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FIT1093/2093 application Assignment
Creation date：2024-06-18 18:06:30
Belonging category：计算机computer science
Tag FIT1093
application

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FIT1093/2093 Assignment

Submission Guidelines & Tasks
Guidelines Details
• Deadline: Assignment 2 submission is due in Week 15 on 10 June 2024 at
11:55pm Melbourne, Australia time (CL Campus) and 10 June 2024 at 11:55pm
Malaysia time (MA Campus). This Task is an individual (not group) work and it
must be submitted by each student individually.
• Submission Platform: Electronic submission via the `Assignment 2 Submission’
link on the Moodle Assessments page (an Ed announcement will be sent once the
link is added).
• Required Files: Required VM files for the assignment will be available for
download via the Moodle Asg 3 Moodle Submission Link.
• Submission File Format: One PDF document for all 4 tasks.
• Submission Page Limit: The submitted PDF document must be at most 20
pages, excluding cover page and references. Any screenshots that cannot fit in
the main 20 pages can be placed in an Appendix (which does not count in the page
limit).
• Plagiarism: It is an academic requirement that your submitted work be original.
Zero marks will be awarded for the whole submission if there is any evidence of
copying, collaboration, pasting from web sites, or copying from textbooks.
• Use of Generative AI tools: ChatGPT or other AI tools may be used for study
purposes, to learn about your topic, and to develop your assignment. However,
similar to citation requirements for other references, you must include a clear
declaration of all generative AI tools used (e.g. ChatGPT, DALL-E, Grammarly,
voice-to-text), how and where you have used them. Please follow the Monash
guidelines on how to acknowledge the use of Generative AI.
Notes
● For each question, you need to answer both the computation result question
and the explanation questions about your working process such as the source
code or the commands you are using to solve the tasks.
● Note that if numbers in this assignment are specified in hexadecimal format,
your written answer and many software packages expect hexadecimal
numbers to be input a ‘0x’ prefix (e.g. ’0xa0b1c2d3’) for indicating the
hexadecimal format. For example, this prefix allows SageMath to interpret the
value in hex.
1
Overview of the assignment
The assignment is worth 30% of your total unit mark.
Your goal in this assignment is to do security/penetration testing of a mini web application to identify
web application and SQL injection vulnerabilities in it, using the techniques covered in our Web and
database security lectures. Then, the goal is to demonstrate how to exploit the vulnerabilities
discovered to break the app’s security. Finally, you will reflect on the invited lecture from Week 12 and
on applying your unit knowledge in a daily life situation.
In Task 1 of the assignment (weight: 10% of your unit mark), you will demonstrate your understanding
of XSS security vulnerabilities by testing the web application such vulnerabilities and assessing
whether any vulnerabilities you find can potentially be exploited by an attacker.
In Task 2 of the assignment (weight: 4% of your unit mark), you will demonstrate your understanding
of client-side penetration testing techniques to attempt to bypass the web application’s mechanism for
enforcing access control to private documents to authorised users.
Task 3 of the assignment (weight 6% of your unit mark) requires you to demonstrate your skills in
testing for SQL injection vulnerabilities in a part of the web application that makes queries to an SQL
database, and exploit any vulnerabilities you discover to breach gain unauthorised access to the
database.
Task 4 of the assignment (weight 10% of your unit mark) requires you to write your reflection of the
invited lecture in Week 12 and personal experience in relation to Cyber Security
2
Assessment Details
Task Rubric
Task 1 10%
■ Task A (3%): list of potential XSS vulnerability points (2%) and
explain the results (1%)
■ Task B (7%): for testing techniques (1%), tests results (2%) and
send out document cookie to attacker’s domain (1%)
Explain the vulnerability (2%) and mitigation (1%)
Task 2 4%
■ Testing(s) techniques (2%) and
■ exploit/vulnerabilities’ explanation (2%)
Task 3 6%
■ Task A (4%): for list of users testing (2%), results and
interpretation, for table and fields testing results and
interpretation) (2%)
■ Task B (2%): for modifying a non phone no. field testing(1%),
results and interpretation (1%)
Task 4 10%
● Reflection of Invited Lecture (5%)
● Reflection of personal cyber security experience (5%)
3
Assignment Details
You can download the Asg3 VM file from the link in the Moodle Asg3 Submission Page:
- for Windows or Mac devices with Intel CPUs (.ova file), or
- for Mac M1/M2 devices with VMWare Fusion player (.zip file), or
- for Mac M1/M2 devices with UTM player (.qcow2 file), see Ed #893.
Once you run the VM, log in with the following credential:
VM login name: student
VM password: student
Your task is to perform the following security tests on this web application. You should perform these
tests using the Firefox or burpsuite built-in web browser installed in your VM, and the burpsuite tool
installed in the given VM.
Task 1 (10% of unit marks): Committee Member Security Test
Visit the homepage for the web application at the URL (http://alicefansclub.org/index.php) using your
web browser. If all is well, the browser should display a page that looks as in Fig. 1.
