CVE-2020-15481

CVE-2020-15481

An issue was discovered in PassMark BurnInTest v9.1 Build 1008, OSForensics v7.1 Build 1012, and PerformanceTest v10.0 Build 1008. The kernel driver exposes IOCTL functionality that allows low-privilege users to map arbitrary physical memory into the address space of the calling process. This could lead to arbitrary Ring-0 code execution and escalation of privileges. This affects DirectIo32.sys and DirectIo64.sys drivers. This issue is fixed in BurnInTest v9.2, PerformanceTest v10.0 Build 1009, OSForensics v8.0.

Source: CVE-2020-15481

CVE-2020-6157

CVE-2020-6157

Opera Touch for iOS before version 2.4.5 is vulnerable to an address bar spoofing attack. The vulnerability allows a malicious page to trick the browser into showing an address of a different page. This may allow the malicious page to impersonate another page and trick a user into providing sensitive data.

Source: CVE-2020-6157

CVE-2020-27217

CVE-2020-27217

In Eclipse Hono version 1.3.0 and 1.4.0 the AMQP protocol adapter does not verify the size of AMQP messages received from devices. In particular, a device may send messages that are bigger than the max-message-size that the protocol adapter has indicated during link establishment. While the AMQP 1.0 protocol explicitly disallows a peer to send such messages, a hand crafted AMQP 1.0 client could exploit this behavior in order to send a message of unlimited size to the adapter, eventually causing the adapter to fail with an out of memory exception.

Source: CVE-2020-27217

CVE-2020-26230

CVE-2020-26230

Radar COVID is the official COVID-19 exposure notification app for Spain. In affected versions of Radar COVID, identification and de-anonymization of COVID-19 positive users that upload Radar COVID TEKs to the Radar COVID server is possible. This vulnerability enables the identification and de-anonymization of COVID-19 positive users when using Radar COVID. The vulnerability is caused by the fact that Radar COVID connections to the server (uploading of TEKs to the backend) are only made by COVID-19 positives. Therefore, any on-path observer with the ability to monitor traffic between the app and the server can identify which users had a positive test. Such an adversary can be the mobile network operator (MNO) if the connection is done through a mobile network, the Internet Service Provider (ISP) if the connection is done through the Internet (e.g., a home network), a VPN provider used by the user, the local network operator in the case of enterprise networks, or any eavesdropper with access to the same network (WiFi or Ethernet) as the user as could be the case of public WiFi hotspots deployed at shopping centers, airports, hotels, and coffee shops. The attacker may also de-anonymize the user. For this additional stage to succeed, the adversary needs to correlate Radar COVID traffic to other identifiable information from the victim. This could be achieved by associating the connection to a contract with the name of the victim or by associating Radar COVID traffic to other user-generated flows containing identifiers in the clear (e.g., HTTP cookies or other mobile flows sending unique identifiers like the IMEI or the AAID without encryption). The former can be executed, for instance, by the Internet Service Provider or the MNO. The latter can be executed by any on-path adversary, such as the network provider or even the cloud provider that hosts more than one service accessed by the victim. The farther the adversary is either from the victim (the client) or the end-point (the server), the less likely it may be that the adversary has access to re-identification information. The vulnerability has been mitigated with the injection of dummy traffic from the application to the backend. Dummy traffic is generated by all users independently of whether they are COVID-19 positive or not. The issue was fixed in iOS in version 1.0.8 (uniform distribution), 1.1.0 (exponential distribution), Android in version 1.0.7 (uniform distribution), 1.1.0 (exponential distribution), Backend in version 1.1.2-RELEASE. For more information see the referenced GitHub Security Advisory.

Source: CVE-2020-26230