CVE-2025-71087 : Detail

CVE-2025-71087

5.5
/
Medium
0.02%V4
Local
2026-01-13
15h34 +00:00
2026-02-09
08h34 +00:00
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CVE Descriptions

iavf: fix off-by-one issues in iavf_config_rss_reg()

In the Linux kernel, the following vulnerability has been resolved: iavf: fix off-by-one issues in iavf_config_rss_reg() There are off-by-one bugs when configuring RSS hash key and lookup table, causing out-of-bounds reads to memory [1] and out-of-bounds writes to device registers. Before commit 43a3d9ba34c9 ("i40evf: Allow PF driver to configure RSS"), the loop upper bounds were: i <= I40E_VFQF_{HKEY,HLUT}_MAX_INDEX which is safe since the value is the last valid index. That commit changed the bounds to: i <= adapter->rss_{key,lut}_size / 4 where `rss_{key,lut}_size / 4` is the number of dwords, so the last valid index is `(rss_{key,lut}_size / 4) - 1`. Therefore, using `<=` accesses one element past the end. Fix the issues by using `<` instead of `<=`, ensuring we do not exceed the bounds. [1] KASAN splat about rss_key_size off-by-one BUG: KASAN: slab-out-of-bounds in iavf_config_rss+0x619/0x800 Read of size 4 at addr ffff888102c50134 by task kworker/u8:6/63 CPU: 0 UID: 0 PID: 63 Comm: kworker/u8:6 Not tainted 6.18.0-rc2-enjuk-tnguy-00378-g3005f5b77652-dirty #156 PREEMPT(voluntary) Hardware name: QEMU Standard PC (Q35 + ICH9, 2009), BIOS 1.16.3-debian-1.16.3-2 04/01/2014 Workqueue: iavf iavf_watchdog_task Call Trace: dump_stack_lvl+0x6f/0xb0 print_report+0x170/0x4f3 kasan_report+0xe1/0x1a0 iavf_config_rss+0x619/0x800 iavf_watchdog_task+0x2be7/0x3230 process_one_work+0x7fd/0x1420 worker_thread+0x4d1/0xd40 kthread+0x344/0x660 ret_from_fork+0x249/0x320 ret_from_fork_asm+0x1a/0x30 Allocated by task 63: kasan_save_stack+0x30/0x50 kasan_save_track+0x14/0x30 __kasan_kmalloc+0x7f/0x90 __kmalloc_noprof+0x246/0x6f0 iavf_watchdog_task+0x28fc/0x3230 process_one_work+0x7fd/0x1420 worker_thread+0x4d1/0xd40 kthread+0x344/0x660 ret_from_fork+0x249/0x320 ret_from_fork_asm+0x1a/0x30 The buggy address belongs to the object at ffff888102c50100 which belongs to the cache kmalloc-64 of size 64 The buggy address is located 0 bytes to the right of allocated 52-byte region [ffff888102c50100, ffff888102c50134) The buggy address belongs to the physical page: page: refcount:0 mapcount:0 mapping:0000000000000000 index:0x0 pfn:0x102c50 flags: 0x200000000000000(node=0|zone=2) page_type: f5(slab) raw: 0200000000000000 ffff8881000418c0 dead000000000122 0000000000000000 raw: 0000000000000000 0000000080200020 00000000f5000000 0000000000000000 page dumped because: kasan: bad access detected Memory state around the buggy address: ffff888102c50000: 00 00 00 00 00 00 00 fc fc fc fc fc fc fc fc fc ffff888102c50080: 00 00 00 00 00 00 00 fc fc fc fc fc fc fc fc fc >ffff888102c50100: 00 00 00 00 00 00 04 fc fc fc fc fc fc fc fc fc ^ ffff888102c50180: 00 00 00 00 00 00 00 00 fc fc fc fc fc fc fc fc ffff888102c50200: fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-193 Off-by-one Error
A product calculates or uses an incorrect maximum or minimum value that is 1 more, or 1 less, than the correct value.

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.

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) 4.7.1 To (excluding) 5.10.248

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.198

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.160

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.120

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.64

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.4

Linux>>Linux_kernel >> Version 4.7

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

References