CVE-2025-37739 : Detail

CVE-2025-37739

7.1
/
High
Overflow
0.02%V4
Local
2025-05-01
12h55 +00:00
2025-11-03
19h54 +00:00
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CVE Descriptions

f2fs: fix to avoid out-of-bounds access in f2fs_truncate_inode_blocks()

In the Linux kernel, the following vulnerability has been resolved: f2fs: fix to avoid out-of-bounds access in f2fs_truncate_inode_blocks() syzbot reports an UBSAN issue as below: ------------[ cut here ]------------ UBSAN: array-index-out-of-bounds in fs/f2fs/node.h:381:10 index 18446744073709550692 is out of range for type '__le32[5]' (aka 'unsigned int[5]') CPU: 0 UID: 0 PID: 5318 Comm: syz.0.0 Not tainted 6.14.0-rc3-syzkaller-00060-g6537cfb395f3 #0 Call Trace: __dump_stack lib/dump_stack.c:94 [inline] dump_stack_lvl+0x241/0x360 lib/dump_stack.c:120 ubsan_epilogue lib/ubsan.c:231 [inline] __ubsan_handle_out_of_bounds+0x121/0x150 lib/ubsan.c:429 get_nid fs/f2fs/node.h:381 [inline] f2fs_truncate_inode_blocks+0xa5e/0xf60 fs/f2fs/node.c:1181 f2fs_do_truncate_blocks+0x782/0x1030 fs/f2fs/file.c:808 f2fs_truncate_blocks+0x10d/0x300 fs/f2fs/file.c:836 f2fs_truncate+0x417/0x720 fs/f2fs/file.c:886 f2fs_file_write_iter+0x1bdb/0x2550 fs/f2fs/file.c:5093 aio_write+0x56b/0x7c0 fs/aio.c:1633 io_submit_one+0x8a7/0x18a0 fs/aio.c:2052 __do_sys_io_submit fs/aio.c:2111 [inline] __se_sys_io_submit+0x171/0x2e0 fs/aio.c:2081 do_syscall_x64 arch/x86/entry/common.c:52 [inline] do_syscall_64+0xf3/0x230 arch/x86/entry/common.c:83 entry_SYSCALL_64_after_hwframe+0x77/0x7f RIP: 0033:0x7f238798cde9 index 18446744073709550692 (decimal, unsigned long long) = 0xfffffffffffffc64 (hexadecimal, unsigned long long) = -924 (decimal, long long) In f2fs_truncate_inode_blocks(), UBSAN detects that get_nid() tries to access .i_nid[-924], it means both offset[0] and level should zero. The possible case should be in f2fs_do_truncate_blocks(), we try to truncate inode size to zero, however, dn.ofs_in_node is zero and dn.node_page is not an inode page, so it fails to truncate inode page, and then pass zeroed free_from to f2fs_truncate_inode_blocks(), result in this issue. if (dn.ofs_in_node || IS_INODE(dn.node_page)) { f2fs_truncate_data_blocks_range(&dn, count); free_from += count; } I guess the reason why dn.node_page is not an inode page could be: there are multiple nat entries share the same node block address, once the node block address was reused, f2fs_get_node_page() may load a non-inode block. Let's add a sanity check for such condition to avoid out-of-bounds access issue.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-125 Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.1 HIGH CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/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.

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.

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) 3.8 To (excluding) 5.10.237

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.181

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.135

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.88

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.24

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.13.12

Linux>>Linux_kernel >> Version From (including) 6.14 To (excluding) 6.14.3

Configuraton 0

Debian>>Debian_linux >> Version 11.0

References