Table Of Links Table Of Links Abstract Abstract 1. Introduction 1. Introduction 1. Introduction 2. Background 2. Background 2. Background Memory Tagging Extension
Speculative Execution Attack Memory Tagging Extension Speculative Execution Attack 3. Threat Model 3. Threat Model 3. Threat Model 4. Finding Tag Leakage Gadgets 4. Finding Tag Leakage Gadgets 4. Finding Tag Leakage Gadgets Tag Leakage Template
Tag Leakage Fuzzing Tag Leakage Template Tag Leakage Fuzzing 5. TIKTAG Gadgets 5. TIKTAG Gadgets 5. TIKTAG Gadgets TIKTAG-v1: Exploiting Speculation Shrinkage
TIKTAG-v2: Exploiting Store-to-Load Forwarding TIKTAG-v1: Exploiting Speculation Shrinkage TIKTAG-v2: Exploiting Store-to-Load Forwarding 6. Real-World Attacks 6. Real-World Attacks 6. Real-World Attacks 6.1. Attacking Chrome 7. Evaluation 7. Evaluation 7. Evaluation 8. Related work 8. Related work 8. Related work 9. Conclusion And References 9. Conclusion And References 9. Conclusion And References Evaluation In this section, we evaluate the TIKTAG gadgets and MTE bypass exploits in two MTE-enabled systems, the Chrome browser (§7.1) and the Linux kernel (§7.2). All experiments were conducted on the Google Pixel 8 devices. 7.1. Chrome Browser Tag Leakage 7.1. Chrome Browser Tag Leakage We evaluated the TIKTAG-v2 gadget in the V8 JavaScript engine in two environments: i) the standalone V8 JavaScript engine, and ii) the Chromium application. The V8 JavaScript engine runs as an independent process, reducing the interference from the Android platform. The Chromium application runs as an Android application, subject to the Android’s application management such as process scheduling and thermal throttling. The experiments were conducted with the V8 v12.1.10 and Chromium v119.0.6022.0 release build. We leveraged MTE random tagging schemes provided by the underlying allocators (Table 1). The standalone V8 used the Scudo allocator [3] (i.e., Android default allocator), which supports 16 random tags for random tagging and offers the OddEvenTags option. When OddEvenTags is enabled, Scudo alternates odd and even random tags for neighboring objects, preventing linear overflow (i.e., OVERFLOW_TUNING). When OddEvenTags is disabled, Scudo utilizes all 16 random tags for every object to maximize tag entropy for use-afterfree detection (i.e., UAF_TUNING). By default, OddEvenTags is enabled, while we evaluate both settings. Upon releasing an object, Scudo sets a new random tag that does not collide with the previous one. PartitionAlloc (i.e., Chrome default allocator) utilizes 15 random tags and reserves the tag 0x0 for unallocated memory. When releasing an object, PartitionAlloc increments the tag by one, making the tag of the re-allocated memory address predictable. However, in real-world exploits, it is challenging to precisely control the number of releases for a specific address, thus we assume the attacker still needs to leak the tag after each allocation. For the evaluation, we constructed the TIKTAG-v2 gadget in JavaScript (Figure 6) and developed MTE bypass attacks as described in §6.1.3. These attacks exploit artificial vulnerabilities designed to mimic real-world renderer vulnerabilities, specifically linear overflow [44] and use-after-free [42]. We developed custom JavaScript APIs to allocate, free, locate, and access the renderer object to manipulate the memory layout and trigger the vulnerabilities. It’s worth noting that our evaluation shows the best-case performance of MTE bypass attacks since real-world renderer exploits involve additional overheads in triggering the vulnerabilities and controlling the memory layout. V8 JavaScript Engine. In the standalone V8 JavaScript engine, we evaluated the tag leakage of the TIKTAG-v2 gadget with cache eviction and a memory-based timer. For cache eviction, we used an L1 index-based random eviction set, 500 elements for slow[0] and probe[PROBE_OFFSET], 300 elements for victim.length. The eviction performance of the random eviction set varies on each run, so we repeated the same test 5 times and listed the best result. V8 JavaScript Engine. The random eviction can be