CVE-2023-26489 : Détail

CVE-2023-26489

10
/
Critique
Overflow
1.17%V4
Network
2023-03-08
19h59 +00:00
2025-02-25
14h59 +00:00
CVE.org
NVD
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Descriptions du CVE

Guest-controlled out-of-bounds read/write on x86_64 in wasmtime

wasmtime is a fast and secure runtime for WebAssembly. In affected versions wasmtime's code generator, Cranelift, has a bug on x86_64 targets where address-mode computation mistakenly would calculate a 35-bit effective address instead of WebAssembly's defined 33-bit effective address. This bug means that, with default codegen settings, a wasm-controlled load/store operation could read/write addresses up to 35 bits away from the base of linear memory. Due to this bug, however, addresses up to `0xffffffff * 8 + 0x7ffffffc = 36507222004 = ~34G` bytes away from the base of linear memory are possible from guest code. This means that the virtual memory 6G away from the base of linear memory up to ~34G away can be read/written by a malicious module. A guest module can, without the knowledge of the embedder, read/write memory in this region. The memory may belong to other WebAssembly instances when using the pooling allocator, for example. Affected embedders are recommended to analyze preexisting wasm modules to see if they're affected by the incorrect codegen rules and possibly correlate that with an anomalous number of traps during historical execution to locate possibly suspicious modules. The specific bug in Cranelift's x86_64 backend is that a WebAssembly address which is left-shifted by a constant amount from 1 to 3 will get folded into x86_64's addressing modes which perform shifts. For example `(i32.load (i32.shl (local.get 0) (i32.const 3)))` loads from the WebAssembly address `$local0 << 3`. When translated to Cranelift the `$local0 << 3` computation, a 32-bit value, is zero-extended to a 64-bit value and then added to the base address of linear memory. Cranelift would generate an instruction of the form `movl (%base, %local0, 8), %dst` which calculates `%base + %local0 << 3`. The bug here, however, is that the address computation happens with 64-bit values, where the `$local0 << 3` computation was supposed to be truncated to a a 32-bit value. This means that `%local0`, which can use up to 32-bits for an address, gets 3 extra bits of address space to be accessible via this `movl` instruction. The fix in Cranelift is to remove the erroneous lowering rules in the backend which handle these zero-extended expression. The above example is then translated to `movl %local0, %temp; shl $3, %temp; movl (%base, %temp), %dst` which correctly truncates the intermediate computation of `%local0 << 3` to 32-bits inside the `%temp` register which is then added to the `%base` value. Wasmtime version 4.0.1, 5.0.1, and 6.0.1 have been released and have all been patched to no longer contain the erroneous lowering rules. While updating Wasmtime is recommended, there are a number of possible workarounds that embedders can employ to mitigate this issue if updating is not possible. Note that none of these workarounds are on-by-default and require explicit configuration: 1. The `Config::static_memory_maximum_size(0)` option can be used to force all accesses to linear memory to be explicitly bounds-checked. This will perform a bounds check separately from the address-mode computation which correctly calculates the effective address of a load/store. Note that this can have a large impact on the execution performance of WebAssembly modules. 2. The `Config::static_memory_guard_size(1 << 36)` option can be used to greatly increase the guard pages placed after linear memory. This will guarantee that memory accesses up-to-34G away are guaranteed to be semantically correct by reserving unmapped memory for the instance. Note that this reserves a very large amount of virtual memory per-instances and can greatly reduce the maximum number of concurrent instances being run. 3. If using a non-x86_64 host is possible, then that will also work around this bug. This bug does not affect Wasmtime's or Cranelift's AArch64 backend, for example.

Informations du CVE

Faiblesses connexes

CWE-ID Nom de la faiblesse Source
CWE-125 Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.
CWE-787 Out-of-bounds Write
The product writes data past the end, or before the beginning, of the intended buffer.

Métriques

Métriques Score Gravité CVSS Vecteur Source
V3.1 10 CRITICAL CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

Changed

An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.

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.

EPSS

EPSS est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.

Score EPSS

Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.

Percentile EPSS

Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.
EPSS First.org

Products Mentioned

Configuraton 0

Bytecodealliance>>Cranelift-codegen >> Version From (including) 0.84.0 To (excluding) 0.91.1

Bytecodealliance>>Cranelift-codegen >> Version 0.92.0

Bytecodealliance>>Cranelift-codegen >> Version 0.93.0

Bytecodealliance>>Wasmtime >> Version From (including) 0.37.0 To (excluding) 4.0.1

Bytecodealliance>>Wasmtime >> Version 5.0.0

Bytecodealliance>>Wasmtime >> Version 6.0.0

Références

Les informations affichées sur CVE Find proviennent de plusieurs sources de référence rigoureusement sélectionnées. Les données CVE sont fournies par MITRE Corporation et la National Vulnerability Database (NVD). Le catalogue des vulnérabilités activement exploitées (KEV) provient de la Cybersecurity and Infrastructure Security Agency (CISA), tandis que les scores EPSS sont issus de FIRST.org. Enfin, les données relatives aux faiblesses logicielles (CWE) et aux schémas d'attaque courants (CAPEC) sont maintenues par MITRE Corporation, et les informations sur les configurations logicielles et matérielles (CPE) proviennent du NVD.