, the value of which was clearly demonstrated in a recent near-miss.
We recently avoided shipping our very first Rust-based memory safety vulnerability: a linear buffer overflow in CrabbyAVIF. It was a near-miss. To ensure the patch received high priority and was tracked through release channels, we assigned it the identifier CVE-2025-48530. While it’s great that the vulnerability never made it into a public release, the near-miss offers valuable lessons. The following sections highlight key takeaways from our postmortem.
A key finding is that Android’s Scudo hardened allocator deterministically rendered this vulnerability non-exploitable due to guard pages surrounding secondary allocations. While Scudo is Android’s default allocator, used on Google Pixel and many other devices, we continue to work with partners to make it mandatory. In the meantime, we will issue CVEs of sufficient severity for vulnerabilities that could be prevented by Scudo.
In addition to protecting against overflows, Scudo’s use of guard pages helped identify this issue by changing an overflow from silent memory corruption into a noisy crash. However, we did discover a gap in our crash reporting: it failed to clearly show that the crash was a result of an overflow, which slowed down triage and response. This has been fixed, and we now have a clear signal when overflows occur into Scudo guard pages.
Operating system development requires unsafe code, typically C, C++, or unsafe Rust (for example, for FFI and interacting with hardware), so simply banning unsafe code is not workable. When developers must use unsafe, they should understand how to do so soundly and responsibly
To that end, we are adding a new deep dive on unsafe code to our Comprehensive Rust training. This new module, currently in development, aims to teach developers how to reason about unsafe Rust code, soundness and undefined behavior, as well as best practices like safety comments and encapsulating unsafe code in safe abstractions.
Better understanding of unsafe Rust will lead to even higher quality and more secure code across the open source software ecosystem and within Android. As we'll discuss in the next section, our unsafe Rust is already really quite safe. It’s exciting to consider just how high the bar can go.
This near-miss inevitably raises the question: "If Rust can have memory safety vulnerabilities, then what’s the point?"
The point is that the density is drastically lower. So much lower that it represents a major shift in security posture. Based on our near-miss, we can make a conservative estimate. With roughly 5 million lines of Rust in the Android platform and one potential memory safety vulnerability found (and fixed pre-release), our estimated vulnerability density for Rust is 0.2 vuln per 1 million lines (MLOC).
Our historical data for C and C++ shows a density of closer to 1,000 memory safety vulnerabilities per MLOC. Our Rust code is currently tracking at a density orders of magnitude lower: a more than 1000x reduction.
Memory safety rightfully receives significant focus because the vulnerability class is uniquely powerful and (historically) highly prevalent. High vulnerability density undermines otherwise solid security design because these flaws can be chained to bypass defenses, including those specifically targeting memory safety exploits. Significantly lowering vulnerability density does not just reduce the number of bugs; it dramatically boosts the effectiveness of our entire security architecture.
The primary security concern regarding Rust generally centers on the approximately 4% of code written within unsafe{} blocks. This subset of Rust has fueled significant speculation, misconceptions, and even theories that unsafe Rust might be more buggy than C. Empirical evidence shows this to be quite wrong.
unsafe{}
Our data indicates that even a more conservative assumption, that a line of unsafe Rust is as likely to have a bug as a line of C or C++, significantly overestimates the risk of unsafe Rust. We don’t know for sure why this is the case, but there are likely several contributing factors:
Historically, we had to accept a trade-off: mitigating the risks of memory safety defects required substantial investments in static analysis, runtime mitigations, sandboxing, and reactive patching. This approach attempted to move fast and then pick up the pieces afterwards. These layered protections were essential, but they came at a high cost to performance and developer productivity, while still providing insufficient assurance.
While C and C++ will persist, and both software and hardware safety mechanisms remain critical for layered defense, the transition to Rust is a different approach where the more secure path is also demonstrably more efficient. Instead of moving fast and then later fixing the mess, we can move faster while fixing things. And who knows, as our code gets increasingly safe, perhaps we can start to reclaim even more of that performance and productivity that we exchanged for security, all while also improving security.
Thank you to the following individuals for their contributions to this post:
Finally, a tremendous thank you to the Android Rust team, and the entire Android organization for your relentless commitment to engineering excellence and continuous improvement.
