CVE-2024-47719 : Detail

CVE-2024-47719

7.8
/
High
Overflow
0.03%V4
Local
2024-10-21
11h53 +00:00
2024-12-19
09h26 +00:00
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CVE Descriptions

iommufd: Protect against overflow of ALIGN() during iova allocation

In the Linux kernel, the following vulnerability has been resolved: iommufd: Protect against overflow of ALIGN() during iova allocation Userspace can supply an iova and uptr such that the target iova alignment becomes really big and ALIGN() overflows which corrupts the selected area range during allocation. CONFIG_IOMMUFD_TEST can detect this: WARNING: CPU: 1 PID: 5092 at drivers/iommu/iommufd/io_pagetable.c:268 iopt_alloc_area_pages drivers/iommu/iommufd/io_pagetable.c:268 [inline] WARNING: CPU: 1 PID: 5092 at drivers/iommu/iommufd/io_pagetable.c:268 iopt_map_pages+0xf95/0x1050 drivers/iommu/iommufd/io_pagetable.c:352 Modules linked in: CPU: 1 PID: 5092 Comm: syz-executor294 Not tainted 6.10.0-rc5-syzkaller-00294-g3ffea9a7a6f7 #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 06/07/2024 RIP: 0010:iopt_alloc_area_pages drivers/iommu/iommufd/io_pagetable.c:268 [inline] RIP: 0010:iopt_map_pages+0xf95/0x1050 drivers/iommu/iommufd/io_pagetable.c:352 Code: fc e9 a4 f3 ff ff e8 1a 8b 4c fc 41 be e4 ff ff ff e9 8a f3 ff ff e8 0a 8b 4c fc 90 0f 0b 90 e9 37 f5 ff ff e8 fc 8a 4c fc 90 <0f> 0b 90 e9 68 f3 ff ff 48 c7 c1 ec 82 ad 8f 80 e1 07 80 c1 03 38 RSP: 0018:ffffc90003ebf9e0 EFLAGS: 00010293 RAX: ffffffff85499fa4 RBX: 00000000ffffffef RCX: ffff888079b49e00 RDX: 0000000000000000 RSI: 00000000ffffffef RDI: 0000000000000000 RBP: ffffc90003ebfc50 R08: ffffffff85499b30 R09: ffffffff85499942 R10: 0000000000000002 R11: ffff888079b49e00 R12: ffff8880228e0010 R13: 0000000000000000 R14: 1ffff920007d7f68 R15: ffffc90003ebfd00 FS: 000055557d760380(0000) GS:ffff8880b9500000(0000) knlGS:0000000000000000 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00000000005fdeb8 CR3: 000000007404a000 CR4: 00000000003506f0 DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 Call Trace: iommufd_ioas_copy+0x610/0x7b0 drivers/iommu/iommufd/ioas.c:274 iommufd_fops_ioctl+0x4d9/0x5a0 drivers/iommu/iommufd/main.c:421 vfs_ioctl fs/ioctl.c:51 [inline] __do_sys_ioctl fs/ioctl.c:907 [inline] __se_sys_ioctl+0xfc/0x170 fs/ioctl.c:893 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 Cap the automatic alignment to the huge page size, which is probably a better idea overall. Huge automatic alignments can fragment and chew up the available IOVA space without any reason.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-787 Out-of-bounds Write
The product writes data past the end, or before the beginning, of the intended buffer.

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

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.

 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) 6.2 To (excluding) 6.6.54

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.10.13

Linux>>Linux_kernel >> Version From (including) 6.11 To (excluding) 6.11.2

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.