CVE-2024-26675 Detail

CVE-2024-26675

Score / Severity

5.5

Medium

EPSS

0.04%V3

Vector

Local

Published

2024-04-02
07h01 +00:00

Modified

2024-12-19
08h44 +00:00

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CVE Descriptions

ppp_async: limit MRU to 64K

In the Linux kernel, the following vulnerability has been resolved: ppp_async: limit MRU to 64K syzbot triggered a warning [1] in __alloc_pages(): WARN_ON_ONCE_GFP(order > MAX_PAGE_ORDER, gfp) Willem fixed a similar issue in commit c0a2a1b0d631 ("ppp: limit MRU to 64K") Adopt the same sanity check for ppp_async_ioctl(PPPIOCSMRU) [1]: WARNING: CPU: 1 PID: 11 at mm/page_alloc.c:4543 __alloc_pages+0x308/0x698 mm/page_alloc.c:4543 Modules linked in: CPU: 1 PID: 11 Comm: kworker/u4:0 Not tainted 6.8.0-rc2-syzkaller-g41bccc98fb79 #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 11/17/2023 Workqueue: events_unbound flush_to_ldisc pstate: 204000c5 (nzCv daIF +PAN -UAO -TCO -DIT -SSBS BTYPE=--) pc : __alloc_pages+0x308/0x698 mm/page_alloc.c:4543 lr : __alloc_pages+0xc8/0x698 mm/page_alloc.c:4537 sp : ffff800093967580 x29: ffff800093967660 x28: ffff8000939675a0 x27: dfff800000000000 x26: ffff70001272ceb4 x25: 0000000000000000 x24: ffff8000939675c0 x23: 0000000000000000 x22: 0000000000060820 x21: 1ffff0001272ceb8 x20: ffff8000939675e0 x19: 0000000000000010 x18: ffff800093967120 x17: ffff800083bded5c x16: ffff80008ac97500 x15: 0000000000000005 x14: 1ffff0001272cebc x13: 0000000000000000 x12: 0000000000000000 x11: ffff70001272cec1 x10: 1ffff0001272cec0 x9 : 0000000000000001 x8 : ffff800091c91000 x7 : 0000000000000000 x6 : 000000000000003f x5 : 00000000ffffffff x4 : 0000000000000000 x3 : 0000000000000020 x2 : 0000000000000008 x1 : 0000000000000000 x0 : ffff8000939675e0 Call trace: __alloc_pages+0x308/0x698 mm/page_alloc.c:4543 __alloc_pages_node include/linux/gfp.h:238 [inline] alloc_pages_node include/linux/gfp.h:261 [inline] __kmalloc_large_node+0xbc/0x1fc mm/slub.c:3926 __do_kmalloc_node mm/slub.c:3969 [inline] __kmalloc_node_track_caller+0x418/0x620 mm/slub.c:4001 kmalloc_reserve+0x17c/0x23c net/core/skbuff.c:590 __alloc_skb+0x1c8/0x3d8 net/core/skbuff.c:651 __netdev_alloc_skb+0xb8/0x3e8 net/core/skbuff.c:715 netdev_alloc_skb include/linux/skbuff.h:3235 [inline] dev_alloc_skb include/linux/skbuff.h:3248 [inline] ppp_async_input drivers/net/ppp/ppp_async.c:863 [inline] ppp_asynctty_receive+0x588/0x186c drivers/net/ppp/ppp_async.c:341 tty_ldisc_receive_buf+0x12c/0x15c drivers/tty/tty_buffer.c:390 tty_port_default_receive_buf+0x74/0xac drivers/tty/tty_port.c:37 receive_buf drivers/tty/tty_buffer.c:444 [inline] flush_to_ldisc+0x284/0x6e4 drivers/tty/tty_buffer.c:494 process_one_work+0x694/0x1204 kernel/workqueue.c:2633 process_scheduled_works kernel/workqueue.c:2706 [inline] worker_thread+0x938/0xef4 kernel/workqueue.c:2787 kthread+0x288/0x310 kernel/kthread.c:388 ret_from_fork+0x10/0x20 arch/arm64/kernel/entry.S:860

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-770	Allocation of Resources Without Limits or Throttling The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	5.5	MEDIUM	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/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. None There is no loss of confidentiality within 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. 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.

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