U.S. patent application number 14/460636 was filed with the patent office on 2016-10-13 for software vulnerabilities detection system and methods.
The applicant listed for this patent is Securisea, Inc.. Invention is credited to Joshua M. Daymont.
Application Number | 20160300063 14/460636 |
Document ID | / |
Family ID | 56939632 |
Filed Date | 2016-10-13 |
United States Patent
Application |
20160300063 |
Kind Code |
A1 |
Daymont; Joshua M. |
October 13, 2016 |
SOFTWARE VULNERABILITIES DETECTION SYSTEM AND METHODS
Abstract
This invention teaches a system and methods of detecting
software vulnerabilities in a computer program by analyzing the
compiled code and optionally the source code of the computer
program. The invention models compiled software to examine both
control flow and dataflow properties of the target program. A
comprehensive instruction model is used for each instruction of the
compiled code, and is complemented by a control flow graph that
includes all potential control flow paths of the instruction. A
data flow model is used to record the flow of unsafe data during
the execution of the program. The system analyzes the data flow
model and creates a security finding corresponding to each
instruction that calls an unsafe function on unsafe data. These
security findings are aggregated in a security report along with
the corresponding debug information, any ancillary information,
remediation recommendations and the optional source code
information for each instruction that triggered the security
finding.
Inventors: |
Daymont; Joshua M.; (San
Francisco, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Securisea, Inc. |
Atlanta |
GA |
US |
|
|
Family ID: |
56939632 |
Appl. No.: |
14/460636 |
Filed: |
August 15, 2014 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 21/566 20130101;
G06F 21/577 20130101; G06F 2221/033 20130101; G06F 11/3608
20130101; G06F 11/3668 20130101 |
International
Class: |
G06F 21/56 20060101
G06F021/56; G06F 11/36 20060101 G06F011/36 |
Goverment Interests
GOVERNMENT LICENSE RIGHTS
[0001] This invention was made with government support under the
CyberFastTrack program documented in DARPA PA-11-53 dated Jan. 31
2013, awarded by Defense Advanced Research Projects Agency (DARPA).
Claims
1. A software vulnerabilities detection system comprising: a)
compiled code and optionally source code that resulted in said
compiled code; b) an instruction model for each instruction of said
compiled code comprising location, debug information, instruction
type, operands, existing memory state requirements, bytecode
metadata, potential security attributes, basic block membership,
function/method membership if applicable and class membership of
each said instruction; c) a control flow graph for each said
instruction comprising all potential control flow paths, and a
bidirectional list of predecessor instructions for each said
instruction; d) a data flow model comprising recorded flow of
unsafe data as observed during the execution of said compiled code;
e) means for analyzing said instruction model, said control flow
graph and said data flow model to create a security finding for
each said instruction that calls an unsafe function on said unsafe
data; and f) a security report comprising each said security
finding with corresponding said debug information and said source
code information if available.
2. The software vulnerabilities detection system of claim 1 wherein
said compiled code is instrumented.
3. The software vulnerabilities detection system of claim 2 wherein
said instrumentation is done at random and critical control flow
points of said compiled code.
4. The software vulnerabilities detection system of claim 1 wherein
said instruction model further comprises placeholders for
additional attributes, including pointer aliasing information and
unsafe dataflow information.
5. The software vulnerabilities detection system of claim 4 wherein
said pointer aliasing information comprises aliasing maps to
determine which pointers may represent the same value given a
plurality of control flows of each said instruction.
6. The software vulnerabilities detection system of claim 1 wherein
said instruction model further comprises attributes deduced from
other attributes, including values for memory, register and
variable type of each said instruction.
7. The software vulnerabilities detection system of claim 1 further
comprising a data flow file recording flow of unsafe data as it
flows during the execution of said compiled code.
8. The software vulnerabilities detection system of claim 1 further
comprising an analyzer module.
9. The software vulnerabilities detection system of claim 1 further
comprising a set of concurrent worker threads, each thread
processing an instruction from said compiled code where an external
input is supplied.
10. The software vulnerabilities detection system of claim 9
wherein said concurrent worker threads are executed across one or
more selections from the group consisting of CPU, processor, core,
computing machine and node.
11. The software vulnerabilities detection system of claim 1
wherein said security report further comprises an execution trace
of said unsafe data corresponding to each said security finding,
said execution trace comprising information from the origin to the
termination of said unsafe data, and the associated line numbers
from said source code information.
12. The software vulnerabilities detection system of claim 1
wherein said security report further comprises a risk rating, a
human-readable description and optionally one or more remediation
recommendations, for each said security finding.
13. A method of detecting software vulnerabilities comprising the
steps of: a) inputting compiled code and optionally source code
that resulted in said compiled code; b) creating an instruction
model for each said instruction comprising location, debug
information, instruction type, operands, existing memory state
requirements, bytecode metadata, potential security attributes,
basic block membership, function/method membership if applicable
and class membership of each said instruction; c) creating a
control flow graph associated with each said instruction model,
comprising all potential control flow paths, and a bidirectional
list of predecessor instructions for each said instruction; d)
creating and populating a data flow model; e) creating a security
finding for each said instruction that calls an unsafe function on
unsafe data; and f) generating a security report comprising said
debug information and said source code information for each said
security finding.
