CVE-2022-49394:詳細資料

CVE-2022-49394

5.5
/
中危
0.02%V4
2025-02-26
02h11 +00:00
Local
2025-05-04
12h44 +00:00
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CVE 描述

blk-iolatency: Fix inflight count imbalances and IO hangs on offline

In the Linux kernel, the following vulnerability has been resolved: blk-iolatency: Fix inflight count imbalances and IO hangs on offline iolatency needs to track the number of inflight IOs per cgroup. As this tracking can be expensive, it is disabled when no cgroup has iolatency configured for the device. To ensure that the inflight counters stay balanced, iolatency_set_limit() freezes the request_queue while manipulating the enabled counter, which ensures that no IO is in flight and thus all counters are zero. Unfortunately, iolatency_set_limit() isn't the only place where the enabled counter is manipulated. iolatency_pd_offline() can also dec the counter and trigger disabling. As this disabling happens without freezing the q, this can easily happen while some IOs are in flight and thus leak the counts. This can be easily demonstrated by turning on iolatency on an one empty cgroup while IOs are in flight in other cgroups and then removing the cgroup. Note that iolatency shouldn't have been enabled elsewhere in the system to ensure that removing the cgroup disables iolatency for the whole device. The following keeps flipping on and off iolatency on sda: echo +io > /sys/fs/cgroup/cgroup.subtree_control while true; do mkdir -p /sys/fs/cgroup/test echo '8:0 target=100000' > /sys/fs/cgroup/test/io.latency sleep 1 rmdir /sys/fs/cgroup/test sleep 1 done and there's concurrent fio generating direct rand reads: fio --name test --filename=/dev/sda --direct=1 --rw=randread \ --runtime=600 --time_based --iodepth=256 --numjobs=4 --bs=4k while monitoring with the following drgn script: while True: for css in css_for_each_descendant_pre(prog['blkcg_root'].css.address_of_()): for pos in hlist_for_each(container_of(css, 'struct blkcg', 'css').blkg_list): blkg = container_of(pos, 'struct blkcg_gq', 'blkcg_node') pd = blkg.pd[prog['blkcg_policy_iolatency'].plid] if pd.value_() == 0: continue iolat = container_of(pd, 'struct iolatency_grp', 'pd') inflight = iolat.rq_wait.inflight.counter.value_() if inflight: print(f'inflight={inflight} {disk_name(blkg.q.disk).decode("utf-8")} ' f'{cgroup_path(css.cgroup).decode("utf-8")}') time.sleep(1) The monitoring output looks like the following: inflight=1 sda /user.slice inflight=1 sda /user.slice ... inflight=14 sda /user.slice inflight=13 sda /user.slice inflight=17 sda /user.slice inflight=15 sda /user.slice inflight=18 sda /user.slice inflight=17 sda /user.slice inflight=20 sda /user.slice inflight=19 sda /user.slice <- fio stopped, inflight stuck at 19 inflight=19 sda /user.slice inflight=19 sda /user.slice If a cgroup with stuck inflight ends up getting throttled, the throttled IOs will never get issued as there's no completion event to wake it up leading to an indefinite hang. This patch fixes the bug by unifying enable handling into a work item which is automatically kicked off from iolatency_set_min_lat_nsec() which is called from both iolatency_set_limit() and iolatency_pd_offline() paths. Punting to a work item is necessary as iolatency_pd_offline() is called under spinlocks while freezing a request_queue requires a sleepable context. This also simplifies the code reducing LOC sans the comments and avoids the unnecessary freezes which were happening whenever a cgroup's latency target is newly set or cleared.

CVE 資訊

相關弱點

CWE-ID 弱點名稱 來源
CWE Other 暫無資訊。

指標

指標 評分 嚴重程度 CVSS 向量 來源
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 是一種預測漏洞被利用可能性的評分模型。

EPSS 評分

EPSS 模型產生介於 0 到 1(0% 到 100%)之間的概率分數。分數越高,漏洞被利用的概率越大。

EPSS 百分位數

百分位數用於根據 EPSS 分數對 CVE 進行排名。例如,EPSS 評分在第 95 百分位的 CVE 比 95% 的其他 CVE 更有可能被利用。因此,百分位數用於比較某 CVE 的 EPSS 分數與其他 CVE 的相對位置。

相關產品

設定 0

Linux>>Linux_kernel >> Version 從(含) 4.19.29 至(不含) 4.19.247

Linux>>Linux_kernel >> Version 從(含) 4.20.16 至(不含) 5.0

Linux>>Linux_kernel >> Version 從(含) 5.0.1 至(不含) 5.4.198

Linux>>Linux_kernel >> Version 從(含) 5.5 至(不含) 5.10.121

Linux>>Linux_kernel >> Version 從(含) 5.11 至(不含) 5.15.46

Linux>>Linux_kernel >> Version 從(含) 5.16 至(不含) 5.17.14

Linux>>Linux_kernel >> Version 從(含) 5.18 至(不含) 5.18.3

Linux>>Linux_kernel >> Version 5.0

Linux>>Linux_kernel >> Version 5.0

Linux>>Linux_kernel >> Version 5.0

Linux>>Linux_kernel >> Version 5.0

參考資料