CVE-2021-47209 : Detail

CVE-2021-47209

5.5
/
Medium
Memory Corruption
0.04%V4
Local
2024-04-10
19h01 +00:00
2024-12-19
07h37 +00:00
CVE.org
NVD
Notifications for a CVE
Stay informed of any changes for a specific CVE.
Notifications manage

CVE Descriptions

sched/fair: Prevent dead task groups from regaining cfs_rq's

In the Linux kernel, the following vulnerability has been resolved: sched/fair: Prevent dead task groups from regaining cfs_rq's Kevin is reporting crashes which point to a use-after-free of a cfs_rq in update_blocked_averages(). Initial debugging revealed that we've live cfs_rq's (on_list=1) in an about to be kfree()'d task group in free_fair_sched_group(). However, it was unclear how that can happen. His kernel config happened to lead to a layout of struct sched_entity that put the 'my_q' member directly into the middle of the object which makes it incidentally overlap with SLUB's freelist pointer. That, in combination with SLAB_FREELIST_HARDENED's freelist pointer mangling, leads to a reliable access violation in form of a #GP which made the UAF fail fast. Michal seems to have run into the same issue[1]. He already correctly diagnosed that commit a7b359fc6a37 ("sched/fair: Correctly insert cfs_rq's to list on unthrottle") is causing the preconditions for the UAF to happen by re-adding cfs_rq's also to task groups that have no more running tasks, i.e. also to dead ones. His analysis, however, misses the real root cause and it cannot be seen from the crash backtrace only, as the real offender is tg_unthrottle_up() getting called via sched_cfs_period_timer() via the timer interrupt at an inconvenient time. When unregister_fair_sched_group() unlinks all cfs_rq's from the dying task group, it doesn't protect itself from getting interrupted. If the timer interrupt triggers while we iterate over all CPUs or after unregister_fair_sched_group() has finished but prior to unlinking the task group, sched_cfs_period_timer() will execute and walk the list of task groups, trying to unthrottle cfs_rq's, i.e. re-add them to the dying task group. These will later -- in free_fair_sched_group() -- be kfree()'ed while still being linked, leading to the fireworks Kevin and Michal are seeing. To fix this race, ensure the dying task group gets unlinked first. However, simply switching the order of unregistering and unlinking the task group isn't sufficient, as concurrent RCU walkers might still see it, as can be seen below: CPU1: CPU2: : timer IRQ: : do_sched_cfs_period_timer(): : : : distribute_cfs_runtime(): : rcu_read_lock(); : : : unthrottle_cfs_rq(): sched_offline_group(): : : walk_tg_tree_from(…,tg_unthrottle_up,…): list_del_rcu(&tg->list); : (1) : list_for_each_entry_rcu(child, &parent->children, siblings) : : (2) list_del_rcu(&tg->siblings); : : tg_unthrottle_up(): unregister_fair_sched_group(): struct cfs_rq *cfs_rq = tg->cfs_rq[cpu_of(rq)]; : : list_del_leaf_cfs_rq(tg->cfs_rq[cpu]); : : : : if (!cfs_rq_is_decayed(cfs_rq) || cfs_rq->nr_running) (3) : list_add_leaf_cfs_rq(cfs_rq); : : : : : : : : : ---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 5.5 MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/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.

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.

 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) 5.13 To (excluding) 5.15.5

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.