14. The method of detecting software vulnerabilities of claim 13
wherein said instruction model is further provided with
placeholders for additional attributes, including pointer aliasing
information and unsafe dataflow information.
15. The method of detecting software vulnerabilities of claim 14
wherein said pointer aliasing information comprises aliasing maps
that are populated with pointers representing the same value given
at least two control flows of each said instruction of said
compiled code.
16. The method of detecting software vulnerabilities of claim 13
wherein said instruction model is further provided with attributes
deduced from other attributes, including values for memory,
register and variable type of each said instruction.
17. The method of detecting software vulnerabilities of claim 13
wherein said population of said data flow model is performed by
running said compiled code at least once and recording flow of
unsafe data for each said run.
18. The method of detecting software vulnerabilities of claim 13
wherein said population of said data flow model is based at least
partially on a data flow file in which flow of unsafe data during
the execution of said compiled code has been recorded.
19. The method of detecting software vulnerabilities of claim 13
wherein said compiled code is further instrumented at random and
critical control flow points allowing observing and modification of
properties of data as it flows during the execution of said
compiled code.
20. The method of detecting software vulnerabilities of claim 13
further comprising the steps of: a) creating three lists Unsafe1,
Unsafe2, Unsafe3 for each said instruction; b) scanning said
compiled code to determine locations where external input is
supplied and marking said locations as containing unsafe data, and
further creating a Worklist of all instructions at said locations
that call an unsafe function; c) creating a set of concurrent
worker threads, each thread selecting an instruction at random from
said Worklist, and processing it according to said control flow
graph, and said data flow model, and populating said Unsafe1 list
with incoming unsafe data at said instruction, Unsafe2 list with
unsafe data currently being processed by said instruction, and
Unsafe3 list with unsafe data that has been fully processed by said
instruction; d) adding an instruction to said Worklist in step(c)
above if said instruction has new data added to its said Unsafe1
list and said instruction further calls an unsafe function, and
repeating step (c); and e) concluding said creation of said worker
threads if all instructions in said Worklist have been processed as
specified in steps (c) and (d), or a predetermined time has
elapsed.
21. The method of detecting software vulnerabilities of claim 20
further creating a concurrency lock for each said list Unsafe1,
Unsafe2 and Unsafe3.
22. The method of detecting software vulnerabilities of claim 21
further applying said concurrency locks to ensure integrity of said
data populated in said lists Unsafe1, Unsafe2, Unsafe3.
23. The method of detecting software vulnerabilities of claim 21
releasing each said concurrency lock corresponding to each said
list Unsafe1, Unsafe2 and Unsafe3, if said list is not in use.
24. The method of detecting software vulnerabilities of claim 20
wherein step 20(c) is further performed according to custom unsafe
data propagation rules provided by user.
25. The method of detecting software vulnerabilities of claim 13
wherein said security finding is created by analyzing said data
flow model.
26. The method of detecting software vulnerabilities of claim 13
wherein said security report is further provided with an execution
trace of said unsafe data corresponding to each said security
finding, said execution trace comprising information from the
origin to the termination of said unsafe data, derived from said
data flow model and the associated line numbers from said source
code information.
27. The method of detecting software vulnerabilities of claim 26
wherein said execution trace further comprises the identifier value
of any register or variable containing said unsafe data.
28. The method of detecting software vulnerabilities of claim 27
wherein said security report highlights at least one said
identifier and variable associated with said unsafe data.
29. The method of detecting software vulnerabilities of claim 13
wherein said security report is further provided with a risk
rating, a human-readable description of each said security finding
and one or more remediation recommendations for each said security
finding.
29. The method of detecting software vulnerabilities of claim 13
wherein said concurrent worker threads are executed across at least
one CPU or processor or core or computing machine or node.
Description
FIELD OF THE INVENTION
[0002] This invention relates generally to ensuring software
security and in particular to exposing software vulnerabilities by
performing static and dynamic analysis of compiled software.
BACKGROUND ART
[0003] Software security and vulnerability checking is an active
field of academic and industrial pursuit. With the news of
exploitation of software vulnerabilities by hackers a commonplace
occurrence, it is unsurprising to see many academic and
professional institutions focusing their efforts to develop tools
and practices that aim to make software more secure against
exploitative attacks from global hackers and adversaries.
[0004] There are many ways of detecting and addressing
vulnerabilities in software in the prior art. U.S. Pat. No.
8,499,353 discloses security assessment and vulnerability testing
of software applications based in part on application metadata in
order to determine an appropriate assurance level and associated
test plan that includes multiple types of analysis. Steps from each
test are combined into a "custom" or "application-specific"
workflow, and the results of each test then correlated with other
results to identify potential vulnerabilities.
