CVE-2021-47034 : Detail

CVE-2021-47034

4.4
/
Medium
0.04%V3
Local
2024-02-28
08h13 +00:00
2024-12-19
07h34 +00:00
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CVE Descriptions

powerpc/64s: Fix pte update for kernel memory on radix

In the Linux kernel, the following vulnerability has been resolved: powerpc/64s: Fix pte update for kernel memory on radix When adding a PTE a ptesync is needed to order the update of the PTE with subsequent accesses otherwise a spurious fault may be raised. radix__set_pte_at() does not do this for performance gains. For non-kernel memory this is not an issue as any faults of this kind are corrected by the page fault handler. For kernel memory these faults are not handled. The current solution is that there is a ptesync in flush_cache_vmap() which should be called when mapping from the vmalloc region. However, map_kernel_page() does not call flush_cache_vmap(). This is troublesome in particular for code patching with Strict RWX on radix. In do_patch_instruction() the page frame that contains the instruction to be patched is mapped and then immediately patched. With no ordering or synchronization between setting up the PTE and writing to the page it is possible for faults. As the code patching is done using __put_user_asm_goto() the resulting fault is obscured - but using a normal store instead it can be seen: BUG: Unable to handle kernel data access on write at 0xc008000008f24a3c Faulting instruction address: 0xc00000000008bd74 Oops: Kernel access of bad area, sig: 11 [#1] LE PAGE_SIZE=64K MMU=Radix SMP NR_CPUS=2048 NUMA PowerNV Modules linked in: nop_module(PO+) [last unloaded: nop_module] CPU: 4 PID: 757 Comm: sh Tainted: P O 5.10.0-rc5-01361-ge3c1b78c8440-dirty #43 NIP: c00000000008bd74 LR: c00000000008bd50 CTR: c000000000025810 REGS: c000000016f634a0 TRAP: 0300 Tainted: P O (5.10.0-rc5-01361-ge3c1b78c8440-dirty) MSR: 9000000000009033 CR: 44002884 XER: 00000000 CFAR: c00000000007c68c DAR: c008000008f24a3c DSISR: 42000000 IRQMASK: 1 This results in the kind of issue reported here: https://lore.kernel.org/linuxppc-dev/15AC5B0E-A221-4B8C-9039-FA96B8EF7C88@lca.pw/ Chris Riedl suggested a reliable way to reproduce the issue: $ mount -t debugfs none /sys/kernel/debug $ (while true; do echo function > /sys/kernel/debug/tracing/current_tracer ; echo nop > /sys/kernel/debug/tracing/current_tracer ; done) & Turning ftrace on and off does a large amount of code patching which in usually less then 5min will crash giving a trace like: ftrace-powerpc: (____ptrval____): replaced (4b473b11) != old (60000000) ------------[ ftrace bug ]------------ ftrace failed to modify [] napi_busy_loop+0xc/0x390 actual: 11:3b:47:4b Setting ftrace call site to call ftrace function ftrace record flags: 80000001 (1) expected tramp: c00000000006c96c ------------[ cut here ]------------ WARNING: CPU: 4 PID: 809 at kernel/trace/ftrace.c:2065 ftrace_bug+0x28c/0x2e8 Modules linked in: nop_module(PO-) [last unloaded: nop_module] CPU: 4 PID: 809 Comm: sh Tainted: P O 5.10.0-rc5-01360-gf878ccaf250a #1 NIP: c00000000024f334 LR: c00000000024f330 CTR: c0000000001a5af0 REGS: c000000004c8b760 TRAP: 0700 Tainted: P O (5.10.0-rc5-01360-gf878ccaf250a) MSR: 900000000282b033 CR: 28008848 XER: 20040000 CFAR: c0000000001a9c98 IRQMASK: 0 GPR00: c00000000024f330 c000000004c8b9f0 c000000002770600 0000000000000022 GPR04: 00000000ffff7fff c000000004c8b6d0 0000000000000027 c0000007fe9bcdd8 GPR08: 0000000000000023 ffffffffffffffd8 0000000000000027 c000000002613118 GPR12: 0000000000008000 c0000007fffdca00 0000000000000000 0000000000000000 GPR16: 0000000023ec37c5 0000000000000000 0000000000000000 0000000000000008 GPR20: c000000004c8bc90 c0000000027a2d20 c000000004c8bcd0 c000000002612fe8 GPR24: 0000000000000038 0000000000000030 0000000000000028 0000000000000020 GPR28: c000000000ff1b68 c000000000bf8e5c c00000000312f700 c000000000fbb9b0 NIP ftrace_bug+0x28c/0x2e8 LR ftrace_bug+0x288/0x2e8 Call T ---truncated---

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 4.4 MEDIUM CVSS:3.1/AV:L/AC:L/PR:H/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.

High

The attacker requires privileges that provide significant (e.g., administrative) control over the vulnerable component allowing access to component-wide settings and files.

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.

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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 From (including) 4.18 To (excluding) 4.19.191

Linux>>Linux_kernel >> Version From (including) 4.20 To (excluding) 5.4.119

Linux>>Linux_kernel >> Version From (including) 5.5 To (excluding) 5.10.37

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.11.21

Linux>>Linux_kernel >> Version From (including) 5.12 To (excluding) 5.12.4

References