CPE, which stands for Common Platform Enumeration, is a standardized scheme for naming hardware, software, and operating systems. CPE provides a structured naming scheme to uniquely identify and classify information technology systems, platforms, and packages based on certain attributes such as vendor, product name, version, update, edition, and language.
CWE, or Common Weakness Enumeration, is a comprehensive list and categorization of software weaknesses and vulnerabilities. It serves as a common language for describing software security weaknesses in architecture, design, code, or implementation that can lead to vulnerabilities.
CAPEC, which stands for Common Attack Pattern Enumeration and Classification, is a comprehensive, publicly available resource that documents common patterns of attack employed by adversaries in cyber attacks. This knowledge base aims to understand and articulate common vulnerabilities and the methods attackers use to exploit them.
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Out-of-bounds Read The product reads data past the end, or before the beginning, of the intended buffer.
Metrics
Metrics
Score
Severity
CVSS Vector
Source
V3.1
9.8
CRITICAL
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/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.
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.
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
7.5
AV:N/AC:L/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
0.82%
–
–
–
–
2021-09-05
–
0.82%
–
–
–
2021-10-17
–
0.82%
–
–
–
2022-01-02
–
0.82%
–
–
–
2022-01-09
–
0.82%
–
–
–
2022-02-06
–
–
34.79%
–
–
2022-04-03
–
–
34.79%
–
–
2023-03-12
–
–
–
3.1%
–
2023-04-09
–
–
–
3.04%
–
2023-05-07
–
–
–
3.14%
–
2023-06-11
–
–
–
3.5%
–
2023-07-16
–
–
–
3.81%
–
2023-08-06
–
–
–
4.31%
–
2023-08-20
–
–
–
4.15%
–
2023-09-10
–
–
–
4.64%
–
2023-10-08
–
–
–
4.74%
–
2023-10-22
–
–
–
5.65%
–
2023-11-19
–
–
–
5.65%
–
2023-12-03
–
–
–
5.65%
–
2023-12-17
–
–
–
5.65%
–
2024-06-02
–
–
–
5.65%
–
2024-08-25
–
–
–
6.45%
–
2024-10-13
–
–
–
5.98%
–
2024-11-10
–
–
–
6.52%
–
2024-12-08
–
–
–
5.78%
–
2024-12-15
–
–
–
6.61%
–
2024-12-29
–
–
–
6.51%
–
2025-01-19
–
–
–
6.38%
–
2025-02-09
–
–
–
5.44%
–
2025-01-19
–
–
–
6.38%
–
2025-02-16
–
–
–
5.44%
–
2025-03-18
–
–
–
–
23.74%
2025-03-18
–
–
–
–
23.74,%
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.
Publication date : 2019-09-23 22h00 +00:00 Author : Google Security Research EDB Verified : Yes
When an NSKeyedUnarchiver decodes an object, it first allocates the object using allocWithZone, and then puts the object into a dictionary for temporary objects. It then calls the appropriate initWithCoder: on the allocated object. If initWithCoder: or any method it calls decodes the same object, its gets back a reference to the original object in the temporary object dictionary. For many classes, this is a placeholder object that will throw an "uninitialized" exception when accessed, but for some classes, this is the object that will eventually be returned by initWithCoder:. This means that when an initWithCoder: method decodes an object that has a reference to itself in it, the object might not be fully initialized.
The NSSharedKeyDictionary class is a subclass of NSDictionary that allows for a dictionary to be greatly optimized if the keys it uses are declared up front. The keys are specified in an instance of class NSSharedKeySet. This instance can have a child keyset, and the child keyset can also have a child keyset and so on. This allows for multiple keysets to be used by a single dictionary. When a dictionary is initialized, it adds the length of its keyset as well as child keysets at each level, and initializes a value array of that length. Values are then stored and accessed by calculating a key's index based on its position in it keyset, and accessing that location in the value array.
It is possible to combine these two behaviors to create an NSSharedKeyDictionary with a value array that is too small. When an NS NSSharedKeyDictionary is decoded, it will start by decoding the NSSharedKeySet for that dictionary. That keyset, can in turn decode another dictionary as one of its keys. If the second dictionary decodes the same keyset as its keyset, it will get back a reference to the keyset that is in the process of being initialized. That keyset could have a child keyset, but the child keyset has not been decoded at this stage in initializtion. This leads to the second dictionary calculating the length of its value array based on keyset not having a child keyset, even though it could have one. This means that if a key in the child keyset of this array is accessed in this dictionary, the value returned will be read from unallocated memory on the heap (this memory could also be written if a key in the child keyset is set, but it unusual for decoded dictionaries to be written to).
To reproduce this issue in iMessage:
1) install frida (pip3 install frida)
2) open sendMessage.py, and replace the sample receiver with the phone number or email of the target device
3) in injectMessage.js replace the marker "PATH" with the path of the obj file
4) in the local directory, run:
python3 sendMessage.py
This PoC does not crash very reliably in Springboard, though I think this issue is likely exploitable. To make reproducing this issue easier, I've attached a test program for Mac that reproduces the decoding issue. To reproduce the issue using this program:
1) Build the program:
clang decodeshared.m -o decodeshared -fobjc-arc -framework Corespotlight
2) Run the program with libgmalloc and the attached obj file:
DYLD_INSERT_LIBRARIES=/usr/lib/libgmalloc.dylib ./decodeshared obj
This will lead to a consistent crash where the out-of-bounds read occurs.
A log of this issue crashing in Springboard is attached.
The NSSharedDictionary initWithCoder implementation is very complex and greatly increases the attack surface of decoding the NSDictionary class. Moreover, it has functional problems that suggest that it is not widely used, and NSSharedDictionary instances can be correctly encoded and decoded with the NSDictionary initWithCoder. I recommend that this issue be resolved by removing custom encoding for the NSSharedDictionary class.
