Automated generation and execution of phishing attack simulations
A system and method for automated generation and execution of phishing attack simulations are presented. The method includes generating an enriched prompt corresponding to a selected phishing attack vector based on a user request to generate a phishing attack simulation; prompting, by a reasoning model, the generated enriched prompt to retrieve a phishing simulation template corresponding to the selected phishing attack vector; generating the phishing attack simulation by one or more generative artificial intelligence (genAI) models using the retrieved phishing simulation template and additional information; and executing the generated phishing attack simulation by transmitting the phishing attack simulation to one or more users via an electronic communication environment.
1 . A method for automated generation and execution of phishing attack simulations, comprising:
generating an enriched prompt corresponding to a selected phishing attack vector based on a user request to generate a phishing attack simulation and either evolving cyber threat behavior or organizational policies, wherein the user request comprises a natural language phishing scenario description, further comprising:
mapping the natural language phishing scenario description to a predefined phishing tactic taxonomy; and
gathering contextual information based on the predefined phishing tactic taxonomy to tailor the phishing attack simulation;
prompting, by a reasoning model, the generated enriched prompt to retrieve a phishing simulation template corresponding to the selected phishing attack vector;
generating the phishing attack simulation by one or more generative artificial intelligence (genAI) models using the retrieved phishing simulation template and additional information; and
executing the generated phishing attack simulation by transmitting the phishing attack simulation to one or more users via an electronic communication environment.
2 . The method of claim 1 , further comprising:
capturing interaction data associated with the phishing attack simulation;
analyzing the captured interaction data;
updating a user risk profile based on the analyzed captured interaction data; and
selecting subsequent phishing attack simulations based on the user risk profile.
3 . The method of claim 1 , wherein the selected phishing attack vector comprises one of business email compromise phishing, QR code phishing, or malicious attachment phishing.
4 . The method of claim 1 , wherein the one or more genAI models comprise separate genAI models respectively configured for business email phishing, QR code phishing, and malicious attachment phishing.
5 . The method of claim 1 , wherein the additional information comprises one or more of phishing attack vector parameters, delivery context information, organizational context information, user context information, and open-source intelligence (OSINT) indicators, wherein the OSINT indicators are representative of current phishing tactics, techniques, and procedures.
6 . The method of claim 1 , further comprising:
generating the phishing simulation template from a legitimate electronic communication associated with at least one software-as-a-service (SaaS) provider.
7 . The method of claim 6 , wherein generating the phishing simulation template comprises analyzing visual structure, formatting attributes, and linguistic patterns of the legitimate electronic communication.
8 . The method of claim 6 , further comprising:
generating a plurality of phishing simulation template variants corresponding to different phishing scenarios associated with the SaaS provider.
9 . The method of claim 1 , further comprising:
evaluating the generated phishing attack simulation according to a phishing indicator scale, wherein evaluating further comprises identifying phishing indicators and generating structured explanation data associated with the generated phishing attack simulation.
10 . The method of claim 2 , further comprising:
distinguishing human user interactions from automated scanning activity by evaluating one or more of network characteristics, access timing, and interaction behavior.
11 . The method of claim 1 , wherein executing the generated attack simulation comprises injecting the generated phishing attack simulation directly into a user mailbox via an application programming interface.
12 . The method of claim 8 , wherein the generated phishing simulation templates and the generated variants are periodically updated to reflect current cyber threats, attack techniques, and emerging security trends.
13 . The method of claim 2 , further comprising:
providing user feedback identifying one or more phishing indicators associated with the executed generated phishing attack simulation; and
assigning one or more remediation actions based on the analyzed captured interaction behavior.