[0005] U.S. Pat. No. 8,365,155 describes a software analysis
framework utilizing a decompilation method and system for parsing
executable code, identifying and recursively modeling data flows,
identifying and recursively modeling control flow and iteratively
refining these models to provide a complete model at the nanocode
level. The nanocode decompiler may be used to determine flaws,
security vulnerabilities, or general quality issues that may exist
in the code.
[0006] U.S. Pat. No. 8,739,280 describes a context-sensitive taint
analysis system. Taint processing applied to a tainted value of an
application is identified and an output context of the application
associated with output of the tainted value is determined. It is
determined whether the taint processing is effective in mitigating
a security vulnerability caused by the tainted value for the output
context.
[0007] U.S. Pat. No. 8,347,392 describes an apparatus and method
for analyzing and supplementing a program to provide security. A
computer readable storage medium has executable instructions to
perform an automated analysis of program instructions. The
automated analysis includes at least two analyses selected from an
automated analysis of injection vulnerabilities, an automated
analysis of potential repetitive attacks, an automated analysis of
sensitive information, and automated analysis of specific HTTP
attributes. Protective instructions are inserted into the program
instructions. The protective instructions are utilized to detect
and respond to attacks during execution of the program
instructions.
[0008] Non-Patent reference, "Dynamic Taint Analysis for Automatic
Detection, Analysis" by James Newsome and Dawn Song of Carnegie
Mellon University, proposes a dynamic taint analysis solution for
automatic detection of overwrite attacks. The approach does not
need source code or special compilation for the monitored program,
and hence works on commodity software. To demonstrate this idea,
they implemented TaintCheck, a mechanism that can perform dynamic
taint analysis by performing binary rewriting at run time.
[0009] Non-Patent reference, "gFuzz: An instrumented web
application fuzzing environment" by Ezequiel D. Gutesman of Core
Security Technologies, Argentina, introduces a fuzzing solution for
PHP web applications that improves the detection accuracy and
enriches the information provided in vulnerability reports. They
use dynamic character-grained taint analysis and grammar-based
analysis in order to analyze the anatomy of each executed SQL query
and determine which resulted in successful attacks. A vulnerability
report is then accompanied by the offending lines of source code
and the fuzz vector (with attacker-controlled characters
individualized).
[0010] One shortcoming of prior art teachings is that they suffer
from poor accuracy while also at times requiring source code for
analysis as opposed to just bytecode/assembly code, or they attempt
to simplify the bytecode/assembly code before analysis. Other prior
art work teaches running both dynamic and static analysis
components in an independent or serial fashion. Furthermore earlier
approaches attempt to exhaustively map all data flows in a
decompiled or intermediate representation of a software system
which impairs performance and slows the overall process. Relatedly,
prior art teachings do not provide for advantages afforded by
concurrent multi-core or multi-CPU processing infrastructure that
is commonplace these days, to allow for distributed analysis of
very large target software systems with high precision.
OBJECTS OF THE INVENTION
[0011] In view of the shortcomings of the prior art, it is an
object of the present invention to provide for high-precision
software analysis system and methods that do not require the source
code of the analyzed program.
[0012] It is another object of the invention to not require an
exhaustive processing of all dataflows in a program but rather than
the ones that include unsafe data.
[0013] It is another object of the invention to not rely on
decompliation of executable binary code.
[0014] It is yet another object of the invention to allow for
distributed processing of the analysis framework taught by the
invention by taking advantage of a multi-CPU or multi-core
processing environment, consequently allowing for analysis of very
large target software systems with efficiency and high
precision.
SUMMARY OF THE INVENTION
[0015] The objects and advantages of the invention are secured by a
system and methods of detecting software vulnerabilities in a
computer program by analyzing the compiled code of that computer
program. The invention optionally uses the source code of the
computer program in conjunction with the compiled code, but having
the source code is not a requirement of the invention. The
invention teaches utilizing an instruction model for each binary
instruction of the compiled code. The instruction model for a given
instruction includes the location, debug information, instruction
type, operands, existing memory state requirements, bytecode
metadata, potential security attributes, basic block membership and
function/method membership if applicable of that instruction.
[0016] The invention further uses a control flow graph for each
instruction that complements the instruction model of that
instruction, and includes all potential control flow paths, and a
bidirectional list of predecessor instructions of that instruction.
Preferably, the compiled code is instrumented at random and
critical points in the code. There is a data flow model to record
the flow of unsafe data during the execution of the program. The
system has the means to analyze the data flow model and create a
security finding corresponding to each instruction that calls an
unsafe function on unsafe data. These security findings are
aggregated in a security report along with the corresponding debug
information and the optional source code information for each
instruction that triggered the security finding.
[0017] In the preferred embodiment of the invention, the
instruction model also includes placeholders for additional
attributes. These additional attributes may include information for
pointer aliases or unsafe dataflow. The pointer alias information
may include an aliasing map containing pointers that have the same
address values given a subset of or all possible control flows of
the instructions of the compiled code.
