CVE-2021-47580 : Detail

CVE-2021-47580

6.6
/
Medium
Overflow
0.05%V4
Local
2024-06-19
14h53 +00:00
2024-12-19
07h45 +00:00
CVE.org
NVD
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CVE Descriptions

scsi: scsi_debug: Fix type in min_t to avoid stack OOB

In the Linux kernel, the following vulnerability has been resolved: scsi: scsi_debug: Fix type in min_t to avoid stack OOB Change min_t() to use type "u32" instead of type "int" to avoid stack out of bounds. With min_t() type "int" the values get sign extended and the larger value gets used causing stack out of bounds. BUG: KASAN: stack-out-of-bounds in memcpy include/linux/fortify-string.h:191 [inline] BUG: KASAN: stack-out-of-bounds in sg_copy_buffer+0x1de/0x240 lib/scatterlist.c:976 Read of size 127 at addr ffff888072607128 by task syz-executor.7/18707 CPU: 1 PID: 18707 Comm: syz-executor.7 Not tainted 5.15.0-syzk #1 Hardware name: Red Hat KVM, BIOS 1.13.0-2 Call Trace: __dump_stack lib/dump_stack.c:88 [inline] dump_stack_lvl+0x89/0xb5 lib/dump_stack.c:106 print_address_description.constprop.9+0x28/0x160 mm/kasan/report.c:256 __kasan_report mm/kasan/report.c:442 [inline] kasan_report.cold.14+0x7d/0x117 mm/kasan/report.c:459 check_region_inline mm/kasan/generic.c:183 [inline] kasan_check_range+0x1a3/0x210 mm/kasan/generic.c:189 memcpy+0x23/0x60 mm/kasan/shadow.c:65 memcpy include/linux/fortify-string.h:191 [inline] sg_copy_buffer+0x1de/0x240 lib/scatterlist.c:976 sg_copy_from_buffer+0x33/0x40 lib/scatterlist.c:1000 fill_from_dev_buffer.part.34+0x82/0x130 drivers/scsi/scsi_debug.c:1162 fill_from_dev_buffer drivers/scsi/scsi_debug.c:1888 [inline] resp_readcap16+0x365/0x3b0 drivers/scsi/scsi_debug.c:1887 schedule_resp+0x4d8/0x1a70 drivers/scsi/scsi_debug.c:5478 scsi_debug_queuecommand+0x8c9/0x1ec0 drivers/scsi/scsi_debug.c:7533 scsi_dispatch_cmd drivers/scsi/scsi_lib.c:1520 [inline] scsi_queue_rq+0x16b0/0x2d40 drivers/scsi/scsi_lib.c:1699 blk_mq_dispatch_rq_list+0xb9b/0x2700 block/blk-mq.c:1639 __blk_mq_sched_dispatch_requests+0x28f/0x590 block/blk-mq-sched.c:325 blk_mq_sched_dispatch_requests+0x105/0x190 block/blk-mq-sched.c:358 __blk_mq_run_hw_queue+0xe5/0x150 block/blk-mq.c:1761 __blk_mq_delay_run_hw_queue+0x4f8/0x5c0 block/blk-mq.c:1838 blk_mq_run_hw_queue+0x18d/0x350 block/blk-mq.c:1891 blk_mq_sched_insert_request+0x3db/0x4e0 block/blk-mq-sched.c:474 blk_execute_rq_nowait+0x16b/0x1c0 block/blk-exec.c:62 sg_common_write.isra.18+0xeb3/0x2000 drivers/scsi/sg.c:836 sg_new_write.isra.19+0x570/0x8c0 drivers/scsi/sg.c:774 sg_ioctl_common+0x14d6/0x2710 drivers/scsi/sg.c:939 sg_ioctl+0xa2/0x180 drivers/scsi/sg.c:1165 vfs_ioctl fs/ioctl.c:51 [inline] __do_sys_ioctl fs/ioctl.c:874 [inline] __se_sys_ioctl fs/ioctl.c:860 [inline] __x64_sys_ioctl+0x19d/0x220 fs/ioctl.c:860 do_syscall_x64 arch/x86/entry/common.c:50 [inline] do_syscall_64+0x3a/0x80 arch/x86/entry/common.c:80 entry_SYSCALL_64_after_hwframe+0x44/0xae

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 6.6 MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:L

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.

Low

Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

Low

Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

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.

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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 To (excluding) 5.10.88

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.11

Linux>>Linux_kernel >> Version 5.16

Linux>>Linux_kernel >> Version 5.16

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.