What is a Sybil attack?
In short
A Sybil attack is the creation of many seemingly independent identities by the same attacker, in order to gain disproportionate influence over a network or an application.
Imagine a building residents’ vote where the same tenant shows up under different names and votes again and again. There seem to be lots of participants, but behind them is one person. That’s roughly how a Sybil attack works in the digital world.
The attacker creates or controls many accounts, wallet addresses or nodes, meaning computers that take part in a network. If the system treats each identity as a separate, independent participant, it may grant the attacker more influence or more rewards than they are entitled to.
For example, an app distributes tokens through an airdrop to users who tried it out. Someone uses many wallets, trying to appear as many different users and collect multiple allocations. In a network, likewise, many controlled nodes can be used to influence the connections and information that other participants receive.
Why it matters
In open systems, creating a new digital identity often costs next to nothing. The hard part is making sure that many identities don’t automatically translate into more power.
That’s why mechanisms such as Proof of Work and Proof of Stake don’t base consensus on simply counting nodes. They tie influence to computational work or to locked-up capital, respectively. Creating additional identities doesn’t, on its own, increase these resources.
For you, this concerns both a network’s security and the reliability of a project’s numbers. Thousands of active addresses don’t necessarily mean thousands of different people. We consider this distinction essential when we assess claims about adoption and decentralization.
What to watch out for
Holding many wallets is not an attack in itself. There are legitimate reasons to keep funds and activities separate. The issue is using multiple identities to deceive or to get around the rules.
Also, a Sybil attack is not the same as a 51% attack, and it doesn’t automatically allow funds to be stolen or the blockchain to be changed. The consequences depend on how the system is designed. Identity checks, participation costs and behavioral filters can limit abuse, but they may come at the expense of privacy or wrongly exclude regular users.