limit remains as the maximum number of packets in the tfifo. The same applies to netem's backlog statistics.">

CVE-2024-56770 : Detail

CVE-2024-56770

5.5
/
Medium
0.04%V3
Local
2025-01-08
16h36 +00:00
2025-01-20
06h27 +00:00
CVE.org
NVD
Notifications for a CVE
Stay informed of any changes for a specific CVE.
Notifications manage

CVE Descriptions

net/sched: netem: account for backlog updates from child qdisc

In the Linux kernel, the following vulnerability has been resolved: net/sched: netem: account for backlog updates from child qdisc In general, 'qlen' of any classful qdisc should keep track of the number of packets that the qdisc itself and all of its children holds. In case of netem, 'qlen' only accounts for the packets in its internal tfifo. When netem is used with a child qdisc, the child qdisc can use 'qdisc_tree_reduce_backlog' to inform its parent, netem, about created or dropped SKBs. This function updates 'qlen' and the backlog statistics of netem, but netem does not account for changes made by a child qdisc. 'qlen' then indicates the wrong number of packets in the tfifo. If a child qdisc creates new SKBs during enqueue and informs its parent about this, netem's 'qlen' value is increased. When netem dequeues the newly created SKBs from the child, the 'qlen' in netem is not updated. If 'qlen' reaches the configured sch->limit, the enqueue function stops working, even though the tfifo is not full. Reproduce the bug: Ensure that the sender machine has GSO enabled. Configure netem as root qdisc and tbf as its child on the outgoing interface of the machine as follows: $ tc qdisc add dev root handle 1: netem delay 100ms limit 100 $ tc qdisc add dev parent 1:0 tbf rate 50Mbit burst 1542 latency 50ms Send bulk TCP traffic out via this interface, e.g., by running an iPerf3 client on the machine. Check the qdisc statistics: $ tc -s qdisc show dev Statistics after 10s of iPerf3 TCP test before the fix (note that netem's backlog > limit, netem stopped accepting packets): qdisc netem 1: root refcnt 2 limit 1000 delay 100ms Sent 2767766 bytes 1848 pkt (dropped 652, overlimits 0 requeues 0) backlog 4294528236b 1155p requeues 0 qdisc tbf 10: parent 1:1 rate 50Mbit burst 1537b lat 50ms Sent 2767766 bytes 1848 pkt (dropped 327, overlimits 7601 requeues 0) backlog 0b 0p requeues 0 Statistics after the fix: qdisc netem 1: root refcnt 2 limit 1000 delay 100ms Sent 37766372 bytes 24974 pkt (dropped 9, overlimits 0 requeues 0) backlog 0b 0p requeues 0 qdisc tbf 10: parent 1:1 rate 50Mbit burst 1537b lat 50ms Sent 37766372 bytes 24974 pkt (dropped 327, overlimits 96017 requeues 0) backlog 0b 0p requeues 0 tbf segments the GSO SKBs (tbf_segment) and updates the netem's 'qlen'. The interface fully stops transferring packets and "locks". In this case, the child qdisc and tfifo are empty, but 'qlen' indicates the tfifo is at its limit and no more packets are accepted. This patch adds a counter for the entries in the tfifo. Netem's 'qlen' is only decreased when a packet is returned by its dequeue function, and not during enqueuing into the child qdisc. External updates to 'qlen' are thus accounted for and only the behavior of the backlog statistics changes. As in other qdiscs, 'qlen' then keeps track of how many packets are held in netem and all of its children. As before, sch->limit remains as the maximum number of packets in the tfifo. The same applies to netem's backlog statistics.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

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.

 [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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 3.3 To (excluding) 5.4.288

Linux>>Linux_kernel >> Version From (including) 5.5 To (excluding) 5.10.232

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.175

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.121

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.67

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.6

Linux>>Linux_kernel >> Version 6.13

Linux>>Linux_kernel >> Version 6.13

References