optimized with eviction set algorithms [70]. We used a memory counter-based timer with a custom worker thread incrementing a counter, which is equivalent to the SharedArrayBuffer timer [58]. For all possible tag guesses (i.e., 0x0-0xf), we measured the access latency of probe[PROBE_OFFSET] after the gadget 256 times and determined the guessed tag with the minimum average access latency as the correct tag. Table 2 summarizes the MTE bypass exploit results in V8. For a single tag leakage, the gadget was successful in all 100 runs (100%), with an average elapsed time of 3.04 seconds. MTE bypass exploits were evaluated over 100 runs for each vulnerability and OddEvenTags configuration (i.e., disabled (0) and enabled (1)). We excluded linear overflow exploit with OddEvenTags enabled, since the memory corruption is always detected with spatially adjacent objects tagged with different tags and the attack would always fail. The results demonstrate that the attacks were successful in over 97% of the runs, with an average elapsed time of 6 to 13 seconds. In use-after-free exploits, enabling OddEvenTags decreased the average elapsed time by around 40%, due to the decrease in tag entropy from 16 to 8, doubling the chance of tag collision between the temporally adjacent objects. Chromium Application. In the Chromium application setting, we evaluated the TIKTAG-v2 gadget with cache flushing and a SharedArrayBuffer-based timer. Unlike V8, random eviction did not effectively evict cache lines, so we manually flushed the cache lines with dc civac instruction. We attribute this to the aggressive resource management of Android, which can be addressed in the future with cache eviction algorithms tailored for mobile applications. Chromium Application. To measure the cache eviction set overhead, we included the cache eviction set traversals in all experiments, using the same cache eviction configuration of the V8 experiments. We measured access latency with a SharedArrayBuffer-based timer as suggested by web browser speculative execution studies [8, 21]. The MTE bypass exploits experiments were conducted in the same manner as the V8 experiments. Table 3 shows the MTE bypass exploit results in the Chromium application. The tag leakage of the TIKTAG-v2 gadget in the Chromium application was successful in 95% of 100 runs, with an average elapsed time of 2.54 seconds. With the MTE bypass exploits, success rates were over 95% for both vulnerability types, with an average elapsed time of 16.11 and 21.90 seconds for linear overflow and use-afterfree, respectively. 7.2. Linux Kernel Tag Leakage 7.2. Linux Kernel Tag Leakage The experiments were conducted on the Android 14 kernel v5.15 using the default configuration. We used 15 random tags (i.e., 0x0–0xe) for kernel objects, as tag 0xf is commonly reserved for the access-all tag in the Linux kernel [37]. The cache line eviction of kernel address cond_ptr to trigger the speculative execution was achieved by cache line bouncing [25] from the user space. For cache measurement, we utilized the virtual counter (i.e., CNTVCT_EL0) to determine the cache hit or miss with the threshold 1.0, which is accessible from the user space. As the virtual counter has a lower resolution (24.5MHz) than the CPU cycle frequency (2.4-2.9 GHz), the accuracy of the cache hit rate is lower than the physical CPU counter-based measurements in §5. The access time was measured in the user space or kernel space, depending on the experiment. Kernel Context Evaluation. We first evaluated whether TIKTAG gadgets can leak MTE tags in the Linux kernel context (Figure 11). We created custom system calls containing TIKTAG-v1 (Figure 2) and TIKTAG-v2 (Figure 6) gadgets and executed them by calling the system calls from the user space. In CHECK, we accessed the guess_ptr that holds either the correct or wrong tag Tg. In TEST, test_ptr pointed to Kernel Context Evaluation. either a kernel address or a user space address, depending on whether the cache state difference was measured in the kernel or user space. When we leveraged a user space address as test_ptr, we passed a user buffer