Simultaneous Multi-threading (SMT) in processors can enable local users to exploit software vulnerable to timing attacks via a side-channel timing attack on 'port contention'.

Simultaneous Multi-threading (SMT) in processors can enable local users to exploit software vulnerable to timing attacks via a side-channel timing attack on 'port contention'.

Simultaneous Multi-threading (SMT) in processors can enable local users to exploit software vulnerable to timing attacks via a side-channel timing attack on 'port contention'.

Simultaneous Multi-threading (SMT) in processors can enable local user ...

The crc32_big function in crc32.c in zlib 1.2.8 might allow context-dependent attackers to have unspecified impact via vectors involving big-endian CRC calculation.

The crc32_big function in crc32.c in zlib 1.2.8 might allow context-dependent attackers to have unspecified impact via vectors involving big-endian CRC calculation.

The crc32_big function in crc32.c in zlib 1.2.8 might allow context-dependent attackers to have unspecified impact via vectors involving big-endian CRC calculation.

The crc32_big function in crc32.c in zlib 1.2.8 might allow context-de ...

Уязвимость пакета cross-spawn программной платформы Node.js, позволяющая нарушителю вызвать отказ в обслуживании

Уязвимость программной платформы Node.js, связанная с использованием ненадёжного пути поиска, позволяющая нарушителю повысить свои привилегии

Уязвимость функции uv__idna_toascii() программной платформы Node.js, позволяющая нарушителю вызвать отказ в обслуживании или получить несанкционированный доступ к защищаемой информации

Уязвимость функций napi_get_value_string_latin1(), napi_get_value_string_utf8(), napi_get_value_string_utf16() программной платформы Node.js, позволяющая нарушителю выполнить произвольный код

Some HTTP/2 implementations are vulnerable to window size manipulation and stream prioritization manipulation, potentially leading to a denial of service. The attacker requests a large amount of data from a specified resource over multiple streams. They manipulate window size and stream priority to force the server to queue the data in 1-byte chunks. Depending on how efficiently this data is queued, this can consume excess CPU, memory, or both.

Some HTTP/2 implementations are vulnerable to resource loops, potentially leading to a denial of service. The attacker creates multiple request streams and continually shuffles the priority of the streams in a way that causes substantial churn to the priority tree. This can consume excess CPU.

Some HTTP/2 implementations are vulnerable to resource loops, potentially leading to a denial of service. The attacker creates multiple request streams and continually shuffles the priority of the streams in a way that causes substantial churn to the priority tree. This can consume excess CPU.

Some HTTP/2 implementations are vulnerable to resource loops, potentially leading to a denial of service. The attacker creates multiple request streams and continually shuffles the priority of the streams in a way that causes substantial churn to the priority tree. This can consume excess CPU.

Some HTTP/2 implementations are vulnerable to resource loops, potentially leading to a denial of service. The attacker creates multiple request streams and continually shuffles the priority of the streams in a way that causes substantial churn to the priority tree. This can consume excess CPU.

Some HTTP/2 implementations are vulnerable to resource loops, potentia ...

Some HTTP/2 implementations are vulnerable to window size manipulation and stream prioritization manipulation, potentially leading to a denial of service. The attacker requests a large amount of data from a specified resource over multiple streams. They manipulate window size and stream priority to force the server to queue the data in 1-byte chunks. Depending on how efficiently this data is queued, this can consume excess CPU, memory, or both.

Some HTTP/2 implementations are vulnerable to window size manipulation and stream prioritization manipulation, potentially leading to a denial of service. The attacker requests a large amount of data from a specified resource over multiple streams. They manipulate window size and stream priority to force the server to queue the data in 1-byte chunks. Depending on how efficiently this data is queued, this can consume excess CPU, memory, or both.