Centripetal Networks, Inc.

Centripetal LLC

Vincent Mutolo

Sean A Moore

Jonathan R Rogers

Peter P Geremia

Alexander Chinchilli

Connor Tess

Matthew Sparrow

John W Fenton

Jess P Parnell

Richard Goodwin

Paul Sprague

Justin Makoto Leach

Christopher T Rodney

John Fenton

Jess Parnell

Methods, apparatuses, systems, and machine-readable media are disclosed for improving packet filtering efficiency by reducing processing time and/or by reducing memory usage. Any of various types of data structures, such as flat hash maps and/or ruletrees, may be used by a packet filtering appliance to search for cybersecurity policy packet filtering rules that should be applied to in-transit packets. The packet filtering appliance may search the index data structures for matches of search objects, in the form of values that the packet filtering appliance extracts from in-transit packets, to threat indicator matching criteria of the policy rules. Each of the index data structures may map rule identifiers (rule IDs) of policy rules to keys that are based on (or that comprise) the matching criteria of those rules.

Methods and systems for efficient cybersecurity policy enforcement on network communications

Malicious homoglyphic domain name (MHDN) generation and associated cyber security applications are described. MHDN generation may be performed by, for example, generating, based on training data, a set of operations for use in generating the one or more potential MHDNs, wherein each operation of the set of operations may be configured to modify a base domain name according to a respective homoglyphic characteristic. The set of operations may be used to generate one or more candidate MHDN mutators. The candidate MHDN mutators may be tested for fitness values corresponding to respective likelihoods of generating an MHDN and the candidate MHDN mutators may be applied to one or more base domain names to generate potential MHDNs.

Malicious homoglyphic domain name generation and associated cyber security applications

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

Malicious homoglyphic domain name (MHDN) detection and associated cyber security applications are described. A domain name may be received that may be a potential MHDN. Homoglyphic domain name detection may be performed by, for example, generating a normalized character string corresponding to the input domain name by applying one or more normalization operations to the input domain name, wherein the one or more normalization operations may be configured to reduce homoglyphic characteristics in the input domain name; and generating a plurality of segmentations of the normalized character string, wherein generating each segmentation, of the plurality of segmentations, may comprise segmenting the normalized character string into a respective plurality of segments, and wherein each segmentation may comprise a different plurality of segments. A segmentation may be selected based on cost values corresponding to each respective segmentation determined using a cost function. The received domain name may be determined to be a homoglyphic domain name based on a determination that one or more segments of the selected first segmentation match a base of a known domain name in the at least one list of known domain names.

Malicious homoglyphic domain name detection and associated cyber security applications

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.

Growing community of inventors

Portsmouth, NH, United States of America

Vincent Mutolo