CVE-2017-0313 : Detail

CVE-2017-0313

7.8
/
High
Overflow
0.07%V3
Local
2017-02-15
22h00 +00:00
2017-08-31
07h57 +00:00
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CVE Descriptions

All versions of NVIDIA Windows GPU Display Driver contain a vulnerability in the kernel mode layer (nvlddmkm.sys) implementation of the SubmitCommandVirtual DDI (DxgkDdiSubmitCommandVirtual) where untrusted input is used to reference memory outside of the intended boundary of the buffer leading to denial of service or escalation of privileges.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-119 Improper Restriction of Operations within the Bounds of a Memory Buffer
The product performs operations on a memory buffer, but it reads from or writes to a memory location outside the buffer's intended boundary. This may result in read or write operations on unexpected memory locations that could be linked to other variables, data structures, or internal program data.

Metrics

Metrics Score Severity CVSS Vector Source
V3.0 7.8 HIGH CVSS:3.0/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

A vulnerability exploitable with Local access means that the vulnerable component is not bound to the network stack, and the attacker's path is via read/write/execute capabilities. In some cases, the attacker may be logged in locally in order to exploit the vulnerability, otherwise, she may rely on User Interaction to execute a malicious file.

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 against the vulnerable component.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

Low

The attacker is authorized with (i.e. 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 may have the ability to cause an impact only to non-sensitive resources.

User Interaction

This metric captures the requirement for a 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

An important property captured by CVSS v3.0 is the ability for a vulnerability in one software component to impact resources beyond its means, or privileges.

Scope

Formally, Scope refers to the collection of privileges defined by a computing authority (e.g. an application, an operating system, or a sandbox environment) when granting access to computing resources (e.g. files, CPU, memory, etc). These privileges are assigned based on some method of identification and authorization. In some cases, the authorization may be simple or loosely controlled based upon predefined rules or standards. For example, in the case of Ethernet traffic sent to a network switch, the switch accepts traffic that arrives on its ports and is an authority that controls the traffic flow to other switch ports.

Unchanged

An exploited vulnerability can only affect resources managed by the same authority. In this case the vulnerable component and the impacted component are the same.

Base: Impact Metrics

The Impact metrics refer to the properties of the impacted component.

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 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 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 that one has in the description of a vulnerability.

Environmental Metrics

[email protected]
V2 7.2 AV:L/AC:L/Au:N/C:C/I:C/A:C [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.

Exploit information

Exploit Database EDB-ID : 41365

Publication date : 2017-02-14 23h00 +00:00
Author : Google Security Research
EDB Verified : Yes

Source: https://bugs.chromium.org/p/project-zero/issues/detail?id=1012 DxgkDdiSubmitCommandVirtual is the function implemented by the kernel mode driver responsible for submitting a command buffer to the GPU. One of the arguments passed contains vendor specific data from the user mode driver. The kernel allocates a single buffer for this purpose for all submit calls for the same context. NVIDIA implements this data as: struct NvPrivateHeader { DWORD magic; WORD unknown_4; WORD unknown_6; DWORD unknown_8; DWORD size; }; struct NvPrivateData { NvPrivateHeader header; DWORD unknown_0; DWORD unknown_1; DWORD some_size; DWORD unknown_2; PVOID a_gpu_address_maybe; BYTE unknown[1220]; }; In one of the functions that process this data, there appears to be code to shift around the contents of this user private data. // |len| is controlled by the user. can come from the |some_size| field if the |a_gpu_address_maybe| field is 0. if ( len ) { if ( 8 * len >= pCommand_->DmaBufferPrivateDataSize - 0x4E8 ) do_debug_thingo(); // doesn't stop the memcpy priv_data = (NvSubmitPrivateData *)pCommand_->pDmaBufferPrivateData; src = (char *)priv_data + priv_data->header.size; // unchecked length priv_data = (NvSubmitPrivateData *)((char *)priv_data + 1256); *(_QWORD *)&v4->unknown_0[256] = priv_data; // potential bad memcpy memcpy(priv_data, src, 8 * len); } There are two main problems here: the |len| value is checked, but that appears to only call a debug logging function and not actually stop the memcpy that occurs afterwards. Also, the |size| field from the header is not properly checked to be smaller than the actual size of the data (this is also checked in the calling function but once again only calls do_debug_thingo()). This lets an attacker specify an arbitrary length for the copy, as well as specify an arbitrary 32-bit offset to copy from, leading to pool memory corruption. Crashing context with PoC (Win 10 x64, driver version 375.95): PAGE_FAULT_IN_NONPAGED_AREA (50) ... rax=0000000000000008 rbx=0000000000000000 rcx=ffffb2087fe8f4f0 rdx=0000000041413c59 rsi=0000000000000000 rdi=0000000000000000 rip=fffff8035fc15b00 rsp=ffffd88179edd1a8 rbp=0000000000000080 r8=00000000020a0a08 r9=0000000000105050 r10=0000000000000000 r11=ffffb2087fe8f4f0 r12=0000000000000000 r13=0000000000000000 r14=0000000000000000 r15=0000000000000000 iopl=0 nv up ei ng nz na po nc nvlddmkm+0x5e5b00: fffff803`5fc15b00 f30f6f040a movdqu xmm0,xmmword ptr [rdx+rcx] ds:ffffb208`c12a3149=???????????????????????????????? Resetting default scope Proof of Concept: https://gitlab.com/exploit-database/exploitdb-bin-sploits/-/raw/main/bin-sploits/41365.zip

Products Mentioned

Configuraton 0

Nvidia>>Gpu_driver >> Version -

Microsoft>>Windows >> Version -

References

https://www.exploit-db.com/exploits/41365/
Tags : exploit, x_refsource_EXPLOIT-DB