1 Refining Buffer Overflow Detection via Demand-Driven Path-Sensitive Analysis Wei Le and Mary Lou Soffa University of Virginia sotesty.cs.virginia.edu

2 Buffer overflow: 20 years since Morris Worm, still the most common exploit Challenge: eliminate exploitable buffer overflows – Detect where buffer overflow can occur – Determine cause and remove it 2 Motivation

3 Detection Precision: false positives Report for errors does not provide much information for diagnosis – report an overflow point in the program Not fully automatic: manual annotation 3 Problems of Static Approaches

4 Goal: automatically identify paths on which a buffer overflow can occur and report the path segment that causes the overflow Challenge: huge number of paths Approach: – interprocedual path-sensitive for precision and help diagnosis – demand-driven for scalability 4 Our Goals and Approaches

5 Infeasible: no input can exercise the path Safe: no input can overflow the buffer Vulnerable: users can write any content to the buffer Overflow-user-independent: the buffer content is statically determinable Don’t-know: the buffer status cannot be judged statically 5 Five Types of Paths

6 n rootd = 1rootd = 0 strlen(wbuf)+rootd+1+ strlen(resolved) > LEN rootd == 0 strcat(resolved, “/”) strcat(resolved, wbuf) exit y n y yn Safe Overflow Infeasible wu-ftpd realpath.c An Example \0 wbuf resolved \0 LEN = 6

7 n rootd = 1rootd = 0 strlen(wbuf)+rootd+1+ strlen(resolved) > LEN rootd == 0 strcat(resolved, “/”) strcat(resolved, wbuf) exit y n y yn Demand-Driven Analysis …… char resolved [LEN ] Q 1 (s+1<l, f) Q1Q1 Q 052 (LEN-1<l, f) Q 05 (LEN-1-rootd<l, f) Q 1 5 (LEN-rootd<l, f) Solved Q0Q0 Infeasible Q 0 (s<l, f) s: strlen(resolved)+strlen(wbuf) l: sizeof(resolved) f: wbuf Q 053 (LEN-1<l, f) Q 15 3 (LEN<l, f)

8 PVS ( potentially vulnerable statement) strcpy(a,b) Query sizeof(a) > strlen(b), flag Information for Updating Queries char a[9] Propagation Rules interprocedural, loop, join point, infeasible Resolving the Query false, flag = user input 8 The Demand-Driven Model

9 Raise Query Yes Propagate Query Update Query Resolve Query Propagate Results Label Paths No Feasibility Detection Infeasible Paths Node Information PVS Program Overflow Properties 9 Approach

10 Purpose − Existence of the 5 types of paths − Benefit of demand-driven analysis Implementation: Microsoft Phoenix APIs [phoenix] Benchmarks − 9 programs, size K LOC − the BugBench [06lu] and Buffer Overflow Benchmark [03Zitser] 10 Experiments

11 Experimental Results BenchmarkPath Types VulCNSTUnKSafe polymorph ncompress man-1.5h gzip bc-1.060>50,0000>30,000 squid wu-ftp ,624 sendmail BIND0020

12 All defined types of paths exist Problematic paths manifest certain complexity Memory usage: 9-65MB Time cost: s Experimental Results

13 Entry PVS User Scenario

14 Entry PVS Vulnerable Overflow User Independent User Scenario

15 Entry PVS Vulnerable Overflow User Independent User Scenario

16 Entry PVS Root Cause Vulnerable Overflow User Independent User Scenario BenchmarkAverage Path Size #P#B polymorph ncompress man-1.5h gzip squid wu-ftp sendmail BIND

17 Static Detection for Buffer Overflow ARCHER [03xie] BOON [00wagner] ESPx [06hackett] Prefast [ms] Prefix [00bush] Splint [96evans] Path-Sensitive Analysis for Defects ARCHER [03xie] ESPx [06hackett] ESP [02das] IPSSA [03livshits] MOPS [02check] Prefix [00bush] Demand-Driven Approach − A general framework [96Duesterwald] − Application for dataflow computation [96Duesterwald], infeasible detection [97bodik], memory leak [06Orlovich], postmortem analysis [04Manevich] Related Work

18 A categorization of five types of paths for buffer overflow An interprocedual demand-driven path- sensitive diagnosis tool for identifying the type of paths through a potential overflow Experimental results that demonstrate the path types existing in real program 18 Conclusions

19 Thank you and Questions?