Denial Of Service (DoS)

tensorflow is vulnerable to Denial of Service DoS attacks. A malicious user is able to gain out-of-bounds access due to mismatched integer type sizes in functiondefimport.cc, causing the application to crash...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists due to a null pointer dereference in ImportGenericFunction of functiondefimport.cc because mlir doesn't disallow empty function attributes which allows an attacker to cause an application crash...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists in ImportNodes in functiondefimport.cc because the assertion fails on MLIR when empty edge names are given which causes an application crash...