AppSecAssignment1.1
1.
Programming – Language C
2.
Program needs to be
executable as per document in virtual machine
3.
Programming
4.
Write up
5.
Deadline: 09/18/2022
6.
Reference:
https://github.com/kcg295/AppSecAssignment1.1
7.
See attached file for further
information
AppSecAssignment1.1 1. Programming – Language C 2. Program needs to be executable as per document in virtual machine 3. Programming 4. Write up 5. Deadline: 09/18/2022 6. Reference: https://github.com/kcg295/AppSecAssignment1.1 7. See attached file for further information Programming Homework 1: Beware of Geeks Bearing Gift Cards Introduction You've been handed the unpleasant task of performing an audit of code written by your company's least-favorite contractor, Shoddycorp's Cut-Rate Contracting. The program is designed to read in gift card files in a legacy binary file format, and then display them in either a simple text output format, or in JSON format. Unfortunately, Shoddycorp isn't returning your calls, so you'll have to make do with the comments in the file and your own testing. Justin Cappos (JAC) and Brendan Dolan-Gavitt (BDG) have read through the code already. It's a mess. We've tried to annotate a few places that look suspicious, but there's no doubt that there are many bugs lurking in this code. Make no mistake, this is not an example of C code that you want to imitate. Part 1: Setting up Your Environment In order to complete this assignment, you are required to use the git VCS. Before beginning to write your code, you should first install git and set up a git repository to store your code in. The git binaries can be installed by your local package manager or at https://git-scm.com/downloads. For a cheat-sheet of git commands, please see https://github.com/nyutandononline/CLI-Cheat-Sheet/blob/master/git-commands.md. Although we will not be checking your commit messages or git log, it is recommended that you write descriptive commit messages so that the evolution of your repository is easy to understand. For a guide to writing good commit messages, please read https://chris.beams.io/posts/git-commit/ and https://git.kernel.org/pub/scm/git/git.git/tree/Documentation/SubmittingPatches#n104 (lines 104 – 160). After git is installed, you will want to configure your git user to sign your commits. This can be done by following the guide at https://git-scm.com/book/en/v2/Git-Tools-Signing-Your-Work. In order for us to be able to verify that you successfully signed your commits, please upload an ASCII armored copy of your signing key in the root directory of your repository and name it signing_key.pub. After installing and configuring git, you should then create a GitHub account at https://github.com, and add an ssh key using the guide found at https://help.github.com/en/articles/adding-a-new-ssh-key-to-your-github-account. After creating a GitHub account, you are ready to create a git repository for the project you will be working on. The recommended way to do this is to create a repository using the GitHub Web interface. This is recommended because it can automatically generate important files for you, such as the license for your project and the gitignore file to avoid unintentionally tracking unnecessary files. After you create the repository on GitHub, you can clone it to your local machine using the following command. $ git clone
[email protected]:
/.git Be sure to make the repository private. The next step is to set up GitHub Actions CI. To do this,you should create a .github/workflows directory in the root of your repository. After that, create a workflow.yaml file in that directory, and set it up to work with GitHub Actions. For information on how to set up GitHub Actions, you can read the GitHub Actions tutorial (https://docs.github.com/en/actions/quickstart). Finally, you are required to set up GitHub Actions. This will take the form of configurations in the workflow YAML file mentioned earlier in the .github/workflows directory. Information on how to configure GitHub Actions using this YAML file can be found on the GitHub Actions Introduction (https://docs.github.com/en/actions/learn-github-actions/introduction-to-github-actions) In Part 2 of this project you will be expanding the functionality of GitHub Actions by including tests. Part 2: Auditing and Test Cases Start off by copying the files from this repository into your own, and add them to git. The files you need are: examplefile.gft giftcardexamplewriter.c giftcard.h giftcardreader.c Makefile Read through the giftcardreader.c program (and its accompanying header, giftcard.h) to get a feel for it. You should also try building and running it with the included examplefile.gft file, to see what its normal output is. You may find it helpful to use a debugger like gdb to step through the program as it executes, to get an understanding of its normal flow of control. For this part, your job will be to find some flaws in the program, and then create test cases (i.e., binary gift cards) that expose flaws in the program. You should write: 1. Two test cases, crash1.gft and crash2.gft, that cause the program to crash; each crash should have a different root cause. 2. One test case, hang.gft, that causes the program to loop infinitely. (Hint: you may want to examine the "program" record type to find a bug that causes the program to loop infinitely.) 