CVE-2021-47242 : Détail

CVE-2021-47242

7.8
/
Haute
0.02%V4
Local
2024-05-21
14h19 +00:00
2024-12-19
07h38 +00:00
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Descriptions du CVE

mptcp: fix soft lookup in subflow_error_report()

In the Linux kernel, the following vulnerability has been resolved: mptcp: fix soft lookup in subflow_error_report() Maxim reported a soft lookup in subflow_error_report(): watchdog: BUG: soft lockup - CPU#0 stuck for 22s! [swapper/0:0] RIP: 0010:native_queued_spin_lock_slowpath RSP: 0018:ffffa859c0003bc0 EFLAGS: 00000202 RAX: 0000000000000101 RBX: 0000000000000001 RCX: 0000000000000000 RDX: ffff9195c2772d88 RSI: 0000000000000000 RDI: ffff9195c2772d88 RBP: ffff9195c2772d00 R08: 00000000000067b0 R09: c6e31da9eb1e44f4 R10: ffff9195ef379700 R11: ffff9195edb50710 R12: ffff9195c2772d88 R13: ffff9195f500e3d0 R14: ffff9195ef379700 R15: ffff9195ef379700 FS: 0000000000000000(0000) GS:ffff91961f400000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 000000c000407000 CR3: 0000000002988000 CR4: 00000000000006f0 Call Trace: _raw_spin_lock_bh subflow_error_report mptcp_subflow_data_available __mptcp_move_skbs_from_subflow mptcp_data_ready tcp_data_queue tcp_rcv_established tcp_v4_do_rcv tcp_v4_rcv ip_protocol_deliver_rcu ip_local_deliver_finish __netif_receive_skb_one_core netif_receive_skb rtl8139_poll 8139too __napi_poll net_rx_action __do_softirq __irq_exit_rcu common_interrupt The calling function - mptcp_subflow_data_available() - can be invoked from different contexts: - plain ssk socket lock - ssk socket lock + mptcp_data_lock - ssk socket lock + mptcp_data_lock + msk socket lock. Since subflow_error_report() tries to acquire the mptcp_data_lock, the latter two call chains will cause soft lookup. This change addresses the issue moving the error reporting call to outer functions, where the held locks list is known and the we can acquire only the needed one.

Informations du CVE

Faiblesses connexes

CWE-ID Nom de la faiblesse Source
CWE-667 Improper Locking
The product does not properly acquire or release a lock on a resource, leading to unexpected resource state changes and behaviors.

Métriques

Métriques Score Gravité CVSS Vecteur Source
V3.1 7.8 HIGH CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/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.

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.

Required

Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited. For example, a successful exploit may only be possible during the installation of an application by a system administrator.

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.

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EPSS

EPSS est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.

Score EPSS

Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.

Percentile EPSS

Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.11.12 To (excluding) 5.12.13

Linux>>Linux_kernel >> Version 5.13

Linux>>Linux_kernel >> Version 5.13

Linux>>Linux_kernel >> Version 5.13

Linux>>Linux_kernel >> Version 5.13

Linux>>Linux_kernel >> Version 5.13

Linux>>Linux_kernel >> Version 5.13

Références