Potential-based interactions play a vital role across a plethora of research fields, including microbiological structures such as collagen fibers assembled from individual tropocollagen molecules, materials science systems like bundles of carbon nanotubes, or even in medical applications such as drug–target binding. In many cases, these microscale interactions occur between slender, rod-like fibers. Owing to the small occurring length scales of these systems, it is often highly complex or even impossible to gain further insights into the fundamental nanomechanical behaviour with experimental investigations. Therefore, in silico models are a promising tool for a better fundamental understanding of underlying mechanisms. The present work employs geometrically exact finite beam elements to model the interaction of slender fibers. Resulting intermolecular forces are evaluated through the section–beam interaction potential (SBIP) approach derived from fundamental interaction principles. By introducing a dimensionally reduced surrogate body for one of the interacting fibers, the SBIP approach significantly improves computational efficiency compared to a brute force evaluation scheme. A current limitation of the SBIP approach is the absence of axial pull-off forces during the separation of parallel fibers, which arises from the assumption of an infinitely long surrogate body. To address this limitation, a novel modeling extension at fiber endpoints is introduced, efficiently capturing these effects. However, the resulting formulation leads to asymmetry due to the single-sided surrogate body principle inherent to the SBIP approach. To resolve this asymmetry, the method is extended by a novel two-half-pass approach, yielding a fully symmetric formulation. The presented advancements to the SBIP approach now enable its application to nanomechanical fibrous real-world problems, such as the modeling of intermolecular phenomena in collagen fibrils, and can, in turn, contribute to the understanding of fundamental pathophysiological processes within biological tissues.