An issue was discovered in OpenEXR before 2.4.1. There is an out-of-bounds read during Huffman uncompression, as demonstrated by FastHufDecoder::refill in ImfFastHuf.cpp.
An issue was discovered in OpenEXR before 2.4.1. There is an out-of-bounds read and write in DwaCompressor::uncompress in ImfDwaCompressor.cpp when handling the UNKNOWN compression case.
An issue was discovered in OpenEXR before 2.4.1. There is an off-by-one error in use of the ImfXdr.h read function by DwaCompressor::Classifier::Classifier, leading to an out-of-bounds read.
cyrus-sasl (aka Cyrus SASL) 2.1.27 has an out-of-bounds write leading to unauthenticated remote denial-of-service in OpenLDAP via a malformed LDAP packet. The OpenLDAP crash is ultimately caused by an off-by-one error in _sasl_add_string in common.c in cyrus-sasl.
A vulnerability was discovered in Linux, FreeBSD, OpenBSD, MacOS, iOS, and Android that allows a malicious access point, or an adjacent user, to determine if a connected user is using a VPN, make positive inferences about the websites they are visiting, and determine the correct sequence and acknowledgement numbers in use, allowing the bad actor to inject data into the TCP stream. This provides everything that is needed for an attacker to hijack active connections inside the VPN tunnel.
Some HTTP/2 implementations are vulnerable to a flood of empty frames, potentially leading to a denial of service. The attacker sends a stream of frames with an empty payload and without the end-of-stream flag. These frames can be DATA, HEADERS, CONTINUATION and/or PUSH_PROMISE. The peer spends time processing each frame disproportionate to attack bandwidth. This can consume excess CPU.
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.