[0018] In another embodiment, the instruction model also contains
attributes that are deduced from other attributes of the
instruction model. These derived attributes may include values for
memory locations, processor registers and variable types associated
with the given instruction of the instruction model. In another
preferred embodiment, the flow of unsafe data is recorded in a data
flow file that utilizes a common file format such as XML, based on
which the data flow model is at least partially populated. In an
advantageous embodiment of the invention, an analyzer module is
used to analyze the instruction model, control flow graph and the
data flow model to detect software vulnerabilities in the compiled
code.
[0019] In a highly advantageous embodiment of the invention, a set
of concurrent worker threads are spawned that take advantage of a
multi-core or multi-node or multi-machine or multi-CPU processing
platform, to analyze instructions where an unknown or unsafe
external input (or taint) data is provided to the program and an
unsafe function or method is called upon it. In another preferred
embodiment of the system, the security findings in the security
report also contain a full trace of the unsafe data at the
instruction that triggered the security finding, along with the
line numbers of the source file if available, a human-readable
description of the finding, a risk rating and optionally one or
more recommendations to address the security finding.
[0020] The methods of the invention further teach the steps
required to carry out the operation of the system. The invention
teaches the steps required to detect software vulnerabilities of a
computer program by taking as input the compiled code of the
program, and optionally its source code. It then creates an
instruction model and a control flow graph for each instruction in
the compiled code. If further creates a data flow model to record
the flow of unsafe data during the execution of the compiled code.
The compiled code is instrumented at random and critical control
flow points of the program.
[0021] For a given instruction, the instruction model includes the
location, debug information, instruction type, operands, existing
memory state requirements, bytecode metadata, potential security
attributes, basic block membership, function/method membership if
applicable and class membership of the given instruction. The
instruction model also includes placeholders for additional
attributes, including pointer aliasing information, unsafe data
flow information and attributes that are deduced from other
attributes including values of memory locations, values of
processor registers and variable types for the given
instruction.
[0022] For each instruction, the control flow graph is populated
with all potential control flow paths, and a bidirectional list of
predecessor instructions. Finally, for each instruction, the data
flow model is populated by running the compiled code with the
instrumentation at least once and recording the flow of unsafe data
for each run. In another preferred embodiment, this recording of
unsafe data flow is first done in a data flow file in a common file
format such as XML, and the population of the data flow model is
based on the data flow file.
[0023] The compiled code is scanned according to the methods
claimed by the invention to find each instruction where an external
input is supplied to the program, denoting unknown, unsafe data. If
that instruction calls an unsafe function on the unsafe data, this
triggers the creation of a security finding. As the analysis is
performed, all security findings are aggregated in a security
report. In the preferred embodiment, each security finding in the
security report includes the debug information for the instruction
that triggered the finding, along with the line numbers of the
source code if available, a trace of the unsafe data from its
origin to termination, identifier values of any processor registers
or variables containing the unsafe data, a description of the
security finding, a risk rating, and optionally one or more
recommendations to address or remedy the security finding.
Appropriate highlighting of these elements in the security report
is also performed to make the report visually presentable, readable
and easy to consume.
[0024] In another advantageous embodiment, three lists are created
for each instruction. These lists are Unsafe1, Unsafe2 and Unsafe3.
All instructions that are determined to be unsafe i.e. they use
unsafe data by calling an unsafe function, are added to a list
called Worklist. A set of concurrent worker threads are spawned,
each thread selecting and processing an instruction at random from
Worklist. Based on the control flow graph and data flow model
earlier created, for each instruction in Worklist, Unsafe1 list is
populated with incoming unsafe data at that instruction, Unsafe2
list with unsafe data currently being processed by that
instruction, and Unsafe3 list with unsafe data that has been fully
processed by that instruction. As the worker threads process the
instructions, the contents of the three lists for each instruction
are updated based on the control flow graph of that instruction as
data flows from its Unsafe1 list to Unsafe2 list to Unsafe3 list
and into the Unsafe1 list of the downstream instruction. If new
unsafe data is added to the Unsafe1 list of an instruction that
calls an unsafe function, it is re-added to the Worklist and a
security finding is generated, and the above process is repeated.
Ultimately, the spawning of worker threads is concluded when there
are no more unsafe instructions left in Worklist, or a
predetermined timeout period has elapsed during the above
processing.
[0025] Concurrency locks are provided for each of the three lists,
Unsafe1, Unsafe2 and Unsafe3 above, and at each step of the above
processing, these locks are used to ensure the integrity of the
contents of these lists. When a list is no longer being used, its
concurrency lock is released (unlocked).
[0026] In a highly advantageous embodiment, worker threads are
distributed across a multi-core or multi-processor or multi-CPU
processing environment to improve the performance of the analysis
and to allow processing of very large target software programs. In
a similarly advantageous embodiment, the traversal of the control
flow graph by the worker threads is performed according to custom
unsafe data propagation rules provided by the user. In another
advantageous embodiment the security findings are created by an
analyzer module.
