White Paper I: Primer to Passive Discovery and Topology Inference in IPv6 Networks Using Neighbor Discovery Protocol
Introduction
IPv6 drastically reshapes the surface of network reconnaissance, replacing the narrow 32-bit address space and broadcast semantics of IPv4 with expansive subnets and a multicast-centric control architecture. In this new model, Neighbor Discovery Protocol (NDP), Multicast Listener Discovery (MLD), and ICMPv6 signaling collectively define how hosts announce their presence, interact with routers, form addresses, resolve local neighbors, and verify reachability. Although this model was engineered for efficiency and stateless configuration, its reliance on predictable multicast traffic introduces a rich layer of metadata that can be quietly harvested by a passive observer. This paper explores the extent to which NDP, and its associated control protocols, leaks meaningful information about a network’s hosts, topology, addressing structure, and operational state. It also outlines how these behaviors can be transformed into the foundation of a silent IPv6 reconnaissance system capable of building detailed environment maps without transmitting a single packet.
A Deeper Look
At its core, NDP replaces ARP with a more structured exchange of Neighbor Solicitations (NS) and Neighbor Advertisements (NA), operating entirely on-link and relying heavily on solicited-node multicast groups. Every host must participate in these exchanges, either to detect duplicate addresses, perform address resolution, defend an address already in use, or validate neighbor reachability. Unlike IPv4 ARP, these operations occur against a backdrop of far more active signaling, especially during system boot, network reattachment events, and periodic router control flows. Because each NS and NA is sent via a predictable multicast address constructed from the host's IPv6 interface identifier, passive listeners monitoring all solicited-node multicast destinations can reconstruct a full map of MAC-to-IPv6 bindings as they occur. Even more revealing is the Duplicate Address Detection phase, during which a host emits an NS for any address it intends to claim. These packets expose not only that a system has come online, but also all temporary privacy addresses it will soon use. This behavior alone makes DAD one of the most powerful passive reconnaissance vectors in modern enterprise environments, as it advertises the existence of hosts well before they can be discovered through higher-layer traffic or active probing.
In addition to neighbor resolution traffic, the behavior of routers in an IPv6 network produces another rich source of architectural information. Router Advertisements (RA) define the operational mode of the subnet, listing available prefixes, their lifetimes, SLAAC flags, reachable time parameters, DNS configuration options, and route information that may reveal internal topologies or policy decisions. By simply observing RAs, a passive sensor can infer which devices function as upstream gateways, how they segment responsibilities, which subnets are operational, and whether the environment uses SLAAC, DHCPv6, or hybrid addressing policies. The cadence, ordering, and option formatting of RA messages also tend to vary by vendor and firmware family, offering indirect OS fingerprinting opportunities that would be difficult to obtain through active interrogation.
Beyond NDP itself, multicast ecosystem protocols such as MLD expand the depth of reconnaissance. MLD’s role in managing multicast membership allows a passive monitor to observe which hosts join particular multicast groups, sometimes indicating the presence of IPv6 services that rely on group communication. Because MLD traffic often includes link-layer source addresses and explicit membership states, it correlates cleanly with NDP-derived address mappings. Together, these protocols reveal patterns in system behavior, including the rotation intervals of privacy addresses, the frequency of reattachment events, and the presence of dormant or intermittent devices, such as mobile endpoints or IoT equipment, that only occasionally emit control traffic. By correlating these observed patterns over time, a passive system can build probabilistic identity models for hosts, even in networks that aggressively use privacy extensions to mask stable identifiers.
The fundamental challenge passive IPv6 reconnaissance faces is that the protocol suite offers no broadcast or enumeration capability comparable to ARP sweeps or ping scanning in IPv4. Because a /64 IPv6 subnet contains 18 quintillion possible addresses, active scanners cannot rely on address-space traversal, and passive systems cannot assume that silence implies absence. Instead, the power of passive discovery arises from the inevitability of NDP traffic: any functioning host must use NS, NA, and DAD mechanisms to communicate or even to exist safely on the link. In this sense, passive reconnaissance is not an approximation of active scanning, it is a fundamentally different paradigm that listens for the control-plane self-management behavior unavoidable in any IPv6 environment.
Building a reconnaissance platform atop these behaviors requires treating the network as a constantly evolving stream of identity and topology hints. Each NS, NA, RA, and MLD event is a timestamped assertion about the network’s structure, and these assertions must be correlated into coherent lifecycle models of hosts and routers. The system must infer not only which hosts are present, but also when they join, when they rotate privacy addresses, when they move between Wi-Fi and wired segments, and when routers change configurations or refresh prefixes. Over long observation windows, the platform effectively reconstructs the operational profile of the environment: the relative health of routers, the presence or absence of duplicate address anomalies, the rate of host churn, and the relationships between MAC addresses, temporary IPv6 addresses, and multicast memberships. By layering vendor fingerprints, RA cadence analysis, MLD metadata, and DAD timing behavior, the platform becomes capable of identifying OS types, security appliances, virtualization footprints, and even unmanaged devices that appear only intermittently.
This approach can be extended further using reachability heuristics. ICMPv6 errors, such as "Destination Unreachable" or "Packet Too Big," may leak the existence of internal routing policies or path MTU constraints even when the passive monitor is not the intended packet recipient. In environments using segment routing, firewalls with IPv6 inspection, or overlay encapsulation, these side-channel signals can illuminate otherwise opaque infrastructure elements. When correlated with NDP and RA data, these sporadic signals enable the passive system to infer L2/L3 boundaries, virtual or containerized network overlays, and multi-router failover behaviors that would be difficult to detect through active scanning alone.
The result of these capabilities is a new model of IPv6 reconnaissance, one that does not attempt exhaustive enumeration but instead aims to infer presence, behavior, and topology from the inescapable protocols that govern IPv6 operation. A well-designed passive tool can quietly populate a dynamic, high-fidelity map of an enterprise segment, identifying hosts, their preferred addresses, their vendor fingerprints, their active time windows, and their relationship to the upstream routing infrastructure without ever transmitting traffic. This differs significantly from classical IPv4 reconnaissance, shifting emphasis from brute-force enumeration to protocol analysis, temporal correlation, and statistical inference.
As enterprises increasingly adopt IPv6, the organizational need for defensive visibility grows correspondingly. Attackers can already exploit these passive techniques to map networks with near-zero detectability, making it imperative for defenders to build internal tools that understand and monitor the same signals. Developing a passive NDP-driven reconnaissance platform provides exactly this capability. It enables security teams to identify shadow IT, misconfigured devices, anomalous host behavior, or rogue routers purely by examining the IPv6 control plane. At the same time, such a platform provides deep architectural insight into how the IPv6 environment functions, evolves, and degrades over time. Furthermore, the revealed inventory from rebuilding network topologies enables classical vulnerability scanning by targeted known active hosts and adds a potential of near real-time scanning as devices enter the control plane..
Conclusion
This white paper represents the conceptual foundation for such a system. By decoding NDP, RA, MLD, and ICMPv6 patterns, a passive sensor can transform raw multicast traffic into a structured map of network behavior, offering silent, continuous visibility where IPv4-derived scanning techniques cannot operate. As IPv6 adoption accelerates, this passive reconnaissance paradigm will become an essential component of enterprise monitoring, threat hunting, and asset discovery efforts.