3. A markdown file, writeup.md with a heading called "bugs" explaining the bug triggered by each of your three test cases. To create your own test files, you may want to look at giftcardexamplewriter.c. Although it is no better written than giftcardreader.c, it should help you understand the basics of the file format and how to produce gift card files. Finally, fix the bugs that are triggered by your test cases, and verify that the program no longer crashes / hangs on your test cases. Above each bug that you fix, please put a comment that states what bug it fixes. For example, if you fix crash1 on line 22, on line 21 you should put "//crash1". This is necessary to ensure that your code fixes are spotted by our autograder! To make sure that these bugs don't come up again as the code evolves, have GitHub Actions automatically build and run the program on your test suite. Part 3: Fuzzing and Coverage As discussed in class, an important part of understanding how well your test suite exercises your program's behaviors is coverage. To start off, measure the coverage that your program achieves with the test cases you created in Part 2. To do this, you should build giftcardreader with the --coverage option to gcc, run your test suite, and then produce a coverage report using lcov (details on how to do this can be found in the lecture slides). You should notice that there are portions of the program that are uncovered (i.e., the code was not executed while processing your test suite). Pick two lines of code from the program that are currently not covered and create test cases that cover them. An easy and effective way of finding crashes and getting higher coverage in a program is to fuzz it with a fuzzer like AFL. Fuzz the program using AFL, following the quick-start instructions. To make the fuzzing more effective, you should provide AFL with all of the test files you have created in its input directory. Let the fuzzer run for at least two hours, and then examine the test cases (in the queue directory) and crashes/hangs (in the crashes and hangs directories). Add the generated test cases (but not the crashes or hangs) to your test suite, and produce a new coverage report. You should see that the tests generated by the fuzzer reach more parts of the gift card program. Finally, pick two crashes/hangs and fix the bugs in the program that cause them. Then, re-run the program on all the crashes and hangs found by AFL. You should find that not all of the crashes found by AFL originally crash the program now---although AFL tries its best to figure out which crashes are caused by unique bugs, if often overcounts. Add the generated tests to your repository and have GitHub Actions run them. Note that depending on how long you ran the fuzzer and how fast your machine is, there may be a lot of redundant test cases! To keep only the ones that exercise new behavior in your program, you can use the afl-tmin tool. To complete the assignment, commit your updated code, your handwritten tests, the fuzzer-generated tests, and a brief writeup explaining the bugs you found and fixed in this part. This writeup should be in the writeup.md file under a header named "testing". Grading Total points: 100 Part 1 is worth 20 points: · 10 points for signed commits · 10 points for GitHub Actions configuration Part 2 is worth 40 points: · 10 points for your test cases and fixes · 10 points for GitHub Actions regression testing · 20 points for the bug writeup Part 3 is worth 40 points: · 10 points for handwritten tests · 10 points for fuzzer-generated tests · 10 points for your code fixes · 10 points for writeup What to Submit On NYU Classes, submit a link to your GitHub repository. The repository should be private, and you should add the instructor/TA's GitHub account as a contributor to give them access for grading. For this section, your instructors are: Kevin Gallagher, GitHub ID kcg295 and Dean Christakos, GitHub ID to be added. For this section, your TAs are Gaurav Chauhan, GitHub ID to be added, Sarthak Bohra, GitHub ID to be added, and more TAs to be added. The repository should contain: · Part 1 · Your GitHub Actions Workflow file · At least one signed commit · Part 2 · A directory named tests that contains crash1.gft, crash2.gft, hang.gft. · A markdown writeup called writeup.md with a heading named bugs · An updated GitHub Actions Workflow file that runs your tests · A commit with the fixed version of the code (if you like, this commit can also contain the files mentioned above) · Part 3 · A directory named fuzz that contains cov1.gft, cov2.gft, fuzzer1.gft, fuzzer2.gft. · writeup.md with a section named "testing". · An updated GitHub Actions Workflow file that runs the new tests · A commit with the fixed version of the code (if you like, this commit can also contain the files mentioned above) Write Up Concluding Remarks Despite the fixes you've made, there are almost certainly still many bugs lurking in the program. Although it is possible to get to a secure program by repeatedly finding and fixing bugs (at least when the program is this small), it's a lot of work, and just because a fuzzer stops finding bugs doesn't mean that the program is bug-free! Realistically, this program is probably unsalvageable in its current state. It would be better in this case to rewrite it from scratch, either in C using a very defensive programming style, or in a safer language like Python or Rust. Once this assignment is complete, we will release a cleanly-written version of the program (written in C) that should be relatively bug-free [1]. You'll notice that it's a lot more verbose,