The DevOps Research and Assessment (DORA) program is published by Google Cloud. ↩
For years, Android has been on the frontlines in the battle against scammers, using the best of Google AI to build proactive, multi-layered protections that can anticipate and block scams before they reach you. Android’s scam defenses protect users around the world from over 10 billion suspected malicious calls and messages every month2. In addition, Google continuously performs safety checks to maintain the integrity of the RCS service. In the past month alone, this ongoing process blocked over 100 million suspicious numbers from using RCS, stopping potential scams before they could even be sent.
To show how our scam protections work in the real world, we asked users and independent security experts to compare how well Android and iOS protect you from these threats. We're also releasing a new report that explains how modern text scams are orchestrated, helping you understand the tactics fraudsters use and how to spot them.
Survey shows Android users’ confidence in scam protections
Google and YouGov3 surveyed 5,000 smartphone users across the U.S., India, and Brazil about their scam experiences. The findings were clear: Android users reported receiving fewer scam texts and felt more confident that their device was keeping them safe.
YouGov study findings on users’ experience with scams on Android and iOS
In a recent evaluation by Counterpoint Research5, a global technology market research firm, Android smartphones were found to have the most AI-powered protections. The independent study compared the latest Pixel, Samsung, Motorola, and iPhone devices, and found that Android provides comprehensive AI-driven safeguards across ten key protection areas, including email protections, browsing protections, and on-device behavioral protections. By contrast, iOS offered AI-powered protections in only two categories. You can see the full comparison in the visual below.
Cybersecurity firm Leviathan Security Group conducted a funded evaluation6 of scam and fraud protection on the iPhone 17, Moto Razr+ 2025, Pixel 10 Pro, and Samsung Galaxy Z Fold 7. Their analysis found that Android smartphones, led by the Pixel 10 Pro, provide the highest level of default scam and fraud protection.The report particularly noted Android's robust call screening, scam detection, and real-time scam warning authentication capabilities as key differentiators. Taken together, these independent expert assessments conclude that Android’s AI-driven safeguards provide more comprehensive and intelligent protection against mobile scams.
Why Android users see fewer scams
Android’s proactive protections work across the platform to help you stay ahead of threats with the best of Google AI.
Here’s how they work:
These safeguards are built directly into the core of Android, alongside other features like real-time app scanning in Google Play Protect and enhanced Safe Browsing in Chrome using LLMs. With Android, you can trust that you have intelligent, multi-layered protection against scams working for you.
Android is always evolving to keep you one step ahead of scams
In a world of evolving digital threats, you deserve to feel confident that your phone is keeping you safe. That’s why we use the best of Google AI to build intelligent protections that are always improving and work for you around the clock, so you can connect, browse, and communicate with peace of mind.
See these protections in action in our new infographic and learn more about phone call scams in our 2025 Phone by Google Scam Report.
1: Data from Global Anti-Scam Alliance, October 2025 ↩
2: 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. ↩
3: Google/YouGov survey, July-August, n=5,100 (1,700 each in the US, Brazil and India), with adults who use their smartphones daily and who have been exposed to a scam or fraud attempt on their smartphone. Survey data have been weighted to smartphone population adults in each country. ↩
4: Among users who use the default texting app on their smartphone ↩
5: Google/Counterpoint Research, “Assessing the State of AI-Powered Mobile Security”, Oct. 2025; based on comparing the Pixel 10 Pro, iPhone 17 Pro, Samsung Galaxy S25 Ultra, OnePlus 13, Motorola Razr+ 2025. Evaluation based on no-cost smartphone features enabled by default. Some features may not be available in all countries. ↩
6: Google/Leviathan Security Group, “October 2025 Mobile Platform Security & Fraud Prevention Assessment”, Oct. 2025; based on comparing the Pixel 10 Pro, iPhone 17 Pro, Samsung Galaxy Z Fold 7 and Motorola Razr+ 2025. Evaluation based on no-cost smartphone features enabled by default. Some features may not be available in all countries. ↩ ↩
7: Accuracy may vary. Availability varies. ↩ ↩ ↩
One year from now, with the release of Chrome 154 in October 2026, we will change the default settings of Chrome to enable “Always Use Secure Connections”. This means Chrome will ask for the user's permission before the first access to any public site without HTTPS.
