CVE-2024-26890 : Detail

CVE-2024-26890

6.5
/
Medium
Overflow
0.45%V4
Network
2024-04-17
10h27 +00:00
2024-12-19
08h49 +00:00
CVE.org
NVD
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CVE Descriptions

Bluetooth: btrtl: fix out of bounds memory access

In the Linux kernel, the following vulnerability has been resolved: Bluetooth: btrtl: fix out of bounds memory access The problem is detected by KASAN. btrtl driver uses private hci data to store 'struct btrealtek_data'. If btrtl driver is used with btusb, then memory for private hci data is allocated in btusb. But no private data is allocated after hci_dev, when btrtl is used with hci_h5. This commit adds memory allocation for hci_h5 case. ================================================================== BUG: KASAN: slab-out-of-bounds in btrtl_initialize+0x6cc/0x958 [btrtl] Write of size 8 at addr ffff00000f5a5748 by task kworker/u9:0/76 Hardware name: Pine64 PinePhone (1.2) (DT) Workqueue: hci0 hci_power_on [bluetooth] Call trace: dump_backtrace+0x9c/0x128 show_stack+0x20/0x38 dump_stack_lvl+0x48/0x60 print_report+0xf8/0x5d8 kasan_report+0x90/0xd0 __asan_store8+0x9c/0xc0 [btrtl] h5_btrtl_setup+0xd0/0x2f8 [hci_uart] h5_setup+0x50/0x80 [hci_uart] hci_uart_setup+0xd4/0x260 [hci_uart] hci_dev_open_sync+0x1cc/0xf68 [bluetooth] hci_dev_do_open+0x34/0x90 [bluetooth] hci_power_on+0xc4/0x3c8 [bluetooth] process_one_work+0x328/0x6f0 worker_thread+0x410/0x778 kthread+0x168/0x178 ret_from_fork+0x10/0x20 Allocated by task 53: kasan_save_stack+0x3c/0x68 kasan_save_track+0x20/0x40 kasan_save_alloc_info+0x68/0x78 __kasan_kmalloc+0xd4/0xd8 __kmalloc+0x1b4/0x3b0 hci_alloc_dev_priv+0x28/0xa58 [bluetooth] hci_uart_register_device+0x118/0x4f8 [hci_uart] h5_serdev_probe+0xf4/0x178 [hci_uart] serdev_drv_probe+0x54/0xa0 really_probe+0x254/0x588 __driver_probe_device+0xc4/0x210 driver_probe_device+0x64/0x160 __driver_attach_async_helper+0x88/0x158 async_run_entry_fn+0xd0/0x388 process_one_work+0x328/0x6f0 worker_thread+0x410/0x778 kthread+0x168/0x178 ret_from_fork+0x10/0x20 Last potentially related work creation: kasan_save_stack+0x3c/0x68 __kasan_record_aux_stack+0xb0/0x150 kasan_record_aux_stack_noalloc+0x14/0x20 __queue_work+0x33c/0x960 queue_work_on+0x98/0xc0 hci_recv_frame+0xc8/0x1e8 [bluetooth] h5_complete_rx_pkt+0x2c8/0x800 [hci_uart] h5_rx_payload+0x98/0xb8 [hci_uart] h5_recv+0x158/0x3d8 [hci_uart] hci_uart_receive_buf+0xa0/0xe8 [hci_uart] ttyport_receive_buf+0xac/0x178 flush_to_ldisc+0x130/0x2c8 process_one_work+0x328/0x6f0 worker_thread+0x410/0x778 kthread+0x168/0x178 ret_from_fork+0x10/0x20 Second to last potentially related work creation: kasan_save_stack+0x3c/0x68 __kasan_record_aux_stack+0xb0/0x150 kasan_record_aux_stack_noalloc+0x14/0x20 __queue_work+0x788/0x960 queue_work_on+0x98/0xc0 __hci_cmd_sync_sk+0x23c/0x7a0 [bluetooth] __hci_cmd_sync+0x24/0x38 [bluetooth] btrtl_initialize+0x760/0x958 [btrtl] h5_btrtl_setup+0xd0/0x2f8 [hci_uart] h5_setup+0x50/0x80 [hci_uart] hci_uart_setup+0xd4/0x260 [hci_uart] hci_dev_open_sync+0x1cc/0xf68 [bluetooth] hci_dev_do_open+0x34/0x90 [bluetooth] hci_power_on+0xc4/0x3c8 [bluetooth] process_one_work+0x328/0x6f0 worker_thread+0x410/0x778 kthread+0x168/0x178 ret_from_fork+0x10/0x20 ==================================================================

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-125 Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 6.5 MEDIUM CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:L

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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

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.

Low

There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

None

There is no loss of integrity within the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

Low

Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

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.

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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) 6.2 To (excluding) 6.6.23

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.7.11

Linux>>Linux_kernel >> Version From (including) 6.8 To (excluding) 6.8.2

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.