CVE Vulnerabilities

CVE-2020-15168

Allocation of Resources Without Limits or Throttling

Published: Sep 10, 2020 | Modified: Sep 17, 2020
CVSS 3.x
5.3
MEDIUM
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
CVSS 2.x
5 MEDIUM
AV:N/AC:L/Au:N/C:N/I:N/A:P
RedHat/V2
RedHat/V3
5.3 LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Ubuntu
LOW

node-fetch before versions 2.6.1 and 3.0.0-beta.9 did not honor the size option after following a redirect, which means that when a content size was over the limit, a FetchError would never get thrown and the process would end without failure. For most people, this fix will have a little or no impact. However, if you are relying on node-fetch to gate files above a size, the impact could be significant, for example: If you dont double-check the size of the data after fetch() has completed, your JS thread could get tied up doing work on a large file (DoS) and/or cost you money in computing.

Weakness

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.

Affected Software

Name Vendor Start Version End Version
Node-fetch Node-fetch_project * 2.6.1 (excluding)
Node-fetch Node-fetch_project 3.0.0-beta1 (including) 3.0.0-beta1 (including)
Node-fetch Node-fetch_project 3.0.0-beta5 (including) 3.0.0-beta5 (including)
Node-fetch Node-fetch_project 3.0.0-beta6 (including) 3.0.0-beta6 (including)
Node-fetch Node-fetch_project 3.0.0-beta7 (including) 3.0.0-beta7 (including)
Node-fetch Node-fetch_project 3.0.0-beta8 (including) 3.0.0-beta8 (including)
Node-fetch Ubuntu bionic *
Node-fetch Ubuntu groovy *
Node-fetch Ubuntu trusty *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat acmesolver-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat acm-must-gather-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat acm-operator-bundle-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat application-ui-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat cainjector-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat cert-manager-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat cert-manager-webhook-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat cert-policy-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat clusterlifecycle-state-metrics-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat configmap-watcher-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat config-policy-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat console-api-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat console-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat console-header-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat console-ui-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat endpoint-component-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat endpoint-monitoring-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat endpoint-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat governance-policy-propagator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat governance-policy-spec-sync-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat governance-policy-status-sync-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat governance-policy-template-sync-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat grafana-dashboard-loader-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat grc-ui-api-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat grc-ui-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat iam-policy-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat klusterlet-addon-lease-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat klusterlet-operator-bundle-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat kui-web-terminal-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat management-ingress-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat mcm-topology-api-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat mcm-topology-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat memcached-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat memcached-exporter-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat metrics-collector-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicloud-manager-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multiclusterhub-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multiclusterhub-repo-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-observability-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-application-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-channel-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-deployable-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-placementrule-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-subscription-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat multicluster-operators-subscription-release-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat observatorium-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat observatorium-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat openshift-hive-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat rbac-query-proxy-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat rcm-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat redisgraph-tls-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat registration-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat registration-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat search-aggregator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat search-api-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat search-collector-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat search-operator-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat search-ui-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat submariner-addon-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat thanos-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat thanos-receive-controller-container *
Red Hat Advanced Cluster Management for Kubernetes 2 RedHat work-container *

Extended Description

Code frequently has to work with limited resources, so programmers must be careful to ensure that resources are not consumed too quickly, or too easily. Without use of quotas, resource limits, or other protection mechanisms, it can be easy for an attacker to consume many resources by rapidly making many requests, or causing larger resources to be used than is needed. When too many resources are allocated, or if a single resource is too large, then it can prevent the code from working correctly, possibly leading to a denial of service.

Potential Mitigations

  • Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.

  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”

  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

  • 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 can be difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.

  • If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery.

  • Ensure that all failures in resource allocation place the system into a safe posture.

  • Use resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems.

  • When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users.

  • Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).

References