[0027] Clearly, the system and methods of the invention find many
advantageous embodiments. The details of the invention, including
its preferred embodiments, are presented in the below detailed
description with reference to the appended drawing figures.
BRIEF DESCRIPTION OF THE DRAWING FIGURES
[0028] FIG. 1 is a block diagram view of the software
vulnerabilities detection system according to the current
invention.
[0029] FIG. 2 is a conceptual diagram of the instruction model
according to the current invention.
[0030] FIG. 3 is a diagram of the control flow graph of an
instruction according to the invention.
[0031] FIG. 4 is a conceptual diagram of the data flow model of an
instruction according to the invention.
[0032] FIG. 5 is a detailed block diagram view of the elements and
their workings according to the current invention.
[0033] FIG. 6 is a flowchart comprising the analytical steps of the
algorithm required for the detection of software vulnerabilities
according to the current invention.
DETAILED DESCRIPTION
[0034] The figures and the following description relate to
preferred embodiments of the present invention by way of
illustration only. It should be noted that from the following
discussion, alternative embodiments of the structures and methods
disclosed herein will be readily recognized as viable alternatives
that may be employed without departing from the principles of the
claimed invention.
[0035] Reference will now be made in detail to several embodiments
of the present invention(s), examples of which are illustrated in
the accompanying figures. It is noted that wherever practicable,
similar or like reference numbers may be used in the figures and
may indicate similar or like functionality. The figures depict
embodiments of the present invention for purposes of illustration
only. One skilled in the art will readily recognize from the
following description that alternative embodiments of the
structures and methods illustrated herein may be employed without
departing from the principles of the invention described
herein.
[0036] The present invention will be best understood by first
reviewing the software vulnerabilities detection system 100
according to the current invention as illustrated in FIG. 1.
Vulnerabilities detection system 100 comprises computer program 102
in the form of its compiled code 104 and optionally source code 106
that resulted in its compiled code 104. Computer program 102 is the
target program to be analyzed by system 100 for software
vulnerabilities. Having source code 106 is desirable but not
required by software vulnerabilities detection system 100 according
to the invention. Vulnerabilities detected by system 100 in
computer program 102 may allow exploitative attacks by potential
adversaries or hackers. Such attacks include, but are not limited
to denial of service attacks, code injection attacks and 2.sup.nd
order attacks such as cross-site scripting (XSS) attacks.
[0037] Software vulnerabilities detection system 100 comprises
instruction model 110, control flow graph 112 and data flow model
114. Based on instruction model 110, control flow graph 112 and
data flow model 114, software vulnerabilities detection system 100
performs analysis 116 to produce security report 118 comprising the
security findings discovered during analysis 116.
[0038] Readers with ordinary skill in the art will understand that
compiled code 104 can be executable binary code, machine code, or
object code that can run directly on a hardware platform such as
x86, Sparc, Mac, HP, IBM Mainframe, etc. or it can be an
intermediate bytecode or portable code that can run in a given
runtime environment such as Java Virtual Machine (JVM). Source code
106 can be in any programing language such as C, C++, Java,
Assembly, Cobol, SQL, etc. Furthermore, source code 106 can be in
any 2.sup.d, 3.sup.rd, 4.sup.th or higher generation programming
language without departing from the principles of the invention. A
highly advantageous aspect of the current invention is that source
code 106 is desirable, but not required to achieve the objects of
the invention. Not requiring the presence of source code 106
overcomes many practical limitations of the prior art.
[0039] Instruction model 110 is a programming construct used by the
invention to model each instruction of compiled code 104. This
programming construct comprises all the necessary and desirable
attributes required by system 100 to model each instruction of
compiled code 104. These attributes include the location (e.g. base
address and relative memory location), debug information if
available (e.g. variable name annotations and/or source code line
annotations), type of the instruction (e.g. mov, add, sub), its
operands (e.g. eax register, an integer immediate value, operand
stack reference, local value reference), its potential security
attributes and existing memory state requirements (e.g. basic block
derived invariant conditions), basic block membership (e.g. start
and end references for all basic blocks encompassing an
instruction), function/method membership and/or class membership of
that instruction if applicable. Those with average skill in the art
will find these attributes familiar from the fundamentals of
software engineering and computer programming. FIG. 2 provides a
conceptual representation of instruction model 110 using a familiar
notation for data structures and member associations in computer
programming.
[0040] Referring to FIG. 1, during the execution of compiled code
104, user input 108 may be provided by the operator or user of
computer program 102 whose vulnerabilities are to be detected.
Those familiar with the art will understand that user input 108
represents a potential security risk for computer program 102 as it
may intentionally or otherwise, violate the bounds of a program
variable which may affect the integrity of computer program 102 or
the data it is operating on. Thus user input 108 represents `taint`
or unsafe data, as will be understood by skilled people of the art.
