Centripetal Networks, Inc.

Centripetal LLC

Jonathan R Rogers

Sean A Moore

Peter P Geremia

Vincent Mutolo

David K Ahn

Robert T Perry

Pierre Mallett, Iii

Keith A George

Jess P Parnell

Steven Rogers

John W Fenton

Richard Goodwin

Zachary Ehnerd

John Fenton

Pierre Mallett Iii

Iii Pierre Mallett

The attack vectors for some denial-of-service cyber attacks on the Internet's Domain Name System (DNS) are bad, bogus, or unregistered domain name DNS requests to resolve domain names that are not registered in the DNS. Some other cyber attacks steal sensitive data by encoding the data in bogus domain names, or domain names otherwise not registered in the DNS, that are transferred across networks in bogus DNS requests. A DNS gatekeeper may filter in-transit packets containing DNS requests and may efficiently determine if a request's domain name is registered in the DNS. When the domain name is not registered in the DNS, the DNS gatekeeper may take one of a plurality of protective actions. The DNS gatekeeper drops requests determined not to be legitimate, which may prevent an attack.

Methods and systems for prevention of attacks associated with the domain name system

Methods and systems are disclosed for integrating cyber threat intelligence (CTI), threat metadata, and threat intelligence gateways with analysis systems to form efficient and effective system for active, proactive, and reactive network protection. A network gateway may be composed of multiple stages. A first stage may include a threat intelligence gateway (TIG). A second stage may include one or more cyber analysis systems that ingest TIG-filtered communications and associated threat metadata signals. A third stage may include network protection logic that determines which protective actions. The gateway may be provisioned and configured with rules that specify the network protection policies to be enforced. The gateway may ingest all communications flowing between the protected network and the unprotected network.

Methods and systems for efficient network protection

A packet-filtering system described herein may be configured to filter packets with encrypted hostnames in accordance with one or packet-filtering rules. The packet-filtering system may resolve a plaintext hostname from ciphertext comprising an encrypted Server Name Indication (eSNI) value. The packet-filtering system may resolve the plaintext hostname using a plurality of techniques. Once the plaintext hostname is resolved, the packet-filtering system may then use the plaintext hostname to determine whether the packets are associated with one or more threat indicators. If the packet-filtering system determines that the packets are associated with one or more threat indicators, the packet-filtering system may apply a packet filtering operation associated with the packet-filtering rules to the packets.

Methods and systems for efficient encrypted SNI filtering for cybersecurity applications

A threat intelligence gateway (TIG) may protect TCP/IP networks from network (e.g., Internet) threats by enforcing certain policies on in-transit packets that are crossing network boundaries. The policies may be composed of packet filtering rules with packet-matching criteria derived from cyber threat intelligence (CTI) associated with Internet threats. These CTI-derived packet-filtering rules may be created offline by policy creation and management servers, which may distribute the policies to subscribing TIGs that subsequently enforce the policies on in-transit packets. Each packet filtering rule may specify a disposition that may be applied to a matching in-transit packet, such as deny/block/drop the in-transit packet or pass/allow/forward the in-transit packet, and also may specify directives that may be applied to a matching in-transit packet, such as log, capture, spoof-tcp-rst, etc. Often, however, the selection of a rule's disposition and directives that best protect the associated network may not be optimally determined before a matching in-transit packet is observed by the associated TIG. In such cases, threat context information that may only be available (e.g., computable) at in-transit packet observation and/or filtering time, such as current time-of-day, current TIG/network location, current TIG/network administrator, the in-transit packet being determined to be part of an active attack on the network, etc., may be helpful to determine the disposition and directives that may best protect the network from the threat associated with the in-transit packet. The present disclosure describes examples of methods, systems, and apparatuses that may be used for efficiently determining (e.g., accessing and/or computing), in response to the in-transit packet, threat context information associated with an in-transit packet. The threat context information may be used to efficiently determine the disposition and/or one or more directives to apply to the in-transit packet. This may result in dispositions and/or directives being applied to in-transit packets that better protect the network as compared with solely using dispositions and directives that were predetermined prior to receiving the in-transit packet.

