Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.