CVE-2024-50194 Detail

CVE-2024-50194

Score / Severity

5.5

Medium

EPSS

0.04%V3

Vector

Local

Published

2024-11-08
05h54 +00:00

Modified

2024-12-19
09h35 +00:00

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CVE.org

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CVE Descriptions

arm64: probes: Fix uprobes for big-endian kernels

In the Linux kernel, the following vulnerability has been resolved: arm64: probes: Fix uprobes for big-endian kernels The arm64 uprobes code is broken for big-endian kernels as it doesn't convert the in-memory instruction encoding (which is always little-endian) into the kernel's native endianness before analyzing and simulating instructions. This may result in a few distinct problems: * The kernel may may erroneously reject probing an instruction which can safely be probed. * The kernel may erroneously erroneously permit stepping an instruction out-of-line when that instruction cannot be stepped out-of-line safely. * The kernel may erroneously simulate instruction incorrectly dur to interpretting the byte-swapped encoding. The endianness mismatch isn't caught by the compiler or sparse because: * The arch_uprobe::{insn,ixol} fields are encoded as arrays of u8, so the compiler and sparse have no idea these contain a little-endian 32-bit value. The core uprobes code populates these with a memcpy() which similarly does not handle endianness. * While the uprobe_opcode_t type is an alias for __le32, both arch_uprobe_analyze_insn() and arch_uprobe_skip_sstep() cast from u8[] to the similarly-named probe_opcode_t, which is an alias for u32. Hence there is no endianness conversion warning. Fix this by changing the arch_uprobe::{insn,ixol} fields to __le32 and adding the appropriate __le32_to_cpu() conversions prior to consuming the instruction encoding. The core uprobes copies these fields as opaque ranges of bytes, and so is unaffected by this change. At the same time, remove MAX_UINSN_BYTES and consistently use AARCH64_INSN_SIZE for clarity. Tested with the following: | #include | #include | | #define noinline __attribute__((noinline)) | | static noinline void *adrp_self(void) | { | void *addr; | | asm volatile( | " adrp %x0, adrp_self\n" | " add %x0, %x0, :lo12:adrp_self\n" | : "=r" (addr)); | } | | | int main(int argc, char *argv) | { | void *ptr = adrp_self(); | bool equal = (ptr == adrp_self); | | printf("adrp_self => %p\n" | "adrp_self() => %p\n" | "%s\n", | adrp_self, ptr, equal ? "EQUAL" : "NOT EQUAL"); | | return 0; | } .... where the adrp_self() function was compiled to: | 00000000004007e0 : | 4007e0: 90000000 adrp x0, 400000 <__ehdr_start> | 4007e4: 911f8000 add x0, x0, #0x7e0 | 4007e8: d65f03c0 ret Before this patch, the ADRP is not recognized, and is assumed to be steppable, resulting in corruption of the result: | # ./adrp-self | adrp_self => 0x4007e0 | adrp_self() => 0x4007e0 | EQUAL | # echo 'p /root/adrp-self:0x007e0' > /sys/kernel/tracing/uprobe_events | # echo 1 > /sys/kernel/tracing/events/uprobes/enable | # ./adrp-self | adrp_self => 0x4007e0 | adrp_self() => 0xffffffffff7e0 | NOT EQUAL After this patch, the ADRP is correctly recognized and simulated: | # ./adrp-self | adrp_self => 0x4007e0 | adrp_self() => 0x4007e0 | EQUAL | # | # echo 'p /root/adrp-self:0x007e0' > /sys/kernel/tracing/uprobe_events | # echo 1 > /sys/kernel/tracing/events/uprobes/enable | # ./adrp-self | adrp_self => 0x4007e0 | adrp_self() => 0x4007e0 | EQUAL

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE Other	No informations.

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 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. 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.	[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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