Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This office action is responsive to amendment received on 6/25/2026. Claims 1, 8, and 15 are amended. Claims 1-20 are pending examination.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 2A, Prong one.
The claim recites an abstract idea. In particular, the claims recite concepts relating to mental processes and certain methods of organizing human activity.
Claim 1 recites, collecting information describing users and target systems;
generating feature vectors for the target systems and users; training and executing a machine learning model using historical defect submissions; predicting a likelihood that a user will identify a defect in a target system; ranking users based on the predicted likelihood; and selecting and communicating with certain users. These limitations amount to collecting information, analyzing the information, evaluating users, and assigning users to tasks based on the evaluation. Such activities can be performed mentally or with pen and paper and are analogous to managing interactions between people and allocating work. The additional limitations directed to scanning target systems to identify open ports and running services and crawling external sources with users merely gather information for users in the evaluation and ranking process. Accordingly, the claims recite an abstract idea.
Step 2A Prong two.
.
The additional elements recited in the claims including: feature vectors, machine learning models, scanning tools, crawlers, processors, memories, and computer networks, simply use generic computer components as tools to perform the abstract idea. Even though the claims recite generating target feature vectors by scanning target systems to identify open ports and running services and generating user feature vectors using information obtained from external sources, these imitations only collect data that is subsequently analyzed by the machine learning model to rank users. The claims do not improve the operation of the scanning tools, the crawler, the machine learning model, or computer technology itself. Moreover, the claims do not recite any improvement to network communications cybersecurity mechanisms, or the functioning of the computer. Rather, the claims use conventional computer comments to implement the abstract idea of predicting which users as more likely to identify the defect in target systems. Accordingly, the claims to no integrate the judicial exception into a practical application.
Step 2B.
The claims do not recite an inventive concept sufficient to transform the abstract idea into patent eligible subject matter. The additional elements individually and in combination amount to no more than the generic and conventional computer functionality. The claims simply use the conventional machine learning models, such as a gradient boosted decision tree and neural networks, together with generic computing components to collect, analyze and evaluate information. The claimed increase in efficiency results from improved selection and ranking of users and not from any technological improvement to the computer systems. The claims simply automate the abstract process of matching users to target systems using conventional computing technology. Therefore, the claims do not amount to significantly more than the judicial exception and are not directed to patent eligible subject matter under 35 U.S.C 101
Response to Arguments
Applicant's arguments filed on 6/25/2026 regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant argues that the amended claim 1 does not recite mental process because the claim recites generating feature vector by scanning a target system to identify open ports and services and generating a user feature vector by crawling external sources associated with users. Applicant further argues that the claimed invention improves the functioning of the online system by reducing the consumption of computing, networking and storage resources.
Applicant’s arguments are not consistent with ethe scope of the claims. Claim 1 as amended, is directed to receiving information describing target systems and users, extracting features from the target systems and users, applying a machine learning model to predict a likelihood that a user will identify a defect in a target system, ranking users according to the predicted likelihood, selecting users based on the ranking, and communicating with the selected users. As such, the claim recites the abstract idea of evaluating and ranking users’ assignment to tasks based on predicted performance. Which falls within the categories of mental processes and certain methods of organizing human activity.
Although, the claims recite additional data-gathering operations, including scanning target systems and crawling external sources, the recited judicial exception is not limited to those operations. The scanning of target systems to identify open ports and services and eh crawling of external websites to obtain user information simply provide information used by the claimed machine learning model and do not change the focus of the claim, which remains directed to the evaluation and selection of users. The automation of information gathering using generic computer technology does not make the claims non abstract.
Applicant further argues that a person could not practically perform the claimed scanning and crawling operations. However, simply performing an activity faster or on a larger scale using computer does not make the claim patent eligible. The inquiry under Step 2A Is whether the claims as a whole is directed to an abstract idea, not whether the computer performs the claimed operation more efficiently. Applicant also argues that eh claims improve efficiency of computing, networking and storage resources by better matching users to target systems. However, these improvements are the result of improving the selection itself, such as selecting users who are more likely to identify defects. The clams do not recite an improvement to computer network, scanning technology, data storage, or machine learning technology. Furthermore, the specification states that the claimed invention uses conventional machine learning techniques, such as gradient- boosted decision trees and neural networks, running on generic computer components. The alleged improvements in submission rates and resource usage result from applying the abstract idea of evaluating and selecting users, rather than from any technological improvement to the computer systems. Therefore, the rejection under 35 U.S.C. 101 is maintained.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SARGON N NANO/Primary Examiner, Art Unit 2443
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