The “Always Use Secure Connections” setting warns users before accessing a site without HTTPS
Chrome Security's mission is to make it safe to click on links. Part of being safe means ensuring that when a user types a URL or clicks on a link, the browser ends up where the user intended. When links don't use HTTPS, an attacker can hijack the navigation and force Chrome users to load arbitrary, attacker-controlled resources, and expose the user to malware, targeted exploitation, or social engineering attacks. Attacks like this are not hypothetical—software to hijack navigations is readily available and attackers have previously used insecure HTTP to compromise user devices in a targeted attack.
Since attackers only need a single insecure navigation, they don't need to worry that many sites have adopted HTTPS—any single HTTP navigation may offer a foothold. What's worse, many plaintext HTTP connections today are entirely invisible to users, as HTTP sites may immediately redirect to HTTPS sites. That gives users no opportunity to see Chrome's "Not Secure" URL bar warnings after the risk has occurred, and no opportunity to keep themselves safe in the first place.
To address this risk, we launched the “Always Use Secure Connections” setting in 2022 as an opt-in option. In this mode, Chrome attempts every connection over HTTPS, and shows a bypassable warning to the user if HTTPS is unavailable. We also previously discussed our intent to move towards HTTPS by default. We now think the time has come to enable “Always Use Secure Connections” for all users by default.
For more than a decade, Google has published the HTTPS transparency report, which tracks the percentage of navigations in Chrome that use HTTPS. For the first several years of the report, numbers saw an impressive climb, starting at around 30-45% in 2015, and ending up around the 95-99% range around 2020. Since then, progress has largely plateaued.
HTTPS adoption expressed as a percentage of main frame page loads
This rise represents a tremendous improvement to the security of the web, and demonstrates that HTTPS is now mature and widespread. This level of adoption is what makes it possible to consider stronger mitigations against the remaining insecure HTTP.
While it may at first seem that 95% HTTPS means that the problem is mostly solved, the truth is that a few percentage points of HTTP navigations is still a lot of navigations. Since HTTP navigations remain a regular occurrence for most Chrome users, a naive approach to warning on all HTTP navigations would be quite disruptive. At the same time, as the plateau demonstrates, doing nothing would allow this risk to persist indefinitely. To balance these risks, we have taken steps to ensure that we can help the web move towards safer defaults, while limiting the potential annoyance warnings will cause to users.
One way we're balancing risks to users is by making sure Chrome does not warn about the same sites excessively. In all variants of the "Always Use Secure Connections" settings, so long as the user regularly visits an insecure site, Chrome will not warn the user about that site repeatedly. This means that rather than warn users about 1 out of 50 navigations, Chrome will only warn users when they visit a new (or not recently visited) site without using HTTPS.
To further address the issue, it's important to understand what sort of traffic is still using HTTP. The largest contributor to insecure HTTP by far, and the largest contributor to variation across platforms, is insecure navigations to private sites. The graph above includes both those to public sites, such as example.com, and navigations to private sites, such as local IP addresses like 192.168.0.1, single-label hostnames, and shortlinks like intranet/. While it is free and easy to get an HTTPS certificate that is trusted by Chrome for a public site, acquiring an HTTPS certificate for a private site unfortunately remains complicated. This is because private names are "non-unique"—private names can refer to different hosts on different networks. There is no single owner of 192.168.0.1 for a certification authority to validate and issue a certificate to.
example.com
192.168.0.1
intranet/
HTTP navigations to private sites can still be risky, but are typically less dangerous than their public site counterparts because there are fewer ways for an attacker to take advantage of these HTTP navigations. HTTP on private sites can only be abused by an attacker also on your local network, like on your home wifi or in a corporate network.
If you exclude navigations to private sites, then the distribution becomes much tighter across platforms. In particular, Linux jumps from 84% HTTPS to nearly 97% HTTPS when limiting the analysis to public sites only. Windows increases from 95% to 98% HTTPS, and both Android and Mac increase to over 99% HTTPS.
In recognition of the reduced risk HTTP to private sites represents, last year we introduced a variant of “Always Use Secure Connections” for public sites only. For users who frequently access private sites (such as those in enterprise settings, or web developers), excluding warnings on private sites significantly reduces the volume of warnings those users will see. Simultaneously, for users who do not access private sites frequently, this mode introduces only a small reduction in protection. This is the variant we intend to enable for all users next year.
“Always Use Secure Connections,” available at chrome://settings/security
In Chrome 141, we experimented with enabling “Always Use Secure Connections” for public sites by default for a small percentage of users. We wanted to validate our expectations that this setting keeps users safer without burdening them with excessive warnings.