14 . A system for automated generation and execution of phishing attack simulations comprising:
one or more processors configured to:
generate an enriched prompt corresponding to a selected phishing attack vector based on a user request to generate a phishing attack simulation and either evolving cyber threat behavior or organizational policies, wherein the user request comprises a natural language phishing scenario description, further comprising:
mapping the natural language phishing scenario description to a predefined phishing tactic taxonomy; and
gathering contextual information based on the predefined phishing tactic taxonomy to tailor the phishing attack simulation;
prompt, by a reasoning model, the generated enriched prompt to retrieve a phishing simulation template corresponding to the selected phishing attack vector
generate the phishing attack simulation by one or more generative artificial intelligence (genAI) models using the retrieved phishing simulation template and additional information; and
execute the generated phishing attack simulation by transmitting the phishing attack simulation to one or more users via an electronic communication environment.
15 . The system of claim 14 , wherein the one or more processors are further configured to:
capture interaction data associated with the phishing attack simulation;
analyze the captured interaction data;
update a user risk profile based on the analyzed captured interaction data; and
select subsequent phishing attack simulations based on the user risk profile.
16 . The system of claim 15 , wherein the one or more processors are further configured to:
distinguish human user interactions from automated scanning activity by evaluating one or more of network characteristics, access timing, and interaction behavior.
17 . The system of claim 15 , wherein the one or more processors are further configured to:
provide user feedback identifying one or more phishing indicators associated with the executed generated phishing attack simulation; and
assign one or more remediation actions based on the analyzed captured interaction behavior.
18 . The system of claim 14 , wherein the one or more processors, when the selected phishing attack vector, are configured to one of business email compromise phish, QR code phishing, or malicious attachment phishing.
19 . The system of claim 14 , wherein the one or more genAI models comprise separate genAI models respectively configured for business email phishing, QR code phishing, and malicious attachment phishing.
20 . The system of claim 14 , wherein the additional information comprises one or more of phishing attack vector parameters, delivery context information, organizational context information, user context information, and open-source intelligence (OSINT) indicators, wherein the OSINT indicators are representative of current phishing tactics, techniques, and procedures.
21 . The system of claim 14 , wherein the one or more processors are further configured to:
generate the phishing simulation template from a legitimate electronic communication associated with at least one software-as-a-service (SaaS) provider.
22 . The system of claim 21 , wherein the one or more processors, when generating the phishing simulation template, are configured to analyze visual structure, formatting attributes, and linguistic patterns of the legitimate electronic communication.
23 . The system of claim 21 , wherein the one or more processors are further configured to:
generate a plurality of phishing simulation template variants corresponding to different phishing scenarios associated with the SaaS provider.
24 . The system of claim 23 , wherein the generated phishing simulation templates and the generated variants are periodically updated to reflect current cyber threats, attack techniques, and emerging security trends.
25 . The system of claim 14 , wherein the one or more processors are further configured to:
evaluate the generated phishing attack simulation according to a phishing indicator scale, wherein evaluating further comprises identifying phishing indicators and generating structured explanation data associated with the generated phishing attack simulation.
26 . The system of claim 14 , wherein the one or more processors, when executing the generated attack simulation, are configured to inject the generated phishing attack simulation directly into a user mailbox via an application programming interface.
27 . A non-transitory computer-readable medium storing a set of instructions for automated generation and execution of phishing attack simulations, the set of instructions comprising:
one or more instructions that, when executed by one or more processors of a device, cause the device to:
generate an enriched prompt corresponding to a selected phishing attack vector based on a user request to generate a phishing attack simulation and either evolving cyber threat behavior or organizational policies, wherein the user request comprises a natural language phishing scenario description, further comprising:
mapping the natural language phishing scenario description to a predefined phishing tactic taxonomy; and
gathering contextual information based on the predefined phishing tactic taxonomy to tailor the phishing attack simulation;
prompt, by a reasoning model, the generated enriched prompt to retrieve a phishing simulation template corresponding to the selected phishing attack vector;
generate the phishing attack simulation by one or more generative artificial intelligence (genAI) models using the retrieved phishing simulation template and additional information; and
execute the generated phishing attack simulation by transmitting the phishing attack simulation to one or more users via an electronic communication environment.