CVE-2024-53123 : Detail

CVE-2024-53123

5.5
/
Medium
0.02%V4
Local
2024-12-02
13h44 +00:00
2024-12-19
09h39 +00:00
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CVE Descriptions

mptcp: error out earlier on disconnect

In the Linux kernel, the following vulnerability has been resolved: mptcp: error out earlier on disconnect Eric reported a division by zero splat in the MPTCP protocol: Oops: divide error: 0000 [#1] PREEMPT SMP KASAN PTI CPU: 1 UID: 0 PID: 6094 Comm: syz-executor317 Not tainted 6.12.0-rc5-syzkaller-00291-g05b92660cdfe #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 09/13/2024 RIP: 0010:__tcp_select_window+0x5b4/0x1310 net/ipv4/tcp_output.c:3163 Code: f6 44 01 e3 89 df e8 9b 75 09 f8 44 39 f3 0f 8d 11 ff ff ff e8 0d 74 09 f8 45 89 f4 e9 04 ff ff ff e8 00 74 09 f8 44 89 f0 99 7c 24 14 41 29 d6 45 89 f4 e9 ec fe ff ff e8 e8 73 09 f8 48 89 RSP: 0018:ffffc900041f7930 EFLAGS: 00010293 RAX: 0000000000017e67 RBX: 0000000000017e67 RCX: ffffffff8983314b RDX: 0000000000000000 RSI: ffffffff898331b0 RDI: 0000000000000004 RBP: 00000000005d6000 R08: 0000000000000004 R09: 0000000000017e67 R10: 0000000000003e80 R11: 0000000000000000 R12: 0000000000003e80 R13: ffff888031d9b440 R14: 0000000000017e67 R15: 00000000002eb000 FS: 00007feb5d7f16c0(0000) GS:ffff8880b8700000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00007feb5d8adbb8 CR3: 0000000074e4c000 CR4: 00000000003526f0 DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 Call Trace: __tcp_cleanup_rbuf+0x3e7/0x4b0 net/ipv4/tcp.c:1493 mptcp_rcv_space_adjust net/mptcp/protocol.c:2085 [inline] mptcp_recvmsg+0x2156/0x2600 net/mptcp/protocol.c:2289 inet_recvmsg+0x469/0x6a0 net/ipv4/af_inet.c:885 sock_recvmsg_nosec net/socket.c:1051 [inline] sock_recvmsg+0x1b2/0x250 net/socket.c:1073 __sys_recvfrom+0x1a5/0x2e0 net/socket.c:2265 __do_sys_recvfrom net/socket.c:2283 [inline] __se_sys_recvfrom net/socket.c:2279 [inline] __x64_sys_recvfrom+0xe0/0x1c0 net/socket.c:2279 do_syscall_x64 arch/x86/entry/common.c:52 [inline] do_syscall_64+0xcd/0x250 arch/x86/entry/common.c:83 entry_SYSCALL_64_after_hwframe+0x77/0x7f RIP: 0033:0x7feb5d857559 Code: 28 00 00 00 75 05 48 83 c4 28 c3 e8 51 18 00 00 90 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 c7 c1 b0 ff ff ff f7 d8 64 89 01 48 RSP: 002b:00007feb5d7f1208 EFLAGS: 00000246 ORIG_RAX: 000000000000002d RAX: ffffffffffffffda RBX: 00007feb5d8e1318 RCX: 00007feb5d857559 RDX: 000000800000000e RSI: 0000000000000000 RDI: 0000000000000003 RBP: 00007feb5d8e1310 R08: 0000000000000000 R09: ffffffff81000000 R10: 0000000000000100 R11: 0000000000000246 R12: 00007feb5d8e131c R13: 00007feb5d8ae074 R14: 000000800000000e R15: 00000000fffffdef and provided a nice reproducer. The root cause is the current bad handling of racing disconnect. After the blamed commit below, sk_wait_data() can return (with error) with the underlying socket disconnected and a zero rcv_mss. Catch the error and return without performing any additional operations on the current socket.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-362 Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
The product contains a concurrent code sequence that requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence operating concurrently.

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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 6.1.60 To (excluding) 6.1.119

Linux>>Linux_kernel >> Version From (including) 6.5.9 To (excluding) 6.6

Linux>>Linux_kernel >> Version From (including) 6.6 To (excluding) 6.6.63

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.11.10

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

Linux>>Linux_kernel >> Version 6.12

References

The information presented on CVE Find originates from several carefully selected reference sources. CVE data is provided by MITRE Corporation and the National Vulnerability Database (NVD). The Known Exploited Vulnerabilities (KEV) catalog is sourced from the Cybersecurity and Infrastructure Security Agency (CISA), while EPSS scores come from FIRST.org. Additionally, data regarding software weaknesses (CWE) and common attack patterns (CAPEC) is maintained by MITRE Corporation, and information on hardware and software configurations (CPE) is provided by the NVD.