Analyzing the data from the experiment, we confirmed that the number of warnings seen by any users is considerably lower than 3% of navigations—in fact, the median user sees fewer than one warning per week, and the ninety-fifth percentile user sees fewer than three warnings per week..
Once “Always Use Secure Connections” is the default and additional sites migrate away from HTTP, we expect the actual warning volume to be even lower than it is now. In parallel to our experiments, we have reached out to a number of companies responsible for the most HTTP navigations, and expect that they will be able to migrate away from HTTP before the change in Chrome 154. For many of these organizations, transitioning to HTTPS isn't disproportionately hard, but simply has not received attention. For example, many of these sites use HTTP only for navigations that immediately redirect to HTTPS sites—an insecure interaction which was previously completely invisible to users.
Another current use case for HTTP is to avoid mixed content blocking when accessing devices on the local network. Private addresses, as discussed above, often do not have trusted HTTPS certificates, due to the difficulties of validating ownership of a non-unique name. This means most local network traffic is over HTTP, and cannot be initiated from an HTTPS page—the HTTP traffic counts as insecure mixed content, and is blocked. One common use case for needing to access the local network is to configure a local network device, e.g. the manufacturer might host a configuration portal at config.example.com, which then sends requests to a local device to configure it.
config.example.com
Previously, these types of pages needed to be hosted without HTTPS to avoid mixed content blocking. However, we recently introduced a local network access permission, which both prevents sites from accessing the user’s local network without consent, but also allows an HTTPS site to bypass mixed content checks for the local network once the permission has been granted. This can unblock migrating these domains to HTTPS.
We will enable the "Always Use Secure Connections" setting in its public-sites variant by default in October 2026, with the release of Chrome 154. Prior to enabling it by default for all users, in Chrome 147, releasing in April 2026, we will enable Always Use Secure Connections in its public-sites variant for the over 1 billion users who have opted-in to Enhanced Safe Browsing protections in Chrome.
While it is our hope and expectation that this transition will be relatively painless for most users, users will still be able to disable the warnings by disabling the "Always Use Secure Connections" setting.
If you are a website developer or IT professional, and you have users who may be impacted by this feature, we very strongly recommend enabling the "Always Use Secure Connections" setting today to help identify sites that you may need to work to migrate. IT professionals may find it useful to read our additional resources to better understand the circumstances where warnings will be shown, how to mitigate them, and how organizations that manage Chrome clients (like enterprises or educational institutions) can ensure that Chrome shows the right warnings to meet those organizations' needs.
While we believe that warning on insecure public sites represents a significant step forward for the security of the web, there is still more work to be done. In the future, we hope to work to further reduce barriers to adoption of HTTPS, especially for local network sites. This work will hopefully enable even more robust HTTP protections down the road.
Empowering cyber defenders with AI is critical to tilting the cybersecurity balance back in their favor as they battle cybercriminals and keep users safe. To help accelerate adoption of AI for cybersecurity workflows, we partnered with Airbus at DEF CON 33 to host the GenSec Capture the Flag (CTF), dedicated to human-AI collaboration in cybersecurity. Our goal was to create a fun, interactive environment, where participants across various skill levels could explore how AI can accelerate their daily cybersecurity workflows.
The CTF also offered a valuable opportunity for the community to use Sec-Gemini, Google’s experimental Cybersecurity AI, as an optional assistant available in the UI alongside major LLMs. And we received great feedback on Sec-Gemini, with 77% of respondents saying that they had found Sec-Gemini either “very helpful” or “extremely helpful” in assisting them with solving the challenges.
We want to thank the DEF CON community for the enthusiastic participation and for making this inaugural event a resounding success. The community feedback during the event has been invaluable for understanding how to improve Sec-Gemini, and we are already incorporating some of the lessons learned into the next iteration.
We are committed to advancing the AI cybersecurity frontier and will continue working with the community to build tools that help protect people online. Stay tuned as we plan to share more research and key learnings from the CTF with the broader community.
To address this gap and help the ecosystem with deploying robust defenses, Google has supported academic research and developed test platforms to analyze DDR5 memory. Our effort has led to the discovery of new attacks and a deeper understanding of Rowhammer on the current DRAM modules, helping to forge the way for further, stronger mitigations.
