DETAILED ACTION
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 .
Remarks
Claims 1-10 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the fuzzer blank" in line 5. There is insufficient antecedent basis for this limitation in the claim. Dependent claims 2-8 are rejected based up on their dependency on their respective independent claim.
Claim 9 recites the limitation "the fuzzer blank" in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 10 recites the limitation "the fuzzer blank" in line 7. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 6 and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (‘Cai’ hereinafter) (Cai, Zhen, Honglin Wang, and Xiaojun Qin. "A Heuristic Guided Optimized Strategy for Non-Deterministic Mutation." Proceedings of the 3rd International Conference on Computer Science and Application Engineering. 2019) in view of Natella (Natella, Roberto. "Stateafl: Greybox fuzzing for stateful network servers." Empirical Software Engineering 27.7 (2022): 191).
As per claim 1, Cai teaches
A method for treating uncertainty estimates for non-deterministic fuzz executions in a fuzzing system having a fuzzer, comprising the following steps: (see abstract)
initializing the fuzzing system by setting observations of the fuzzer blank or to one or more initial test cases that are executed on a target program; (generates test cases to explore new execution paths within the program, section 2.1, first paragraph)
executing test cases; (test cases are run and tracked, section 2.1, second paragraph; figure 1)
creating an output report for each test case, wherein the output report includes information about a code coverage of the target program; (test cases are run and tracked, coverage information is gathered, section 2.1, second paragraph)
repeating the execution of each test case to determine whether the test case leads to jitter or non-deterministic behavior in the target program; (non-deterministic stage where time wasted on deterministic fuzzing tests is avoided by altering/mutation of bytes to cause non-deterministic behavior and causes inconsistent execution path, sections 2.2-3.2; note that one of skill in the art would know that this mutating of bytes to lead to test cases with non-deterministic behavior would essentially be the same as repeating tests until such non-deterministic behavior occurs)
and adding, to a corpus of the test cases, the new test cases which cause a new behavior of the target program. (test cases are run and tracked, coverage information is gathered to identify interesting test cases (eg, test cases that reach the new control flow edge), and interesting test cases are added to the seed pool for the next round of testing and AFL uses a similar genetic algorithm guided by path coverage for loop iteration, section 2.1)
Cai does not explicitly indicate “deciding using an optimizer based on an estimate, for each of those of the test cases generating jitter or non-deterministic behavior, how often the test case is to be executed in order to obtain an optimized estimate of the code path distribution; deciding using the optimizer whether and how the test cases are mutated to obtain new cases in order to minimize overall uncertainty and to investigate more areas in the target program;”.
However, Natella discloses “deciding using an optimizer based on an estimate, for each of those of the test cases generating jitter or non-deterministic behavior, how often the test case is to be executed in order to obtain an optimized estimate of the code path distribution; deciding using the optimizer whether and how the test cases are mutated to obtain new cases in order to minimize overall uncertainty and to investigate more areas in the target program;” (calibration stage that runs one reference execution and additional repetitions for seeds to determine hash values and distances between hashes to find when outlier thresholds that cause non-determinism, and this shows how often server visits new states that cause these states in the seeds in fuzzing campaign, page 14, first full paragraph; fuzzer can also grow state machine after each input adding a new state to further increase code coverage, pages 14-15; where calibration stage is claimed optimizer, thresholds are claimed estimate, and seeds are test cases mutated to obtain new test cases).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Cai and Natella because using the steps claimed would have given those skilled in the art the tools to improve the invention by providing a less costly solution that provides a greybox fuzzer that relies on lightweight analysis with no manual customization to provide better code coverage and bug detection (see Natella, abstract). This gives the user the advantage of having automated fuzzing solution that are more efficient and less resource intensive.