User input 108 can be provided in many different ways, for example,
via a web form and keyboard, a file, an input/output buffer or
stream, a pipe, screen redirect, etc.
[0041] Compiled code 104 according to the invention is preferably
instrumented at random and critical control flow points of the
program. Those familiar with the art will understand that
instrumentation may refer to code instructions and metadata
augmented to the computer program that allow monitoring of its
behavior, performance and operation more closely than during normal
execution, and may generate additional logging and debug output to
the screen or files as desired. As claimed by the invention,
computer program 102 is preferably instrumented at random points
within the program. Instead of or in addition to that, the program
is also preferably instrumented at points where there is a critical
control flow transition in the program.
[0042] Those familiar with the art will understand that there are
many ways to determine these points where instrumentation will be
provided in computer program 102 in the preferred embodiment. For
example, instructions in compiled code 104 can be randomly selected
for instrumentation. Alternatively or in addition, a pre-processor
can be used to determine the critical control flow points in
program 102 prior to its execution, and then instrumentation can be
added at those points in program 102. Indeed, it is allowed by the
invention to instrument entire or none of computer program 102,
without departing from the principles of the invention. The
instrumentation of program 102 allows observing and modification of
unsafe data as it flows through program 102 according to the
teachings of the invention.
[0043] The invention further uses control flow graph 112 for each
instruction that complements instruction model 110 of that
instruction. Control flow graph 110 for a given instruction of
compiled code 104 is populated with all potential control flow
paths of that instruction, assuming there is no overwriting of the
underlying instructions. Control flow graph 112 for a given
instruction also contains a bidirectional list of its predecessor
instructions. FIG. 3 represents control flow graph 114 for an
instruction I according to the teachings of the invention. In FIG.
3, each instruction is represented by a circle. Instruction I has 4
predecessor instructions P and 3 successor instructions S
representing all possible control flow paths for I as shown in the
figure. All P instructions will be contained in a bidirectional
list in control flow graph 112 for instruction I as represented by
the dashed line in FIG. 3.
[0044] Referring back to FIG. 1, the invention further comprises
data flow model 114. During the execution of program 102, the
movement of unsafe data is recorded in data flow model 114. As
unsafe data moves from one variable or processor register to
another and from one instruction to the successor instruction, this
movement is recorded in data flow model 114 according to the
teachings of the invention. FIG. 4 represents an example data flow
model 114 populated according to the teachings of the invention.
Variable V1 contains unsafe data that may have been previously
supplied by user input 108 as taught earlier. Tainted data V1 is
then moved to processor register AX in the next instruction of one
control flow path, and then copied to variable V2. The subsequent
instruction then calls an unsafe function on variable V2
representing a potential security risk in the computer program.
FIG. 4 also illustrates additional control flow paths in data flow
model 114 where the unsafe function call is performed on the
tainted data contained in variable V2. Those familiar with the art
will know the various types of unsafe function calls that may
result in a potential security flaw in the code that can be
exploited by an adversary. For example, in C/C++
"char*strcpy(char*dest, const char*src)" function on tainted data
is an unsafe function call, because it can allow a security
condition called buffer overflow to happen and damage the integrity
of computer program 102 of FIG. 1, or its data, or worse allow a
malicious adversary to inject harmful code or virus into the
computer program.
[0045] According to the teachings of the current invention as
explained above, data flow model 114 only records the flow of
unsafe data during the execution of the program, as opposed to
attempting to include and record all potential data flows. This
significantly reduces the performance overhead and memory
requirements of software vulnerabilities detection system 100,
allowing it to analyze large target software systems more
comprehensively than possible through the teachings of prior art.
This also allows the current invention to not require decompilation
of compiled code, as required by some prior art teachings.
[0046] According to the main embodiment of the invention, based on
instruction model 110, control flow graph 112 and data flow model
114, all instructions in computer program 102 that call an unsafe
function on unsafe data, trigger a security finding which is
recorded in security report 118 as represented in FIG. 1. Each such
security finding contains debug information of the instruction that
triggered the security finding, along with its source code
information, if available. Security report 118 exposes the
vulnerabilities in computer program 102 that can be appropriately
remediated to prevent exploitative attacks by amateur and
professional adversaries according to the teachings of the
invention.
[0047] As represented in FIG. 2, instruction model 110 further
includes placeholders for additional attributes or deduced
attributes that may not be immediately known at the time of the
initial creation of instruction model 110. These additional
attributes may include pointer aliases. Pointer aliases represent
pointers that point to, or contain memory addresses, that remain
the same for multiple control flow paths of computer program 102.
In addition, instruction model 110 for a given instruction I may
include information related to its predecessor instructions P as
represented in FIG. 3, and any additional information or metadata
as deemed necessary to facilitate recording of the flow of unsafe
data as represented in FIG. 4. Furthermore, instruction model 110
may also include information deduced from other attributes.
