CVE-2024-53170 : Detail

CVE-2024-53170

7.8
/
High
Memory Corruption
0.03%V4
Local
2024-12-27
13h49 +00:00
2025-02-10
17h21 +00:00
CVE.org
NVD
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CVE Descriptions

block: fix uaf for flush rq while iterating tags

In the Linux kernel, the following vulnerability has been resolved: block: fix uaf for flush rq while iterating tags blk_mq_clear_flush_rq_mapping() is not called during scsi probe, by checking blk_queue_init_done(). However, QUEUE_FLAG_INIT_DONE is cleared in del_gendisk by commit aec89dc5d421 ("block: keep q_usage_counter in atomic mode after del_gendisk"), hence for disk like scsi, following blk_mq_destroy_queue() will not clear flush rq from tags->rqs[] as well, cause following uaf that is found by our syzkaller for v6.6: ================================================================== BUG: KASAN: slab-use-after-free in blk_mq_find_and_get_req+0x16e/0x1a0 block/blk-mq-tag.c:261 Read of size 4 at addr ffff88811c969c20 by task kworker/1:2H/224909 CPU: 1 PID: 224909 Comm: kworker/1:2H Not tainted 6.6.0-ga836a5060850 #32 Workqueue: kblockd blk_mq_timeout_work Call Trace: __dump_stack lib/dump_stack.c:88 [inline] dump_stack_lvl+0x91/0xf0 lib/dump_stack.c:106 print_address_description.constprop.0+0x66/0x300 mm/kasan/report.c:364 print_report+0x3e/0x70 mm/kasan/report.c:475 kasan_report+0xb8/0xf0 mm/kasan/report.c:588 blk_mq_find_and_get_req+0x16e/0x1a0 block/blk-mq-tag.c:261 bt_iter block/blk-mq-tag.c:288 [inline] __sbitmap_for_each_set include/linux/sbitmap.h:295 [inline] sbitmap_for_each_set include/linux/sbitmap.h:316 [inline] bt_for_each+0x455/0x790 block/blk-mq-tag.c:325 blk_mq_queue_tag_busy_iter+0x320/0x740 block/blk-mq-tag.c:534 blk_mq_timeout_work+0x1a3/0x7b0 block/blk-mq.c:1673 process_one_work+0x7c4/0x1450 kernel/workqueue.c:2631 process_scheduled_works kernel/workqueue.c:2704 [inline] worker_thread+0x804/0xe40 kernel/workqueue.c:2785 kthread+0x346/0x450 kernel/kthread.c:388 ret_from_fork+0x4d/0x80 arch/x86/kernel/process.c:147 ret_from_fork_asm+0x1b/0x30 arch/x86/entry/entry_64.S:293 Allocated by task 942: kasan_save_stack+0x22/0x50 mm/kasan/common.c:45 kasan_set_track+0x25/0x30 mm/kasan/common.c:52 ____kasan_kmalloc mm/kasan/common.c:374 [inline] __kasan_kmalloc mm/kasan/common.c:383 [inline] __kasan_kmalloc+0xaa/0xb0 mm/kasan/common.c:380 kasan_kmalloc include/linux/kasan.h:198 [inline] __do_kmalloc_node mm/slab_common.c:1007 [inline] __kmalloc_node+0x69/0x170 mm/slab_common.c:1014 kmalloc_node include/linux/slab.h:620 [inline] kzalloc_node include/linux/slab.h:732 [inline] blk_alloc_flush_queue+0x144/0x2f0 block/blk-flush.c:499 blk_mq_alloc_hctx+0x601/0x940 block/blk-mq.c:3788 blk_mq_alloc_and_init_hctx+0x27f/0x330 block/blk-mq.c:4261 blk_mq_realloc_hw_ctxs+0x488/0x5e0 block/blk-mq.c:4294 blk_mq_init_allocated_queue+0x188/0x860 block/blk-mq.c:4350 blk_mq_init_queue_data block/blk-mq.c:4166 [inline] blk_mq_init_queue+0x8d/0x100 block/blk-mq.c:4176 scsi_alloc_sdev+0x843/0xd50 drivers/scsi/scsi_scan.c:335 scsi_probe_and_add_lun+0x77c/0xde0 drivers/scsi/scsi_scan.c:1189 __scsi_scan_target+0x1fc/0x5a0 drivers/scsi/scsi_scan.c:1727 scsi_scan_channel drivers/scsi/scsi_scan.c:1815 [inline] scsi_scan_channel+0x14b/0x1e0 drivers/scsi/scsi_scan.c:1791 scsi_scan_host_selected+0x2fe/0x400 drivers/scsi/scsi_scan.c:1844 scsi_scan+0x3a0/0x3f0 drivers/scsi/scsi_sysfs.c:151 store_scan+0x2a/0x60 drivers/scsi/scsi_sysfs.c:191 dev_attr_store+0x5c/0x90 drivers/base/core.c:2388 sysfs_kf_write+0x11c/0x170 fs/sysfs/file.c:136 kernfs_fop_write_iter+0x3fc/0x610 fs/kernfs/file.c:338 call_write_iter include/linux/fs.h:2083 [inline] new_sync_write+0x1b4/0x2d0 fs/read_write.c:493 vfs_write+0x76c/0xb00 fs/read_write.c:586 ksys_write+0x127/0x250 fs/read_write.c:639 do_syscall_x64 arch/x86/entry/common.c:51 [inline] do_syscall_64+0x70/0x120 arch/x86/entry/common.c:81 entry_SYSCALL_64_after_hwframe+0x78/0xe2 Freed by task 244687: kasan_save_stack+0x22/0x50 mm/kasan/common.c:45 kasan_set_track+0x25/0x30 mm/kasan/common.c:52 kasan_save_free_info+0x2b/0x50 mm/kasan/generic.c:522 ____kasan_slab_free mm/kasan/common.c:236 [inline] __kasan_slab_free+0x12a/0x1b0 mm/kasan/common.c:244 kasan_slab_free include/linux/kasan.h:164 [in ---truncated---

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

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.

 nvd@nist.gov

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

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.19 To (excluding) 6.11.11

Linux>>Linux_kernel >> Version From (including) 6.12 To (excluding) 6.12.2

References

The information presented on CVE Find originates from several carefully selected reference sources. CVE data is provided by MITRE Corporation and the National Vulnerability Database (NVD). The Known Exploited Vulnerabilities (KEV) catalog is sourced from the Cybersecurity and Infrastructure Security Agency (CISA), while EPSS scores come from FIRST.org. Additionally, data regarding software weaknesses (CWE) and common attack patterns (CAPEC) is maintained by MITRE Corporation, and information on hardware and software configurations (CPE) is provided by the NVD.