CVE-2023-52438 Detail

CVE-2023-52438

Score / Severity

7.8

High

CVE Descriptions

binder: fix use-after-free in shinker's callback

In the Linux kernel, the following vulnerability has been resolved: binder: fix use-after-free in shinker's callback The mmap read lock is used during the shrinker's callback, which means that using alloc->vma pointer isn't safe as it can race with munmap(). As of commit dd2283f2605e ("mm: mmap: zap pages with read mmap_sem in munmap") the mmap lock is downgraded after the vma has been isolated. I was able to reproduce this issue by manually adding some delays and triggering page reclaiming through the shrinker's debug sysfs. The following KASAN report confirms the UAF: ================================================================== BUG: KASAN: slab-use-after-free in zap_page_range_single+0x470/0x4b8 Read of size 8 at addr ffff356ed50e50f0 by task bash/478 CPU: 1 PID: 478 Comm: bash Not tainted 6.6.0-rc5-00055-g1c8b86a3799f-dirty #70 Hardware name: linux,dummy-virt (DT) Call trace: zap_page_range_single+0x470/0x4b8 binder_alloc_free_page+0x608/0xadc __list_lru_walk_one+0x130/0x3b0 list_lru_walk_node+0xc4/0x22c binder_shrink_scan+0x108/0x1dc shrinker_debugfs_scan_write+0x2b4/0x500 full_proxy_write+0xd4/0x140 vfs_write+0x1ac/0x758 ksys_write+0xf0/0x1dc __arm64_sys_write+0x6c/0x9c Allocated by task 492: kmem_cache_alloc+0x130/0x368 vm_area_alloc+0x2c/0x190 mmap_region+0x258/0x18bc do_mmap+0x694/0xa60 vm_mmap_pgoff+0x170/0x29c ksys_mmap_pgoff+0x290/0x3a0 __arm64_sys_mmap+0xcc/0x144 Freed by task 491: kmem_cache_free+0x17c/0x3c8 vm_area_free_rcu_cb+0x74/0x98 rcu_core+0xa38/0x26d4 rcu_core_si+0x10/0x1c __do_softirq+0x2fc/0xd24 Last potentially related work creation: __call_rcu_common.constprop.0+0x6c/0xba0 call_rcu+0x10/0x1c vm_area_free+0x18/0x24 remove_vma+0xe4/0x118 do_vmi_align_munmap.isra.0+0x718/0xb5c do_vmi_munmap+0xdc/0x1fc __vm_munmap+0x10c/0x278 __arm64_sys_munmap+0x58/0x7c Fix this issue by performing instead a vma_lookup() which will fail to find the vma that was isolated before the mmap lock downgrade. Note that this option has better performance than upgrading to a mmap write lock which would increase contention. Plus, mmap_write_trylock() has been recently removed anyway.

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-416	Use After Free The product reuses or references memory after it has been freed. At some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. Any operations using the original pointer are no longer valid because the memory "belongs" to the code that operates on the new pointer.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	7.8	HIGH	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H More informations Base: Exploitabilty Metrics The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component. Attack Vector This metric reflects the context by which vulnerability exploitation is possible. Local The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Attack Complexity This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. Low Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component. Privileges Required This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability. Low The attacker requires privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources. User Interaction This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component. None The vulnerable system can be exploited without interaction from any user. Base: Scope Metrics The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope. Scope Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs. Unchanged An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority. Base: Impact Metrics The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve. Confidentiality Impact This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability. High There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server. Integrity Impact This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. High There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component. Availability Impact This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. High There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable). Temporal Metrics The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability. Environmental Metrics These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.	[email protected]

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

EPSS First.org