Examples of such derived attributes include memory locations or
addresses, processor registers and variable type information for
the given instruction based on its type, debug information and
bytecode metadata.
[0048] According to an additional embodiment of the invention,
analysis 116 in FIG. 1 may be performed by an analyzer module.
Analyzer module may be a part of system 100 or may be external to
it. If it is external to system 100, appropriate remote invocation
calls or function calls or remote procedure calls (RPC) may be
implemented to call the external module, as will be obvious to
those skilled in the art. Indeed it is possible that the analyzer
module is a 3.sup.rd party software with its own application
programming interface (API), without departing from the principles
of the invention. Similarly, in a highly advantageous embodiment,
analysis 116 is performed by worker threads that are spawned
specifically for that purpose. These worker threads may then be
distributed across a cluster of computing nodes, processors or
cores, in a multi-CPU or multi-core, parallel processing
environment.
[0049] Further embodiments claim that security report 118 of FIG. 1
may comprise an execution trace of unsafe data corresponding to
each said security finding populated in the report. The execution
trace may contain the origin and termination information for the
unsafe data that ultimately caused the security finding to be
triggered. For example, if unsafe data was provided as a user input
in function or instruction I1 and it traversed through several
intervening functions or instructions I2 . . . I9 before being
discarded or reset in instruction I10, then execution trace for the
corresponding security finding in security report 118 may contain
the entire lifecycle or trace of that data along with the names of
functions or instructions I1 . . . I10. In addition, security
report 118 may contain a human friendly description of the security
finding, and a risk rating or risk factor assigned to the security
finding by system 100. Depending on the severity of the
vulnerability associated with each finding, vulnerabilities
detection system 100 may assign a risk rating from 1 to 10, or as a
percentage, or use some other suitable rating system. Security
report 118 may also contain one or more recommendations on how to
address the security finding, or `fix` the problem. Such
recommendations and risk assignments may be based on a
knowledgebase (not shown) derived from subject matter expertise in
detecting and correcting such software vulnerabilities.
[0050] The methods of the invention describe the steps required to
operate software vulnerabilities detection system 100 of FIG. 1. In
the preferred embodiment, computer program 102 is executed at least
once and the flow of unsafe data through the program is first
recorded in a data flow file 140 as shown in FIG. 4. Based on the
contents of data flow file 140, data flow model 114 is populated.
The format of data flow file 140 can be any suitable file format,
such as XML, plain text, any other markup format, or a binary (or
compiled) format, without departing from the principles of the
invention.
[0051] In the preferred embodiment, three lists, Unsafe1, Unsafe2,
Unsafe3 are created for each instruction. Persons with average
skill in the art will understand that these lists can be linked
lists, arrays or any other appropriate data structures of computer
software without departing from the principles of the invention.
Compiled code 104 is scanned to find each instruction where an
external input is supplied to the program, denoting unknown, unsafe
or `taint` data. If that instruction calls an unsafe function on
the unsafe data, that instruction is added to another list,
Worklist. Persons skilled in the art will again understand that
Worklist can be a linked list, an array or any other suitable data
structure. List Worklist 160, Unsafe1 list 180, Unsafe2 list 184
and Unsafe3 list 186 are shown in FIG. 5 along with the other
elements of the invention as taught earlier.
[0052] Next, a set of concurrent worker threads are spawned, each
thread selecting and processing an instruction at random from
Worklist 160 of FIG. 5. Based on instruction model 110, control
flow graph 112 and data flow model 114, for each instruction in
Worklist 160, Unsafe1 list 180 is populated with incoming unsafe
data at that instruction, Unsafe2 list 182 with unsafe data
currently being processed by that instruction, and Unsafe3 list 184
with unsafe data that has been fully processed by that instruction.
As the worker threads process the instructions of compiled code
104, the contents of Unsafe1 list 180, Unsafe2 list 182, Unsafe3
list 184 for each instruction are updated based on control flow
graph 112 of that instruction as data flows from its Unsafe1 list
180 to Unsafe2 list 182 to Unsafe3 list 184 and into Unsafe1 list
180 of the successor instruction.
[0053] If new unsafe data is added to Unsafe1 list 180 of an
instruction that calls an unsafe function, a new security finding
200 is created and added to security report 118 as represented in
FIG. 5, and that instruction is re-added to Worklist 160, and the
above process is repeated. Ultimately, the spawning of worker
threads is concluded when there are no more unsafe instructions
left in Worklist 160, or a predetermined timeout period has elapsed
during the above processing. FIG. 6 shows the above algorithm in a
flowchart format where an unsafe instruction denotes an instruction
that calls an unsafe function on unsafe data as explained above,
and the label instr is used to abbreviate the term instruction.