pointer to the kernel space as a system call argument and accessed the pointer in TEST using copy_to_user(). The user space address was flushed in the user space before the system call invocation, and the cache state was measured after the system call returned. When we used a kernel address as test_ptr, the cache flush and measurement were performed in the kernel. Each experiment measured the access time over 1000 runs. When executing TIKTAG-v1 in the kernel context, the MTE tag leakage was feasible in both the kernel and user space, where the user space measurement results are shown in Figure 11a. Compared to the user space gadget evaluation (Figure 3), the kernel context required more loads in CHECK to distinguish the cache state difference. Specifically, the cache state difference was discernible from 4 loads in the kernel context, while the user space context required only 2 loads. This can be attributed to the noises from the kernel to the user space context switch overhead, such that the cache hit rates of the tag match cases were lower (i.e., under 90%) than the user space gadget evaluation (i.e., 100%). When executing the TIKTAG-v2 gadget in the kernel space, MTE tag leakage was observed only in the kernel space (Figure 11b). When we measured the access latency of test_ptr in the user space, the gadget did not exhibit a cache state difference. Although the TIKTAG-v2 gadget might not be directly exploitable in the user space, cache state amplification techniques [21, 72] could be utilized to make it observable from the user space. Kernel MTE Bypass Exploit. We evaluated MTE bypass exploits in the Linux kernel with two TIKTAG-v1 gadgets: an artificial TIKTAG-v1 gadget with 8 loads in CHECK (i.e., artificial) and a real-world TIKTAG-v1 gadget in snd_timer_user_read() (Figure 10). The artificial gadget evaluates the best-case performance of MTE bypass attacks, while the snd_timer_user_read() gadget demonstrates realworld exploit performance. Kernel MTE Bypass Exploit. Both gadgets were triggered by invoking the system call containing the gadget from the user space, leveraging a user space address as test_ptr, and measuring the access latency of test_ptr in user space. We conducted a tag leakage attack and MTE bypass attack for each gadget. For the MTE bypass attack, we synthesized a buffer overflow vulnerability. Each gadget dereferenced the vulnerable pointer (i.e., guess_ptr) to trigger tag checks; an out-of-bounds pointer and a dangling pointer for the buffer overflow and use-after-free exploits, respectively. The exploit methodology followed the process described in §D. summarizes the MTE bypass exploit results. For a single tag leakage, the gadgets successfully leaked the correct tag in all 100 runs (100%), with an average elapsed time of 0.12 seconds in the artificial gadget, and 3.38 seconds in the snd_timer_user_read() gadget. The MTE bypass exploit for the artificial TIKTAG-v1 gadget was successful in all 100 runs (100%), with an average elapsed time of 0.18 seconds. summarizes the MTE bypass exploit results. Regarding the MTE bypass exploit for the snd_timer_user_read() gadget, the success rate was 97% with an average elapsed time of 6.86 seconds. As the snd_timer_user_read() gadget involves complex kernel function calls and memory accesses, the performance of the MTE bypass exploit is slightly lower compared to the artificial gadget. Nevertheless, it still demonstrates a high success rate within a reasonable time frame. Authors:

Juhee Kim
Jinbum Park
Sihyeon Roh
Jaeyoung Chung
Youngjoo Lee
Taesoo Kim
Byoungyoung Lee Authors: Authors: Juhee Kim
Jinbum Park
Sihyeon Roh
Jaeyoung Chung
Youngjoo Lee
Taesoo Kim
Byoungyoung Lee Juhee Kim Juhee Kim Jinbum Park Jinbum Park Sihyeon Roh Sihyeon Roh Jaeyoung Chung Jaeyoung Chung Youngjoo Lee Youngjoo Lee Taesoo Kim Taesoo Kim Byoungyoung Lee Byoungyoung Lee This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv iv

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Why Hardware Memory Tagging Isn’t the Security Silver Bullet It Promised to Be

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