indy-node is the server portion of Hyperledger Indy, a distributed ledger purpose-built for decentralized identity. In vulnerable versions of indy-node, an attacker can max out the number of client connections allowed by the ledger, leaving the ledger unable to be used for its intended purpose. However, the ledger content will not be impacted and the ledger will resume functioning after the attack. This attack exploits the trade-off between resilience and availability. Any protection against abusive client connections will also prevent the network being accessed by certain legitimate users. As a result, validator nodes must tune their firewall rules to ensure the right trade-off for their networks expected users. The guidance to network operators for the use of firewall rules in the deployment of Indy networks has been modified to better protect against denial of service attacks by increasing the cost and complexity in mounting such attacks. The mitigation for this vulnerability is not in the Hyperledger Indy code per se, but rather in the individual deployments of Indy. The mitigations should be applied to all deployments of Indy, and are not related to a particular release.
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Indy-node | Linuxfoundation | * | 1.12.6 (including) |
| Indy-node | Linuxfoundation | 1.13.2-rc1 (including) | 1.13.2-rc1 (including) |
Limited resources include memory, file system storage, database connection pool entries, and CPU. If an attacker can trigger the allocation of these limited resources, but the number or size of the resources is not controlled, then the attacker could cause a denial of service that consumes all available resources. This would prevent valid users from accessing the product, and it could potentially have an impact on the surrounding environment. For example, a memory exhaustion attack against an application could slow down the application as well as its host operating system. There are at least three distinct scenarios which can commonly lead to resource exhaustion:
Resource exhaustion problems are often result due to an incorrect implementation of the following situations:
Mitigation of resource exhaustion attacks requires that the target system either:
The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.