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SATE 2010 Background

SATE 2010 Background. Vadim Okun, NIST vadim.okun@nist.gov October 1, 2010 The SAMATE Project http://samate.nist.gov/. Cautions on Using SATE Data. Our analysis procedure has limitations

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SATE 2010 Background

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  1. SATE 2010 Background Vadim Okun, NIST vadim.okun@nist.gov October 1, 2010 The SAMATE Project http://samate.nist.gov/

  2. Cautions on Using SATE Data • Our analysis procedure has limitations • In practice, users write special rules, suppress false positives, and write code in certain ways to minimize tool warnings. • There are many other factors that we did not consider: user interface, integration, etc. • So do NOT use our analysis to rate/choose tools

  3. Overview Tools that work on source code Security? Quality? Insignificant? False? ? Program CVE entries Tool C Tool B X Tool A X Buf Leak Race … X X Human findings X

  4. SATE 2010 timeline • Choose test programs (2 C, 1 C++, 2 Java). Provide them to tool makers (28 June) • Teams run their tools, return reports (30 July) • Analyze the tool reports (22 Sept) • Report at the workshop (1 Oct) • Teams submit a research paper (Dec) • Publish data (between Feb and May 2011)

  5. Participating teams • Armorize CodeSecure • Concordia University Marfcat • Coverity Static Analysis for C/C++ • Cppcheck • Grammatech CodeSonar • LDRA Testbed • Red Lizard Software Goanna • Seoul National University Sparrow • SofCheck Inspector • Veracode • a service company

  6. Test cases • Dovecot: secure IMAP and POP3 server – C • Pebble: weblog server – Java • Wireshark - C • Google Chrome – C++ • Apache Tomcat - Java • All are open source programs • All have aspects relevant to security • From 30k LoC (Pebble) to 4.7M LoC (Chrome) CVE-based pairs (vulnerable and fixed)

  7. Tool reports • Teams converted reports to SATE format • Several teams also provided original reports • Described environment in which they ran tool • Some teams tuned their tools • Several teams provided analysis of their tool warnings Original tool formats XML HTML DB … SATE format

  8. Analysis procedure 3 Selection Methods Select randomly Tool warnings ~60K warnings Analyze for correctness and associate Related to human findings Selected warnings Related to CVEs Analyze the data

  9. Method 1 – Warning SelectionFor Dovecot and Pebble only • We assigned severity if a tool did not • Mostly avoid warnings with severity 5 (lowest) • Statistically select from each warning class • Select more warnings from higher severities • Select 30 warnings from each of 10 tool reports • 1 report had only 6 warnings • Did not analyze Marfcat warnings • Total is 276

  10. Method 2 – Human findingsFor Dovecot and Pebble only • Security experts analyze test cases • A small number of findings • Root cause, with an example trace • Find related warnings from tools • Goal: focus our analysis on weaknesses found most important by security experts

  11. Method 3 - CVEsFor Wireshark, Chrome, and Tomcat • Identify the CVEs • Locations in code • Find related warnings from tools • Goal: focus our analysis on real-life exploitable vulnerabilities

  12. Correctness categories • True security weakness • True quality weakness • True but insignificant weakness • Weakness status unknown • Not a weakness

  13. Differences from SATE 2009 • Add CVE-selected test cases • Include a C++ test case • Larger test cases: Chrome - 4.7 MLOC • More correctness categories (true quality) • More detailed guidelines for analysis • Still, much can be improved…

  14. Thanks • Romain Gaucher, Ram Sugasi • Aurelien Delaitre, Sue Wang, Paul Black, Charline Cleraux, and other SAMATE team members • Most of all, the participating teams!

  15. Questions • What weaknesses exist in real programs? • What do tools report for real programs? • Do tools find important weaknesses? • Focus on tools that work on source code • Defects that may affect security • Goal is NOT too choose the “best” tools • This is the 3rd SATE (1st in 2008)

  16. SATE goals • To enable empirical research based on large test sets • To encourage improvement and adoption of tools • NOT to choose the “best” tools

  17. SATE common tool output format optional <weakness id=“23”> <name cweid=“79”>SQL Injection</name> <location id=“1” path=“dir/f.c” line=“71”/> … <grade severity=“2” probability=“0.5”/> <output> Query is constructed with user supplied input … </output> … </weakness> one or more traces that it is true 1 to 5, with 1 – the highest …and other annotation

  18. Lessons learned • Guidelines for analysis often ambiguous – need to be refined even more • Our analysis has inconsistencies and lapses • Careful analysis takes longer than expected • We do not know the code well • Tool interface is important to understand a weakness

  19. Analysis procedure • We cannot know all weaknesses in the test cases • Impractical to analyze all tool warnings So analyze the following: • Method 1. A subset of warnings from each tool report • Method 2. Tool warnings related to manually identified weaknesses

  20. SATE tool output format • Common format in XML • For each weakness • One or more trace - locations - line number and pathname • Name of weakness and (optional) CWE id • Severity: 1 to 5 (ordinal scale), with 1 – the highest • Probability that the problem is true positive • Original message from the tool • And other annotation

  21. Our analysis • Correctness of warning • Associate warnings that refer to the same (or similar) weakness

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