Efficient threat context-aware packet filtering for network protection

A packet-filtering network appliance such as a threat intelligence gateway (TIG) protects TCP/IP networks from Internet threats by enforcing certain policies on in-transit packets that are crossing network boundaries. The policies are composed of packet filtering rules derived from cyber threat intelligence (CTI). Logs of rule-matching packets and their associated flows are sent to cyberanalysis applications located at security operations centers (SOCs) and operated by cyberanalysts. Some cyber threats/attacks, or incidents, are composed of many different flows occurring at a very high rate, which generates a flood of logs that may overwhelm computer, storage, network, and cyberanalysis resources, thereby compromising cyber defenses. The present disclosure describes incident logging, in which a single incident log efficiently incorporates the logs of the many flows that comprise the incident, thereby potentially reducing resource consumption while improving the informational/cyberanalytical value of the incident log for cyberanalysis when compared to the component flow logs. Incident logging vs. flow logging can be automatically and adaptively switched on or off depending on the combination of resource consumption and informational/cyberanalytical value.

Methods and systems for efficient adaptive logging of cyber threat incidents

A cyber threat intelligence (CTI) gateway device may receive rules for filtering TCP/IP packet communications events that are configured to cause the CTI gateway device to identify communications corresponding to indicators, signatures, and behavioral patterns of network threats. The CTI gateway device may receive packets that compose endpoint-to-endpoint communication events and, for each event, may determine that the event corresponds to criteria specified by a filtering rule. The criteria may correspond to one or more of the network threat indicators, signatures, and behavioral patterns. The CTI gateway may create a log of the threat event and forward the threat event log to a task queue managed by a cyberanalysis workflow application. Human cyberanalysts use the cyberanalysis workflow application to service the task queue by removing the task at the front of the queue, investigating the threat event, and deciding whether the event is a reportable finding that should be reported to the proper authorities. In order to improve the efficiency of the workflow process, tasks in the queue are ordered by the likelihood, or probability, that cyberanalysts will determine the associated threat events to be reportable findings; thus, high-likelihood events are investigated first. Likelihoods are computed using human-designed algorithms and machine-learned algorithms that are applied to characteristics of the events. Low-likelihood events may be dropped from the work queue to further improve efficiency.

Cyberanalysis workflow acceleration

A packet gateway may protect TCP/IP networks by enforcing security policies on in-transit packets that are crossing network boundaries. The policies may include packet filtering rules derived from cyber threat intelligence (CTI). The rapid growth in the volume of CTI and in the size of associated CTI-derived policies, coupled with ever-increasing network link speeds and network traffic volume, may cause the costs of sufficient computational resources to be prohibitive. To efficiently process packets, a packet gateway may be provided with at least one probabilistic data structure, such as a Bloom filter, for testing packets to determine if packet data may match a packet filtering rule. Packet filtering rules may be grouped into subsets of rules, and a data structure may be provided for determining a matching subset of rules associated with a particular packet.

Methods and systems for efficient packet filtering

A packet-filtering device may receive packet-filtering rules configured to cause the packet-filtering device to identify packets corresponding to network-threat indicators. The packet-filtering device may receive packets and, for each packet, may determine that the packet corresponds to criteria specified by a packet-filtering rule. The criteria may correspond to one or more of the network-threat indicators. The packet-filtering device may apply an operator specified by the packet-filtering rule. The operator may be configured to cause the packet-filtering device to either prevent the packet from continuing toward its destination or allow the packet to continue toward its destination. The packet-filtering device may generate a log entry comprising information from the packet-filtering rule that identifies the one or more network-threat indicators and indicating whether the packet-filtering device prevented the packet from continuing toward its destination or allowed the packet to continue toward its destination.

Growing community of inventors

Hampton Falls, NH, United States of America

Jonathan R Rogers