R&D Institute GMO pepabo, Inc. / 2. KRPEO / 3. SAKURA Research Center, SAKURA Internet Inc. 2019.07.15 The 9th IEEE International Workshop on Network Technologies for Security, Administration and Protection Automatic Whitelist Generation for SQL Queries Using Web Application Tests 1 1,2 3
severe vulnerability issue for web applications • e.g: SQL injection, OS command injection and so on • The attacks are caused by executing illegal queries to the database • The Illegal query is an unexpected query for web application developers • To prevent the attacks, illegal queries must be detected before they are executed in the database 4 Background
list and detect queries which matched the list • Whitelist method • define normal query pattern in a list and detect queries which doesn’t matched the list 5 Illegal query detection method Using only the blacklist can't detect unknown illegal query → Using the whitelist is required to detect Illegal query which has unknown patterns
by the web application • The large-scale web application issue enormous queries → Registering all queries in whitelist is difficult • Queries issued by the web application change with updating of the web application → Developers need to update the whitelist 6 Whitelist creation and its issue 5IFNFUIPEJNQPTFTBOJNQSBDUJDBMCVSEFOPOEFWFMPQFST
a whitelist without much effort • and detect illegal queries using it → The whitelist should be automatically generated according to changes of queries issued by a web application 7 Purpose of our research
while the web application is running • The method can create a whitelist independently of the web application implementation • Programming language, Framework 9 Generating a whitelist using issued queries %BUBCBTF 8FCBQQMJDBUJPO 2VFSZ 8IJUFMJTU %VSJOHXFCBQQMJDBUJPOJTSVOOJOH )551SFRVFTU
the web application • need a period to collect queries during running the web application • The period which can’t detect illegal queries occurs frequently • Queries change frequently because web services are frequently updated 10 5IFXIJUFMJTUHFOFSBUJPOTIPVMECFEPOFCFGPSFSVOOJOHUIFXFCBQQMJDBUJPO Generating a whitelist using issued queries
of issuing the query in the web application source code • The method can generate a whitelist before web application running by using the source code as input 11 Generating a whitelist using static analysis "OBMZ[FS 4PVSDFDPEF 8IJUFMJTU #FGPSFXFCBQQMJDBUJPOSVOT
application with different implementations • Source code analysis depends on the implementation of the web application • If web service is constructed various languages and frameworks, implementing an analyzer for each application impose high workload 12 8IJUFMJTUHFOFSBUJPOTIPVMECFQFSGPSNFEJOEFQFOEFOUMZPGUIFXFC BQQMJDBUJPOJNQMFNFOUBUJPO Generating a whitelist using static analysis
web application • to detect illegal queries immediately after running the web application 2. The whitelist generation should be performed independently of the web application implementation • to reduce the workload to implement for each web application 14 Requirements of proposed method
• The whitelist generation incorporates into the development process using an automatic test • Database proxy collects the queries issued during testing 15 Proposed method
$POWFSUJOUPRVFSZTUSVDUVSFUIBUSFQMBDF MJUFSBMTPGUIFRVFSZXJUIQMBDFIPMEFST 3FHJTUFSUIFRVFSZTUSVDUVSFXJUIBXIJUFMJTU 2VFSZ 2VFSZ 4&-&$5 '30.VTFST8)&3&JE 4&-&$5 '30.VTFST8)&3&JE &YBNQMFPGRVFSZTUSVDUVSF Collecting queries using the database proxy realize whitelist generation independent of the web application implementation
Detection using the whitelist 3FDFJWFRVFSZBOEDPOWFSUUIFRVFSZJOUPRVFSZTUSVDUVSF $IFDLXIFUIFSUIFRVFSZTUSVDUVSFJTPOUIFXIJUFMJTU *GUIFRVFSZTUSVDUVSFJTOPUPOUIFXIJUFMJTU UIFRVFSZJTEFUFDUFEBTBOJMMFHBMRVFSZ
means that normal query is determined as illegal • The normal query is an expected query issued by a web application receiving user input. • False negative means that illegal query is determined as normal • The illegal query is an unexpected query issued by attacks such as web application vulnerability attacks. 21 Indicator of detection accuracy
affect the detection accuracy 22 Queries that cause false positive / negative #2VFSJFTEVSJOHSVOOJOH "2VFSJFTEVSJOHUFTUJOH • The reason for queries issued only during testing • Registering test data • Deleting all test data • The reason for queries issued only during running • Test cases are a subset of usage during running 5IFDBVTFPGGBMTFOFHBUJWF 5IFDBVTFPGGBMTFQPTJUJWF
production • We obtained query log in production for 3 days of holidays • to remove the changes of queries issued by the web application • We ran tests of the web application that was running during the query log period and obtained the queries issued during testing 23 Experiment in production
the normal process • These queries are not issued in the test by lacking test case or skipping access to the database • Complementing queries lacking in the whitelist is necessary • Applying the proposed method only to the database table with confidential information is important • Reducing false positive by reducing the queries of the detection target 25 Consideration of false positive cases #2VFSZTUSVDUVSFTJTTVFEJOQSPEVDUJPO "2VFSZTUSVDUVSFTJTTVFEJOUFTU
query 1. Queries issued not issued during the query log period 2. Queries issued only in the test • Include a query that deletes all confidential data in the database table • The detection combined whitelist and blacklist is necessary • Registering queries handling a lot of data into the blacklist • e.g: query deleting all data in the database table 26 Consideration of false negative cases
that • can’t detect illegal queries immediately after running the web application • can’t be commonly used in multiple web application with different implementations • The proposed method solves these issues • by incorporating whitelist generation into the development process • by collecting queries during testing using the database proxy 28 Conclusion
false positive and false negative • Regarding false positive cases • Complementing queries lacking in the whitelist • Applying the proposed method only to the table with confidential information • Regarding false negative cases • Detection combining whitelist and blacklist for illegal queries 29 Conclusion
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