Rowhammer exploits a vulnerability in DRAM. DRAM cells store data as electrical charges, but these electric charges leak over time, causing data corruption. To prevent data loss, the memory controller periodically refreshes the cells. However, if a cell discharges before the refresh cycle, its stored bit may corrupt. Initially considered a reliability issue, it has been leveraged by security researchers to demonstrate privilege escalation attacks. By repeatedly accessing a memory row, an attacker can cause bit flips in neighboring rows. An adversary can exploit Rowhammer via:
Reliably cause bit flips by repeatedly accessing adjacent DRAM rows.
Coerce other applications or the OS into using these vulnerable memory pages.
Target security-sensitive code or data to achieve privilege escalation.
Or simply corrupt system’s memory to cause denial of service.
Previous work has repeatedly demonstrated the possibility of such attacks from software [Revisiting rowhammer, Are we susceptible to rowhammer?, Drammer, Flip feng shui, Jolt]. As a result, defending against Rowhammer is required for secure isolation in multi-tenant environments like the cloud.
The primary approach to mitigate Rowhammer is to detect which memory rows are being aggressively accessed and refreshing nearby rows before a bit flip occurs. TRR is a common example, which uses a number of counters to track accesses to a small number of rows adjacent to a potential victim row. If the access count for these aggressor rows reaches a certain threshold, the system issues a refresh to the victim row. TRR can be incorporated within the DRAM or in the host CPU.
However, this mitigation is not foolproof. For example, the TRRespass attack showed that by simultaneously hammering multiple, non-adjacent rows, TRR can be bypassed. Over the past couple of years, more sophisticated attacks [Half-Double, Blacksmith] have emerged, introducing more efficient attack patterns.
In response, one of our efforts was to collaborate with JEDEC, external researchers, and experts to define the PRAC as a new mitigation that deterministically detects Rowhammer by tracking all memory rows.
However, current systems equipped with DDR5 lack support for PRAC or other robust mitigations. As a result, they rely on probabilistic approaches such as ECC and enhanced TRR to reduce the risk. While these measures have mitigated older attacks, their overall effectiveness against new techniques was not fully understood until our recent findings.
Mitigating Rowhammer attacks involves making it difficult for an attacker to reliably cause bit flips from software. Therefore, for an effective mitigation, we have to understand how a determined adversary introduces memory accesses that bypass existing mitigations. Three key information components can help with such an analysis:
How the improved TRR and in-DRAM ECC work.
How memory access patterns from software translate into low-level DDR commands.
(Optionally) How any mitigations (e.g., ECC or TRR) in the host processor work.
The first step is particularly challenging and involves reverse-engineering the proprietary in-DRAM TRR mechanism, which varies significantly between different manufacturers and device models. This process requires the ability to issue precise DDR commands to DRAM and analyze its responses, which is difficult on an off-the-shelf system. Therefore, specialized test platforms are essential.
The second and third steps involve analyzing the DDR traffic between the host processor and the DRAM. This can be done using an off-the-shelf interposer, a tool that sits between the processor and DRAM. A crucial part of this analysis is understanding how a live system translates software-level memory accesses into the DDR protocol.
The third step, which involves analyzing host-side mitigations, is sometimes optional. For example, host-side ECC (Error Correcting Code) is enabled by default on servers, while host-side TRR has only been implemented in some CPUs.
For the first challenge, we partnered with Antmicro to develop two specialized, open-source FPGA-based Rowhammer test platforms. These platforms allow us to conduct in-depth testing on different types of DDR5 modules.
DDR5 RDIMM Platform: A new DDR5 Tester board to meet the hardware requirements of Registered DIMM (RDIMM) memory, common in server computers.
SO-DIMM Platform: A version that supports the standard SO-DIMM pinout compatible with off-the-shelf DDR5 SO-DIMM memory sticks, common in workstations and end-user devices.
Antmicro designed and manufactured these open-source platforms and we worked closely with them, and researchers from ETH Zurich, to test the applicability of these platforms for analyzing off-the-shelf memory modules in RDIMM and SO-DIMM forms.
Antmicro DDR5 RDIMM FPGA test platform in action.
