CVE-2024-40907 : Detail

CVE-2024-40907

5.5
/
Medium
Memory Corruption
0.04%V3
Local
2024-07-12
12h20 +00:00
2024-12-19
09h07 +00:00
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CVE Descriptions

ionic: fix kernel panic in XDP_TX action

In the Linux kernel, the following vulnerability has been resolved: ionic: fix kernel panic in XDP_TX action In the XDP_TX path, ionic driver sends a packet to the TX path with rx page and corresponding dma address. After tx is done, ionic_tx_clean() frees that page. But RX ring buffer isn't reset to NULL. So, it uses a freed page, which causes kernel panic. BUG: unable to handle page fault for address: ffff8881576c110c PGD 773801067 P4D 773801067 PUD 87f086067 PMD 87efca067 PTE 800ffffea893e060 Oops: Oops: 0000 [#1] PREEMPT SMP DEBUG_PAGEALLOC KASAN NOPTI CPU: 1 PID: 25 Comm: ksoftirqd/1 Not tainted 6.9.0+ #11 Hardware name: ASUS System Product Name/PRIME Z690-P D4, BIOS 0603 11/01/2021 RIP: 0010:bpf_prog_f0b8caeac1068a55_balancer_ingress+0x3b/0x44f Code: 00 53 41 55 41 56 41 57 b8 01 00 00 00 48 8b 5f 08 4c 8b 77 00 4c 89 f7 48 83 c7 0e 48 39 d8 RSP: 0018:ffff888104e6fa28 EFLAGS: 00010283 RAX: 0000000000000002 RBX: ffff8881576c1140 RCX: 0000000000000002 RDX: ffffffffc0051f64 RSI: ffffc90002d33048 RDI: ffff8881576c110e RBP: ffff888104e6fa88 R08: 0000000000000000 R09: ffffed1027a04a23 R10: 0000000000000000 R11: 0000000000000000 R12: ffff8881b03a21a8 R13: ffff8881589f800f R14: ffff8881576c1100 R15: 00000001576c1100 FS: 0000000000000000(0000) GS:ffff88881ae00000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: ffff8881576c110c CR3: 0000000767a90000 CR4: 00000000007506f0 PKRU: 55555554 Call Trace: ? __die+0x20/0x70 ? page_fault_oops+0x254/0x790 ? __pfx_page_fault_oops+0x10/0x10 ? __pfx_is_prefetch.constprop.0+0x10/0x10 ? search_bpf_extables+0x165/0x260 ? fixup_exception+0x4a/0x970 ? exc_page_fault+0xcb/0xe0 ? asm_exc_page_fault+0x22/0x30 ? 0xffffffffc0051f64 ? bpf_prog_f0b8caeac1068a55_balancer_ingress+0x3b/0x44f ? do_raw_spin_unlock+0x54/0x220 ionic_rx_service+0x11ab/0x3010 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ? ionic_tx_clean+0x29b/0xc60 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ? __pfx_ionic_tx_clean+0x10/0x10 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ? __pfx_ionic_rx_service+0x10/0x10 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ? ionic_tx_cq_service+0x25d/0xa00 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ? __pfx_ionic_rx_service+0x10/0x10 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ionic_cq_service+0x69/0x150 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] ionic_txrx_napi+0x11a/0x540 [ionic 9180c3001ab627d82bbc5f3ebe8a0decaf6bb864] __napi_poll.constprop.0+0xa0/0x440 net_rx_action+0x7e7/0xc30 ? __pfx_net_rx_action+0x10/0x10

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.

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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) 6.9 To (excluding) 6.9.6

Linux>>Linux_kernel >> Version 6.10

Linux>>Linux_kernel >> Version 6.10

References