CVE-2023-52599 Detail

CVE-2023-52599

Score / Severity

7.8

High

EPSS

0.04%V3

Vector

Local

Published

2024-03-06
06h45 +00:00

Modified

2024-12-19
08h22 +00:00

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CVE.org

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CVE Descriptions

jfs: fix array-index-out-of-bounds in diNewExt

In the Linux kernel, the following vulnerability has been resolved: jfs: fix array-index-out-of-bounds in diNewExt [Syz report] UBSAN: array-index-out-of-bounds in fs/jfs/jfs_imap.c:2360:2 index -878706688 is out of range for type 'struct iagctl[128]' CPU: 1 PID: 5065 Comm: syz-executor282 Not tainted 6.7.0-rc4-syzkaller-00009-gbee0e7762ad2 #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 11/10/2023 Call Trace: __dump_stack lib/dump_stack.c:88 [inline] dump_stack_lvl+0x1e7/0x2d0 lib/dump_stack.c:106 ubsan_epilogue lib/ubsan.c:217 [inline] __ubsan_handle_out_of_bounds+0x11c/0x150 lib/ubsan.c:348 diNewExt+0x3cf3/0x4000 fs/jfs/jfs_imap.c:2360 diAllocExt fs/jfs/jfs_imap.c:1949 [inline] diAllocAG+0xbe8/0x1e50 fs/jfs/jfs_imap.c:1666 diAlloc+0x1d3/0x1760 fs/jfs/jfs_imap.c:1587 ialloc+0x8f/0x900 fs/jfs/jfs_inode.c:56 jfs_mkdir+0x1c5/0xb90 fs/jfs/namei.c:225 vfs_mkdir+0x2f1/0x4b0 fs/namei.c:4106 do_mkdirat+0x264/0x3a0 fs/namei.c:4129 __do_sys_mkdir fs/namei.c:4149 [inline] __se_sys_mkdir fs/namei.c:4147 [inline] __x64_sys_mkdir+0x6e/0x80 fs/namei.c:4147 do_syscall_x64 arch/x86/entry/common.c:51 [inline] do_syscall_64+0x45/0x110 arch/x86/entry/common.c:82 entry_SYSCALL_64_after_hwframe+0x63/0x6b RIP: 0033:0x7fcb7e6a0b57 Code: ff ff 77 07 31 c0 c3 0f 1f 40 00 48 c7 c2 b8 ff ff ff f7 d8 64 89 02 b8 ff ff ff ff c3 66 0f 1f 44 00 00 b8 53 00 00 00 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 c7 c1 b8 ff ff ff f7 d8 64 89 01 48 RSP: 002b:00007ffd83023038 EFLAGS: 00000286 ORIG_RAX: 0000000000000053 RAX: ffffffffffffffda RBX: 00000000ffffffff RCX: 00007fcb7e6a0b57 RDX: 00000000000a1020 RSI: 00000000000001ff RDI: 0000000020000140 RBP: 0000000020000140 R08: 0000000000000000 R09: 0000000000000000 R10: 0000000000000000 R11: 0000000000000286 R12: 00007ffd830230d0 R13: 0000000000000000 R14: 0000000000000000 R15: 0000000000000000 [Analysis] When the agstart is too large, it can cause agno overflow. [Fix] After obtaining agno, if the value is invalid, exit the subsequent process. Modified the test from agno > MAXAG to agno >= MAXAG based on linux-next report by kernel test robot (Dan Carpenter).

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-129	Improper Validation of Array Index The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	7.8	HIGH	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H More informations 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. 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.	[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.

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