Sound and Precise Malware Analysis for Android via Pushdown Reachability and Entry-Point Saturation

We present Anadroid, a static malware analysis framework for Android apps. Anadroid exploits two techniques to soundly raise precision: (1) it uses a pushdown system to precisely model dynamically dispatched interprocedural and exception-driven control-flow; (2) it uses Entry-Point Saturation (EPS) to soundly approximate all possible interleavings of asynchronous entry points in Android applications. (It also integrates static taint-flow analysis and least permissions analysis to expand the class of malicious behaviors which it can catch.) Anadroid provides rich user interface support for human analysts which must ultimately rule on the "maliciousness" of a behavior. To demonstrate the effectiveness of Anadroid's malware analysis, we had teams of analysts analyze a challenge suite of 52 Android applications released as part of the Auto- mated Program Analysis for Cybersecurity (APAC) DARPA program. The first team analyzed the apps using a ver- sion of Anadroid that uses traditional (finite-state-machine-based) control-flow-analysis found in existing malware analysis tools; the second team analyzed the apps using a version of Anadroid that uses our enhanced pushdown-based control-flow-analysis. We measured machine analysis time, human analyst time, and their accuracy in flagging malicious applications. With pushdown analysis, we found statistically significant (p < 0.05) decreases in time: from 85 minutes per app to 35 minutes per app in human plus machine analysis time; and statistically significant (p < 0.05) increases in accuracy with the pushdown-driven analyzer: from 71% correct identification to 95% correct identification.Comment: Appears in 3rd Annual ACM CCS workshop on Security and Privacy in SmartPhones and Mobile Devices (SPSM'13), Berlin, Germany, 201

Introspective Pushdown Analysis of Higher-Order Programs

In the static analysis of functional programs, pushdown flow analysis and abstract garbage collection skirt just inside the boundaries of soundness and decidability. Alone, each method reduces analysis times and boosts precision by orders of magnitude. This work illuminates and conquers the theoretical challenges that stand in the way of combining the power of these techniques. The challenge in marrying these techniques is not subtle: computing the reachable control states of a pushdown system relies on limiting access during transition to the top of the stack; abstract garbage collection, on the other hand, needs full access to the entire stack to compute a root set, just as concrete collection does. \emph{Introspective} pushdown systems resolve this conflict. Introspective pushdown systems provide enough access to the stack to allow abstract garbage collection, but they remain restricted enough to compute control-state reachability, thereby enabling the sound and precise product of pushdown analysis and abstract garbage collection. Experiments reveal synergistic interplay between the techniques, and the fusion demonstrates "better-than-both-worlds" precision.Comment: Proceedings of the 17th ACM SIGPLAN International Conference on Functional Programming, 2012, AC

Pushdown Control-Flow Analysis of Higher-Order Programs

Context-free approaches to static analysis gain precision over classical approaches by perfectly matching returns to call sites---a property that eliminates spurious interprocedural paths. Vardoulakis and Shivers's recent formulation of CFA2 showed that it is possible (if expensive) to apply context-free methods to higher-order languages and gain the same boost in precision achieved over first-order programs. To this young body of work on context-free analysis of higher-order programs, we contribute a pushdown control-flow analysis framework, which we derive as an abstract interpretation of a CESK machine with an unbounded stack. One instantiation of this framework marks the first polyvariant pushdown analysis of higher-order programs; another marks the first polynomial-time analysis. In the end, we arrive at a framework for control-flow analysis that can efficiently compute pushdown generalizations of classical control-flow analyses.Comment: The 2010 Workshop on Scheme and Functional Programmin

Pushdown Control-Flow Analysis for Free

Traditional control-flow analysis (CFA) for higher-order languages, whether implemented by constraint-solving or abstract interpretation, introduces spurious connections between callers and callees. Two distinct invocations of a function will necessarily pollute one another's return-flow. Recently, three distinct approaches have been published which provide perfect call-stack precision in a computable manner: CFA2, PDCFA, and AAC. Unfortunately, CFA2 and PDCFA are difficult to implement and require significant engineering effort. Furthermore, all three are computationally expensive; for a monovariant analysis, CFA2 is in $O(2^n)$, PDCFA is in $O(n^6)$, and AAC is in $O(n^9 log n)$. In this paper, we describe a new technique that builds on these but is both straightforward to implement and computationally inexpensive. The crucial insight is an unusual state-dependent allocation strategy for the addresses of continuation. Our technique imposes only a constant-factor overhead on the underlying analysis and, with monovariance, costs only O(n3) in the worst case. This paper presents the intuitions behind this development, a proof of the precision of this analysis, and benchmarks demonstrating its efficacy.Comment: in Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 201

CFA2: a Context-Free Approach to Control-Flow Analysis

In a functional language, the dominant control-flow mechanism is function call and return. Most higher-order flow analyses, including k-CFA, do not handle call and return well: they remember only a bounded number of pending calls because they approximate programs with control-flow graphs. Call/return mismatch introduces precision-degrading spurious control-flow paths and increases the analysis time. We describe CFA2, the first flow analysis with precise call/return matching in the presence of higher-order functions and tail calls. We formulate CFA2 as an abstract interpretation of programs in continuation-passing style and describe a sound and complete summarization algorithm for our abstract semantics. A preliminary evaluation shows that CFA2 gives more accurate data-flow information than 0CFA and 1CFA.Comment: LMCS 7 (2:3) 201