Proof of Concept:
https://gitlab.com/exploit-database/exploitdb-bin-sploits/-/raw/main/bin-sploits/47415.zip
Publication date : 2019-11-10 23h00 +00:00 Author : Google Security Research EDB Verified : Yes
During processing of incoming iMessages, attacker controlled data is deserialized using the
NSUnarchiver API. One of the classes that is allowed to be decoded from the incoming data is
NSDictionary. However, due to the logic of NSUnarchiver, all subclasses of NSDictionary that also
implement secure coding can then be deserialized as well. NSSharedKeyDictionary is an example of
such a subclass. A NSSharedKeyDictionary is a dictionary for which, for performance reasons, the
keys are predefined using a NSSharedKeySet.
A NSSharedKeyDictionary is essentially a linear array of values and a pointer to its
NSSharedKeySet. An NSSharedKeySet on the other hand looks roughly like this (with some fields
omitted for simplicity and translated to pseudo-C):
struct NSSharedKeySet {
unsigned int _numKeys; // The number of keys in the _keys array
id* _keys; // A pointer to an array containing the key values
unsigned int _rankTable; // A table basically mapping the hashes of
// the keys to an index into _keys
unsigned int _M; // The size of the _rankTable
unsigned int _factor; // Used to compute the index into _rankTable from a hash.
NSSharedKeySet* _subKeySet; // The next KeySet in the chain
};
The value lookup on an NSSharedKeyDictionary then works roughly as follows:
* NSSharedKeyDictionary invokes [NSSharedKeySet indexForKey:] on its associated keySet
* indexForKey: computes the hash of the key, basically computes rti = hash % _factor, bounds-checks
that against _M, and finally uses it to lookup the index in its rankTable: idx = _rankTable[rti]
* It verifies that idx < _numKeys
* It loads _keys[idx] and invokes [key isEqual:candidate] with it as argument
* If the result is true, the index has been found and is returned to the NSSharedKeyDictionary where
it is used to index into its values array
* If not, indexForKey: recursively processes the subKeySet in the same way until it either finds the
key or there is no subKeySet left, in which case it returns -1
The NSArchiver format is powerful enough to allow reference cycles between decoded objects.
This now enables the following attack:
SharedKeyDictionary1 --[ keySet ]-> SharedKeySet1 --[ subKeySet ]-> SharedKeySet2 --+
^ |
| [ subKeySet ]
| |
+-----------------------------------------+
What will happen now is the following:
* The SharedKeyDictionary1 is decoded and its initWithCoder: executed
* [NSSharedKeyDictionary initWithCoder:] decodes its _keySet, which is SharedKeySet1
* The [NSSharedKeySet initWithCoder:] for SharedKeyDictionary1 reads and initializes the following fields:
* _numKeys, which at this point is unchecked and can be any unsigned integer value.
Only later will it be checked to be equal to the number of keys in the _keys array.
* _rankTable, with completely attacker controlled content
* _M, which must be equal to the size of the _rankTable
* _factor, which must be a prime but otherwise can be arbitrarily chosen
At this point, _numKeys = 0xffffffff but _keys is still nullptr (because ObjC objects are
allocated with calloc)
* Next, *before* initializing _keys, it deserializes the _subKeySet, SharedKeySet2
* [NSSharedKeySet initWithCoder:] of SharedKeySet2 finishes, and at the end verifies that
it is a valid SharedKeySet. It does that by checking that all its keys correctly map to an index.
For that it calls [NSSharedKeySet indexForKey:] on itself for every key.
* (At least) one of the keys will, however, not be found on SharedKeySet2. As such,
indexForKey: will proceed to search for the key in its _subKeySet, which is actually SharedKeySet1
* The lookup proceeds and determines that the index should be (in our case) 2189591170, which is
less than SharedKeySet1->numKey (which is still 0xffffffff)
* It then loads SharedKeySet1->keys[2189591170], which, as ->_keys is still nullptr, reads an
objc_object* from 0x414141410 and thus crashes
The attached PoC demonstrates this on the latest macOS 10.14.6
> clang -o tester tester.m -framework Foundation
> ./generator.py
> lldb -- ./tester payload.xml
(lldb) target create "./tester"
Current executable set to './tester' (x86_64).
(lldb) settings set -- target.run-args "payload.xml"
(lldb) r
2019-07-29 15:40:28.989305+0200 tester[71168:496831] Let's go
Process 71168 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x414141410)
frame #0: 0x00007fff3390d3e7 CoreFoundation`-[NSSharedKeySet indexForKey:] + 566
CoreFoundation`-[NSSharedKeySet indexForKey:]:
-> 0x7fff3390d3e7 <+566>: mov rdx, qword ptr [rax + 8*r13]
Combined with a heap spray, this bug could likely be remotely exploitable.
Ideally, this issue and similar ones can be prevented by removing the NSSharedKeyDictionary attack
surface completely, as originally suggested by Natalie. Alternatively, I think another solution
might be to stop encoding all the internal fields of the NSSharedKeyDictionary/NSSharedKeySet
(rankTable, numKeys, especially the subKeySet, ...) and only encode the keys and values. The new
[initWithCoder:] implementations could then just call +[NSSharedKeySet keySetWithKeys:] and
+[NSSharedKeyDictionary sharedKeyDictionaryWithKeySet:] to construct new instances with the decoded
keys and values. This should be fine as all the other fields are implementation details anyway.
Proof of Concept:
https://gitlab.com/exploit-database/exploitdb-bin-sploits/-/raw/main/bin-sploits/47608.zip