In collaboration with researchers from ETH, we applied the new Rowhammer test platforms to evaluate the effectiveness of current in-DRAM DDR5 mitigations. Our findings, detailed in the recently co-authored "Phoenix” research paper, reveal that we successfully developed custom attack patterns capable of bypassing enhanced TRR (Target Row Refresh) defense on DDR5 memory. We were able to create a novel self-correcting refresh synchronization attack technique, which allowed us to perform the first-ever Rowhammer privilege escalation exploit on a standard, production-grade desktop system equipped with DDR5 memory. While this experiment was conducted on an off-the-shelf workstation equipped with recent AMD Zen processors and SK Hynix DDR5 memory, we continue to investigate the applicability of our findings to other hardware configurations.
We showed that current mitigations for Rowhammer attacks are not sufficient, and the issue remains a widespread problem across the industry. They do make it more difficult “but not impossible” to carry out attacks, since an attacker needs an in-depth understanding of the specific memory subsystem architecture they wish to target.
Current mitigations based on TRR and ECC rely on probabilistic countermeasures that have insufficient entropy. Once an analyst understands how TRR operates, they can craft specific memory access patterns to bypass it. Furthermore, current ECC schemes were not designed as a security measure and are therefore incapable of reliably detecting errors.
Memory encryption is an alternative countermeasure for Rowhammer. However, our current assessment is that without cryptographic integrity, it offers no valuable defense against Rowhammer. More research is needed to develop viable, practical encryption and integrity solutions.
Google has been a leader in JEDEC standardization efforts, for instance with PRAC, a fully approved standard to be supported in upcoming versions of DDR5/LPDDR6. It works by accurately counting the number of times a DRAM wordline is activated and alerts the system if an excessive number of activations is detected. This close coordination between the DRAM and the system gives PRAC a reliable way to address Rowhammer.
In the meantime, we continue to evaluate and improve other countermeasures to ensure our workloads are resilient against Rowhammer. We collaborate with our academic and industry partners to improve analysis techniques and test platforms, and to share our findings with the broader ecosystem.
“Phoenix: Rowhammer Attacks on DDR5 with Self-Correcting Synchronization” will be presented at IEEE Security & Privacy 2026 in San Francisco, CA (MAY 18-21, 2026).
At Made by Google 2025, we announced that the new Google Pixel 10 phones will support C2PA Content Credentials in Pixel Camera and Google Photos. This announcement represents a series of steps towards greater digital media transparency:
These capabilities are powered by Google Tensor G5, Titan M2 security chip, the advanced hardware-backed security features of the Android platform, and Pixel engineering expertise.
In this post, we’ll break down our architectural blueprint for bringing a new level of trust to digital media, and how developers can apply this model to their own apps on Android.
Generative AI can help us all to be more creative, productive, and innovative. But it can be hard to tell the difference between content that’s been AI-generated, and content created without AI. The ability to verify the source and history—or provenance—of digital content is more important than ever.
Content Credentials convey a rich set of information about how media such as images, videos, or audio files were made, protected by the same digital signature technology that has secured online transactions and mobile apps for decades. It empowers users to identify AI-generated (or altered) content, helping to foster transparency and trust in generative AI. It can be complemented by watermarking technologies such as SynthID.
Content Credentials are an industry standard backed by a broad coalition of leading companies for securely conveying the origin and history of media files. The standard is developed by the Coalition for Content Provenance and Authenticity (C2PA), of which Google is a steering committee member.
The traditional approach to classifying digital image content has focused on categorizing content as “AI” vs. “not AI”. This has been the basis for many legislative efforts, which have required the labeling of synthetic media. This traditional approach has drawbacks, as described in Chapter 5 of this seminal report by Google. Research shows that if only synthetic content is labeled as “AI”, then users falsely believe unlabeled content is “not AI”, a phenomenon called “the implied truth effect”. This is why Google is taking a different approach to applying C2PA Content Credentials.
Instead of categorizing digital content into a simplistic “AI” vs. “not AI”, Pixel 10 takes the first steps toward implementing our vision of categorizing digital content as either i) media that comes with verifiable proof of how it was made or ii) media that doesn't.
Given the broad range of scenarios in which Content Credentials are attached by these apps, we designed our C2PA implementation architecture from the onset to be:
Good actors in the C2PA ecosystem are motivated to ensure that provenance data is trustworthy. C2PA Certification Authorities (CAs), such as Google, are incentivized to only issue certificates to genuine instances of apps from trusted developers in order to prevent bad actors from undermining the system. Similarly, app developers want to protect their C2PA claim signing keys from unauthorized use. And of course, users want assurance that the media files they rely on come from where they claim. For these reasons, the C2PA defined the Conformance Program.
