CWE-770

Etherpad < 1.8.3 is affected by a missing lock check which could cause a denial of service. Aggressively targeting random pad import endpoints with empty data would flatten all pads due to lack of rate limiting and missing ownership check.

An issue has been found in function XRef::fetch in PDF2JSON 0.70 that allows attackers to cause a Denial of Service due to a stack overflow .

An issue has been found in function vfprintf in PDF2JSON 0.70 that allows attackers to cause a Denial of Service due to a stack overflow.

An uncontrolled memory allocation in DataBufdata(subBox.length-sizeof(box)) function of Exiv2 0.27 allows attackers to cause a denial of service (DOS) via a crafted input.

The parse_report() function in whoopsie.c in Whoopsie through 0.2.69 mishandles memory allocation failures, which allows an attacker to cause a denial of service via a malformed crash file.

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.