CVE-2025-38472 : Detail

CVE-2025-38472

9.8
/
Critical
0.08%V4
Network
2025-07-28
11h21 +00:00
2026-07-30
05h54 +00:00
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CVE Descriptions

netfilter: nf_conntrack: fix crash due to removal of uninitialised entry

In the Linux kernel, the following vulnerability has been resolved: netfilter: nf_conntrack: fix crash due to removal of uninitialised entry A crash in conntrack was reported while trying to unlink the conntrack entry from the hash bucket list: [exception RIP: __nf_ct_delete_from_lists+172] [..] #7 [ff539b5a2b043aa0] nf_ct_delete at ffffffffc124d421 [nf_conntrack] #8 [ff539b5a2b043ad0] nf_ct_gc_expired at ffffffffc124d999 [nf_conntrack] #9 [ff539b5a2b043ae0] __nf_conntrack_find_get at ffffffffc124efbc [nf_conntrack] [..] The nf_conn struct is marked as allocated from slab but appears to be in a partially initialised state: ct hlist pointer is garbage; looks like the ct hash value (hence crash). ct->status is equal to IPS_CONFIRMED|IPS_DYING, which is expected ct->timeout is 30000 (=30s), which is unexpected. Everything else looks like normal udp conntrack entry. If we ignore ct->status and pretend its 0, the entry matches those that are newly allocated but not yet inserted into the hash: - ct hlist pointers are overloaded and store/cache the raw tuple hash - ct->timeout matches the relative time expected for a new udp flow rather than the absolute 'jiffies' value. If it were not for the presence of IPS_CONFIRMED, __nf_conntrack_find_get() would have skipped the entry. Theory is that we did hit following race: cpu x cpu y cpu z found entry E found entry E E is expired nf_ct_delete() return E to rcu slab init_conntrack E is re-inited, ct->status set to 0 reply tuplehash hnnode.pprev stores hash value. cpu y found E right before it was deleted on cpu x. E is now re-inited on cpu z. cpu y was preempted before checking for expiry and/or confirm bit. ->refcnt set to 1 E now owned by skb ->timeout set to 30000 If cpu y were to resume now, it would observe E as expired but would skip E due to missing CONFIRMED bit. nf_conntrack_confirm gets called sets: ct->status |= CONFIRMED This is wrong: E is not yet added to hashtable. cpu y resumes, it observes E as expired but CONFIRMED: nf_ct_expired() -> yes (ct->timeout is 30s) confirmed bit set. cpu y will try to delete E from the hashtable: nf_ct_delete() -> set DYING bit __nf_ct_delete_from_lists Even this scenario doesn't guarantee a crash: cpu z still holds the table bucket lock(s) so y blocks: wait for spinlock held by z CONFIRMED is set but there is no guarantee ct will be added to hash: "chaintoolong" or "clash resolution" logic both skip the insert step. reply hnnode.pprev still stores the hash value. unlocks spinlock return NF_DROP In case CPU z does insert the entry into the hashtable, cpu y will unlink E again right away but no crash occurs. Without 'cpu y' race, 'garbage' hlist is of no consequence: ct refcnt remains at 1, eventually skb will be free'd and E gets destroyed via: nf_conntrack_put -> nf_conntrack_destroy -> nf_ct_destroy. To resolve this, move the IPS_CONFIRMED assignment after the table insertion but before the unlock. Pablo points out that the confirm-bit-store could be reordered to happen before hlist add resp. the timeout fixup, so switch to set_bit and before_atomic memory barrier to prevent this. It doesn't matter if other CPUs can observe a newly inserted entry right before the CONFIRMED bit was set: Such event cannot be distinguished from above "E is the old incarnation" case: the entry will be skipped. Also change nf_ct_should_gc() to first check the confirmed bit. The gc sequence is: 1. Check if entry has expired, if not skip to next entry 2. Obtain a reference to the expired entry. 3. Call nf_ct_should_gc() to double-check step 1. nf_ct_should_gc() is thus called only for entries that already failed an expiry check. After this patch, once the confirmed bit check pas ---truncated---

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-908 Use of Uninitialized Resource
The product uses or accesses a resource that has not been initialized.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 9.8 CRITICAL CVSS:3.1/AV:N/AC:L/PR:N/UI:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

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.

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.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.18.13 To (excluding) 6.1.147

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.100

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.40

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.15.8

Linux>>Linux_kernel >> Version 6.16

Linux>>Linux_kernel >> Version 6.16

Linux>>Linux_kernel >> Version 6.16

Linux>>Linux_kernel >> Version 6.16

Linux>>Linux_kernel >> Version 6.16

Linux>>Linux_kernel >> Version 6.16

Configuraton 0

Debian>>Debian_linux >> Version 11.0

References