As per claim 2, Cai teaches
steering the fuzzer in a first fuzzing mode to deterministic locations in the target program and/or steering the fuzzer in a second fuzzing mode to non-deterministic locations in the target program. (non-deterministic stage where time wasted on deterministic fuzzing tests is avoided by altering/mutation of bytes to cause non-deterministic behavior and causes inconsistent execution path, sections 2.2-3.2; note that one of skill in the art would know that this mutating of bytes to lead to test cases with non-deterministic behavior would essentially be the same as repeating tests until such non-deterministic behavior occurs)
As per claim 3, Cai teaches
upon reaching a non-deterministic location in the target program, the fuzzer is switched into another fuzzing mode. (non-deterministic stage where fuzzing includes havoc and splice, section 2.2)
As per claim 4, Cai teaches
the output report includes information about a line coverage, and/or a branch coverage, and/or a functional coverage, and/or an edge coverage. (test cases are run and tracked, coverage information is gathered to identify interesting test cases (eg, test cases that reach the new control flow edge), and interesting test cases are added to the seed pool for the next round of testing, section 2.1)
As per claim 6, Cai teaches
the new test cases can be selected for further mutations. (iterative mutation, section 3.2, second paragraph)
As per claim 9,
This claim is rejected on grounds corresponding to the reasons given above for rejected claim 1 and is similarly rejected.
As per claim 10,
This claim is rejected on grounds corresponding to the reasons given above for rejected claim 1 and is similarly rejected.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (‘Cai’ hereinafter) (Cai, Zhen, Honglin Wang, and Xiaojun Qin. "A Heuristic Guided Optimized Strategy for Non-Deterministic Mutation." Proceedings of the 3rd International Conference on Computer Science and Application Engineering. 2019) in view of Natella (Natella, Roberto. "Stateafl: Greybox fuzzing for stateful network servers." Empirical Software Engineering 27.7 (2022): 191) and further in view of O'Leary et al. (‘O'Leary’ hereinafter) (Patent Number 7594142),
As per claim 5,
Neither Cai nor Natella explicitly indicates “the output report includes time information when testing target programs that have state information”.
However, O'Leary discloses “the output report includes time information when testing target programs that have state information” (column 4, lines 48-68).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Cai, Natella and O'Leary because using the steps claimed would have given those skilled in the art the tools to improve the invention by providing critical data regarding the testing to help guide future tests. This gives the user the advantage of having an archive for future use.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (‘Cai’ hereinafter) (Cai, Zhen, Honglin Wang, and Xiaojun Qin. "A Heuristic Guided Optimized Strategy for Non-Deterministic Mutation." Proceedings of the 3rd International Conference on Computer Science and Application Engineering. 2019) in view of Natella (Natella, Roberto. "Stateafl: Greybox fuzzing for stateful network servers." Empirical Software Engineering 27.7 (2022): 191) and further in view of Shen et al. (‘Shen’ hereinafter) (Shen, Ning, et al. "A practical and secure stateless order preserving encryption for outsourced databases." 2021 IEEE 26th Pacific Rim International Symposium on Dependable Computing (PRDC). IEEE, 2021).
As per claim 7,
Neither Cai nor Natella explicitly indicates “the fuzzing system includes encrypting and/or discarding network packets”.
However, Shen discloses “the fuzzing system includes encrypting and/or discarding network packets” (section IV.D & IV.E).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Cai, Natella and Shen because using the steps claimed would have given those skilled in the art the tools to improve the invention by providing order-preserving encryption (OPE) non-deterministic algorithm to help secure critical databases (see Shen, abstract). This gives the user the advantage of being assured that important information is not hacked.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (‘Cai’ hereinafter) (Cai, Zhen, Honglin Wang, and Xiaojun Qin. "A Heuristic Guided Optimized Strategy for Non-Deterministic Mutation." Proceedings of the 3rd International Conference on Computer Science and Application Engineering. 2019) in view of Natella (Natella, Roberto. "Stateafl: Greybox fuzzing for stateful network servers." Empirical Software Engineering 27.7 (2022): 191) and further in view of Campobasso et al. (‘Campobasso’ hereinafter) (Publication Number 20240211834).
As per claim 8,
Neither Cai nor Natella explicitly indicates “the optimizer includes a Bayesian optimizer”.
However, Campobasso discloses “the optimizer includes a Bayesian optimizer” (paragraph [0037]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Cai, Natella and Campobasso because using the steps claimed would have given those skilled in the art the tools to improve the invention by finding optimal settings with fewer expensive test case runs. This gives the user the advantage of reducing time and resource usage.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAY A MORRISON whose telephone number is (571)272-7112. The examiner can normally be reached on Monday - Friday, 8:00 am - 4:00 pm ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Trujillo K James, can be reached at telephone number (571)272-3677. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAY A MORRISON/Primary Examiner, Art Unit 2151