Fig.1 Login Pag
4
This web app allows committee members of Alice Fans Club to access their personal documents.
In this part, your aim is to do security testing of the committee member part of the web application,
from the point of view of an attacker trying to reveal the secret committee information. To help you with
this, you are given the login credentials of one of the registered committee members (however, note
that an outsider attacker may or may not know credentials other than provided):
Username: Alice
Password: alice
City: Sydney
After clicking the “submit” button with the above credential, the browser should display a welcome
page, as shown in Fig. 2.
Fig. 2. Welcome page
Then, after entering the event details e.g May 2024 and Sydney into the boxes and then clicking the
“submit” button, you should see the show poster as shown in Fig. 3.
5
Fig. 3. Secret report of observation.
Complete the following tasks:
● Task 1A (3 mark) Based on the application behavior for login and welcome pages above:
o Based on the behaviour of the web application pages above with an honest user, list
potential points on the home and greeting pages where a reflected XSS input
injection vulnerability may potentially exist. (No actual XSS attack is required in this
task).
o Explain why the points you listed are potential XSS vulnerability points.
● Task 1B (7 mark) Experiment with the home page login and welcome and member report
pages in Figs. 1-3, and examine the behavior of these pages to different inputs. In particular:
o For each of the potential XSS vulnerability points listed in Task A.1, perform tests to
see if XSS vulnerabilities actually exist at these points.
o Assume you set up a web application server, craft a malicious script that could allow the
attacker to receive the target user’s session cookie by launching an XSS attack on one
of the chosen vulnerability points.
o In the report,
▪ Describe and explain your testing approach
▪ Draw a table of test results and your interpretation/conclusions on why or why
not such XSS vulnerability exists (note: you only need to test if script injection is
possible, no social engineering considerations are required).
▪ Screenshot of script and the feasibility of receiving cookies at the attacker’s
application server. (note: you only need to show the script and evidence for its
execution to steal the cookie, no social engineering attack feasibility/demo is
required)
▪ Explain how to mitigate the vulnerabilities.
6
Task 2 (4% of unit marks): Personal Information Security Test
In this part, your aim is to do security testing of the fans’ personal information part of the web app. For
this, you are given one of fans’ name and password, namely:
Member Name: Grace
Member ID Number: 3
Member password: Ro4mvSemq45xfepvaEr24
Use Grace’s member ID number and Member password to log in to the Personal Private Information
login page shown in Fig. 4.
Fig. 4. Personal Private Information login page.
Complete the following tasks:
Grace has two private documents stored in his account with document IDs 1 and 2. Your goal in this
task is to test the application against attacks by Grace (Member ID: 3) who is curious to learn about
another member Camy’s (Member ID: 4) private information.
o Can Grace gain unauthorised access to Camy’s personal private data?
▪ If you think it is possible, explain the vulnerability you found and how Grace can
exploit it, and show any private data of Camy you managed to expose by the
attack.
▪ If you think it is not possible, explain why.
Case category