The Pixel Camera application on the Pixel 10 lineup has achieved Assurance Level 2, the highest security rating currently defined by the C2PA Conformance Program. This was made possible by a strong set of hardware-backed technologies, including Tensor G5 and the certified Titan M2 security chip, along with Android’s hardware-backed security APIs. Only mobile apps running on devices that have the necessary silicon features and Android APIs can be designed to achieve this assurance level. We are working with C2PA to help define future assurance levels that will push protections even deeper into hardware.
Achieving Assurance Level 2 requires verifiable, difficult-to-forge evidence. Google has built an end-to-end system on Pixel 10 devices that verifies several key attributes. However, the security of any claim is fundamentally dependent on the integrity of the application and the OS, an integrity that relies on both being kept current with the latest security patches.
The C2PA Conformance Program requires verifiable artifacts backed by a hardware Root of Trust, which Android provides through features like Key Attestation. This means Android developers can leverage these same tools to build apps that meet this standard for their users.
The robust security stack we described is the foundation of privacy. But Google takes steps further to ensure your privacy even as you use Content Credentials, which required solving two additional challenges:
Challenge 1: Server-side Processing of Certificate Requests. Google’s C2PA Certification Authorities must certify new cryptographic keys generated on-device. To prevent fraud, these certificate enrollment requests need to be authenticated. A more common approach would require user accounts for authentication, but this would create a server-side record linking a user's identity to their C2PA certificates—a privacy trade-off we were unwilling to make.
Our Solution: Anonymous, Hardware-Backed Attestation. We solve this with Android Key Attestation, which allows Google CAs to verify what is being used (a genuine app on a secure device) without ever knowing who is using it (the user). Our CAs also enforce a strict no-logging policy for information like IP addresses that could tie a certificate back to a user.
Challenge 2: The Risk of Traceability Through Key Reuse. A significant privacy risk in any provenance system is traceability. If the same device or app-specific cryptographic key is used to sign multiple photos, those images can be linked by comparing the key. An adversary could potentially connect a photo someone posts publicly under their real name with a photo they post anonymously, deanonymizing the creator.
Our Solution: Unique Certificates. We eliminate this threat with a maximally private approach. Each key and certificate is used to sign exactly one image. No two images ever share the same public key, a "One-and-Done" Certificate Management Strategy, making it cryptographically impossible to link them. This engineering investment in user privacy is designed to set a clear standard for the industry.
Overall, you can use Content Credentials on Pixel 10 without fear that another person or Google could use it to link any of your images to you or one another.
Implementations of Content Credentials use trusted time-stamps to ensure the credentials can be validated even after the certificate used to produce them expires. Obtaining these trusted time-stamps typically requires connectivity to a Time-Stamping Authority (TSA) server. But what happens if the device is offline?
This is not a far-fetched scenario. Imagine you’ve captured a stunning photo of a remote waterfall. The image has Content Credentials that prove that it was captured by a camera, but the cryptographic certificate used to produce them will eventually expire. Without a time-stamp, that proof could become untrusted, and you're too far from a cell signal, which is required to receive one.
To solve this, Pixel developed an on-device, offline TSA.
Powered by the security features of Tensor, Pixel maintains a trusted clock in a secure environment, completely isolated from the user-controlled one in Android. The clock is synchronized regularly from a trusted source while the device is online, and is maintained even after the device goes offline (as long as the phone remains powered on). This allows your device to generate its own cryptographically-signed time-stamps the moment you press the shutter—no connection required. It ensures the story behind your photo remains verifiable and trusted after its certificate expires, whether you took it in your living room or at the top of a mountain.
C2PA Content Credentials are not the sole solution for identifying the provenance of digital media. They are, however, a tangible step toward more media transparency and trust as we continue to unlock more human creativity with AI.
In our initial implementation of Content Credentials on the Android platform and Pixel 10 lineup, we prioritized a higher standard of privacy, security, and usability. We invite other implementers of Content Credentials to evaluate our approach and leverage these same foundational hardware and software security primitives. The full potential of these technologies can only be realized through widespread ecosystem adoption.
We look forward to adding Content Credentials across more Google products in the near future.
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