The code performs a comparison such as an equality test between two float (floating point) values, but it uses comparison operators that do not account for the possibility of loss of precision.
Numeric calculation using floating point values can generate imprecise results because of rounding errors. As a result, two different calculations might generate numbers that are mathematically equal, but have slightly different bit representations that do not translate to the same mathematically-equal values. As a result, an equality test or other comparison might produce unexpected results.
This issue can prevent the product from running reliably. If the relevant code is reachable by an attacker, then this reliability problem might introduce a vulnerability.
Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)