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 EARN 5 FE 825 IERG 5130 STAT 8178 EE161 ADS2 G54FUZ CS326 113B ECN 226 QBUS6860 ELEC3202 COMP9334 MGT11B MET CS 777 STA238 00099F Python SMM306 CMT206 EC116 SP MAST90084 CS480/680 BCPM0091 CMPT 300 ECON2209 FY20 STAT 432 CVEN9625 MATH1712 CMP9771M CMP3750M CIS 325 AI506 MAT344H1S MGT7180 PSTAT 160B CSYS5010 1D STAT 453/558 ME152B STA304H1F CSCI-128 ME428 CO3002 FINE 7640 COMP3234 ECSE 223 EE497 – 3D MATH5905 ECS648U ENG5009 MATH10242 EC665 A CPI221 ISOM5220 MACE40402 MGT B456F COMP9315 AFM 113 STAT 778 CS 564 MA231 CS 230 CS 124 COMP5511 CSC317 ITEC1010 ELEC207 INFT 3019 7CCMFM06 EE 161 5G ECLT5810 MATH 7349 CS526 O2 COMP90054 ELE00063M ACCT5034 ARC1015 CSCI 40 CSCI E40 FIN 524B CS 462 389COM CMT309 MFIN703 COMP4250 STA304 STA304H1S STA 1003 FIN 448 BUFN 732 CS520 CVEN3701 ECMT6006 PHAS0100 CSIT314 MDIA 5028 CSCI 2134 MAT 451 CMPT 459 STAT 457 INFO20003 COMP4141 IELE8066 F540 ECM9 CSE 6321 FIN 430 MATH3911 BFC5916 COMP1011 EEE 6209 STATS 240 CW3 COMP206 COMP1003 4331W ISE 530 CMPT 295 MATH 239 QF5203 INFR08010 IT114105 FIT2093 ECON3124 ECON1195 MATH 337 STAT 3006 COMP202 COMP3130 MATH3609 COMP 250 CS6140 IEEE ELE00041I FIN40090 CIV 5899 MATH3066 IGNMENT MATH 2009 STAT3405 HIST 101 MATH 3281 CEGE0042 ICT532 LAB 7 LAB 5 MCO455 CSIT214 Q4 IFB104 A1 ECO220Y5Y DA5020 CMPSC473 FIN9007 DSCI553 MSCI534 COMP3308 CSE-112 CMPT 310 EE104 F 2C P20 ALY2010 BUSM060 STA258 ECO00030M R BIOSTAT 274 COS6012-B FIT3155 CMPUT 340 EC421 INFS4205 ECOM135 NATS 1740 COMP809 MBE 6005 STA465 CSSE2310 CIVL2700 DATA4700 CMPSC 473 ISE 529 CS5044 MAST30020 COMP2207 ENGG1001 COMP0046 FIT3165 STAT GR5241 MECH0007 vATHK1001 ANALYTIC ATHK1001 MATH352001 HW3 S1 BMAN 24662 COMP 636 Stat-461 STAT 302 STAT 2132 STAR534 ENG4137 CMP3752M CS3103 BISM3222 STA 135 ME155A IIMT3601 ECON3371 ECON 3371 HW4 FINA 5840 DT211C CTEC3902 MAT005 MATH2148 S261F Econ 332 MATH3734 MIS41270 7CCMFM13 SYST 664 CIS434 CENG10014 MT4111 MT4527 ECMM424 CMT219 Math 136 MATH 3120 COMP10002 MAST20009 MATH0058 BEEM117 ISYE 6420 MGMTMFE 405 25579 1ECE 273 M122 COMP4434 1ELEC ELEC5620M STAT0010 BFF2401 MXB361 MATH3811 CS330 CMT307 FIT1033 CptS 583 UP 431 MATH6005 AF5343 CS2435 ECOM30002 ES50061 CS 2506 ECMT6002 CODE 00099F MT4539 ESSAY ICM317 MATH1231 MFIT5010 BMA547 MATH334 CIVL2201 MATH39032 T-04 CIVE97119 EMESTER CAB302 CAB301 59PM STAT802 ISYS3412 RM3 COSC 2123 AcF 311 MATH2022 1FINAL 4CCS1PHC ICM 142 ENVS3023 Math 4023 I1 ACSE8 FIN B385F CS-275 STA 4109-01 A31021 EE140 MT1 EE124 ECO-6004B Inf2-IADS CS126 IS2184 UL18 MATH5092 ECOM009 COMP 6211 ELEC202 MKT3019 IAB230 FIT5046 584-S21 COMP3210 CO250 A29401 MATH 136 MGT6174 ECMT6007 DATA2001 MAT 443 MATH10222 PHDE0071 ELE00123M COSC1295 MAT00045H MATH32032 1004GRC MAS223 COMP10001 DATA3404 CIVL2110 STAT2008 FNCE10002 EEE6431 COM6515 COMP9120 NBS8185 ECTE942 ECON 405 MATH314301 STAT 2011 COMPSCI 350 COMP20007 CMPSC-132 ECON5002 STA 35 MTH6108 FIT5147 MTH6150 100C FINA 5260 DESC9115 ECON4998 NBS8257 GMM ECON 6070 BSA2 ECE599 STATS 102B STA120 INFS601 BFC3241 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CIVL2010 ECMT2150 CS 333 CP1406 KIT308 Economics 701 ECON3740 ECE 5759 BFC3340 FINC2012 COMP4500 MATH3871 FIT3080 18-819C Economic ECO202Y5Y PHY100 FINC-780 Econ 100B EC602 IE582 EE450 COMP9517 WRDS 150B ECON 570 LECTURE 2 ECA5101 ECE 4420 ADAD9311 FIT3031 CS 544 MF 703 CS 6140 KIT501 ENGSCI 344 CSC171 IE 332 FINM8007 21S2 COSC 1114 FE545 E471 SIT102 CSC108 MAT301 IAE 101 COP3503 STAT2004 EC 303 CS1026 STAT1203 MATH3171 ISOM5160 IFN657 FIT2014 ACCT2102 DSCI550 STATS 330 ELEC421 COMP3670 QBUS6840 MEES:698B MAST30027 MIET1077 Economics IFT 6758 FIT5122 BUSN5101 CptS 111 HRMT5502 Math2018 PP 312 INFS3200 CZ3005 CSSE1001 SENG 2011 MKTG 553Q BUFN 640 COMP507 ETF5952 DATA 311 ECE4043 BANK3011 finance M3H623544 HW1 INFS 7410 AI6103 STAT3888 INFS3208 ACCT7103 ECOS3013 PSYCH 20B F79MA STAT3006 ENGG952 2X MGSC 7000 ECE4132 MSF 526 MATH 3033 CDS 511 EEEE4120 EEET2465 ECA5103 MATH2070 ELEC3104 BU51019 EEE8147 ENGR20003 COSC 1107 ETF3200 FNCE 435 MSFI 435 ISyE6420 GENG4405 HW ETC5523 IE 7315 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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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