CVE-2022-49700 Detail

CVE-2022-49700

Score / Severity

7.8

High

CVE Descriptions

mm/slub: add missing TID updates on slab deactivation

In the Linux kernel, the following vulnerability has been resolved: mm/slub: add missing TID updates on slab deactivation The fastpath in slab_alloc_node() assumes that c->slab is stable as long as the TID stays the same. However, two places in __slab_alloc() currently don't update the TID when deactivating the CPU slab. If multiple operations race the right way, this could lead to an object getting lost; or, in an even more unlikely situation, it could even lead to an object being freed onto the wrong slab's freelist, messing up the `inuse` counter and eventually causing a page to be freed to the page allocator while it still contains slab objects. (I haven't actually tested these cases though, this is just based on looking at the code. Writing testcases for this stuff seems like it'd be a pain...) The race leading to state inconsistency is (all operations on the same CPU and kmem_cache): - task A: begin do_slab_free(): - read TID - read pcpu freelist (==NULL) - check `slab == c->slab` (true) - [PREEMPT A->B] - task B: begin slab_alloc_node(): - fastpath fails (`c->freelist` is NULL) - enter __slab_alloc() - slub_get_cpu_ptr() (disables preemption) - enter ___slab_alloc() - take local_lock_irqsave() - read c->freelist as NULL - get_freelist() returns NULL - write `c->slab = NULL` - drop local_unlock_irqrestore() - goto new_slab - slub_percpu_partial() is NULL - get_partial() returns NULL - slub_put_cpu_ptr() (enables preemption) - [PREEMPT B->A] - task A: finish do_slab_free(): - this_cpu_cmpxchg_double() succeeds() - [CORRUPT STATE: c->slab==NULL, c->freelist!=NULL] From there, the object on c->freelist will get lost if task B is allowed to continue from here: It will proceed to the retry_load_slab label, set c->slab, then jump to load_freelist, which clobbers c->freelist. But if we instead continue as follows, we get worse corruption: - task A: run __slab_free() on object from other struct slab: - CPU_PARTIAL_FREE case (slab was on no list, is now on pcpu partial) - task A: run slab_alloc_node() with NUMA node constraint: - fastpath fails (c->slab is NULL) - call __slab_alloc() - slub_get_cpu_ptr() (disables preemption) - enter ___slab_alloc() - c->slab is NULL: goto new_slab - slub_percpu_partial() is non-NULL - set c->slab to slub_percpu_partial(c) - [CORRUPT STATE: c->slab points to slab-1, c->freelist has objects from slab-2] - goto redo - node_match() fails - goto deactivate_slab - existing c->freelist is passed into deactivate_slab() - inuse count of slab-1 is decremented to account for object from slab-2 At this point, the inuse count of slab-1 is 1 lower than it should be. This means that if we free all allocated objects in slab-1 except for one, SLUB will think that slab-1 is completely unused, and may free its page, leading to use-after-free.

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.	134c704f-9b21-4f2e-91b3-4a467353bcc0

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