[0054] Referring to FIG. 5, concurrency locks 190, 192, 194 are
provided for each of Unsafe1 list 180, Unsafe2 list 182 and Unsafe3
list 184 respectively, and at each step of the above processing,
these locks are used to ensure the integrity of the contents of
these lists. When a list is no longer being used, its concurrency
lock is released (unlocked). Those skilled in the art will
understand how the contents of Unsafe1 list 180, Unsafe2 list 182
and Unsafe3 list 184 will be updated as explained above. Further
explained, when a worker thread selects an instruction to process
from Worklist 160, it locks its Unsafe2 list 182 and Unsafe3 list
184, and also temporarily locks its Unsafe1 list 180 while it
imports data from its Unsafe1 list 180 to Unsafe2 list 182. The
worker thread then statically analyzes the currently selected
instruction to determine from its incoming unsafe data in Unsafe1
list, currently processed data in Unsafe2 list and fully processed
data in Unsafe3 list, what other instructions that unsafe data may
propagate to, based on the attributes of the current instruction as
contained in its instruction model 110, and any other custom unsafe
data propagation rules pre-defined or provided by the user.
[0055] Examples of custom unsafe data propagation rules include
specifying that a function or method, e.g. execSqlStatement(String
query), should never receive unsafe or "taint" user input in its
first and only parameter. Such a rule could be expressed as an XML
file defining regular expressions to identify the specific class
and method for this call, along with a numeric value identifying
that the first parameter should never be tainted or uncontrolled,
along with security information defining the security impact of
such a condition. Another example would be a rule which identifies
that the subString(Integer from) call will propagate the value of
its object instance to its return value, which could be similarly
expressed in an xml file, and identifying the return value. Still
other examples of custom rules include source rules, which define
the insertion of uncontrolled or tainted data into a program and
cleanse rules which define methods that are known to control data
such that the data can afterwards be considered safe in one or more
ways.
[0056] Referring back to FIG. 5 and preceding teachings, based on
control flow graph 112 of the current instruction, the current
worker thread aggregates all possible control flow destinations of
the current instruction in a list Next Instructions (not shown).
Subsequently, for each instruction in Next Instructions list, the
current worker thread locks its Unsafe1 list and adds outgoing
processed unsafe data contained in Unsafe3 list 184 of current
instruction, to incoming unsafe data contained in Unsafe1 list 180
of the instruction selected from Next Instructions list. As
explained above, if unsafe data is added to Unsafe1 list of an
instruction that calls an unsafe function, a security finding 200
is added to security report 118 and that instruction is re-added to
Worklist 160. The above process continues until there are no more
instructions left to process in Worklist 160 or a timeout period
has elapsed.
[0057] In a highly advantageous embodiment, worker threads are
distributed across a multi-core or multi-CPU or multi-machine or
multi-node processing environment to improve the performance of the
analysis and to allow processing of very large target software
programs. In a similarly advantageous embodiment, the traversal of
the control flow graph by the worker threads is performed according
to custom unsafe data propagation rules provided by the user. In
another advantageous embodiment the security findings are created
by an analyzer module.
[0058] In another advantageous embodiment, security report 118 as
shown in FIG. 5 contains a full execution trace of unsafe data
corresponding to each security finding 200 populated in security
report 118. The execution trace may contain the origin and
termination information for the unsafe data that ultimately caused
security finding 200 to be triggered. For example, if unsafe data
was provided as a user input in function or instruction I1 and it
traversed through several intervening functions or instructions I2
. . . I9 before being discarded or reset in instruction I10, then
execution trace for corresponding security finding 200 in security
report 118 may contain the entire lifecycle or trace of that data
along with the names or labels of instructions I1 . . . I10 along
with filename or filenames and corresponding line numbers in the
source files obtained from debug information or assembly
instructions or source code 106 if available. If source code 106 is
available, each source file corresponding to the above trace is
parsed into an abstract syntax tree or trees, and the line numbers
and offsets for non-keyword identifier tokens is generated. Persons
skilled in the art will understand that these non-keyword
identifier tokens will represent user or custom variables, as
opposed to keywords belonging to the grammar of the programming
language itself. Using the abstract syntax tree or trees above,
corresponding to each instruction in the trace, the identifier
names and values of any variables or processor registers that
contained the unsafe data is obtained using the debug information
and added to the trace information.
[0059] In addition, security report 118 of FIG. 5 may be properly
formatted to be visually appealing with proper highlighting of
important pieces of information for each security finding 200, and
contain a human friendly description of the finding along with a
risk rating or risk factor assigned to the finding by system 100.
Depending on the severity of the vulnerability associated with each
security finding 200, vulnerabilities detection system 100 may
assign a risk rating from 1 to 10, or as a percentage, or use some
other suitable rating system. Security report 118 may also contain
one or more recommendations on how to address security finding 200,
or `fix` the problem. Such recommendations and risk assignments may
be based on a knowledgebase (not shown) derived from subject matter
expertise in detecting and correcting such software
vulnerabilities. The knowledgebase may be further designed to
continuously augment its content either automatically or with human
assistance or by a combination of both automatic and manual means,
as vulnerabilities detection system 100 operates over time.
[0060] In view of the above teaching, a person skilled in the art
will recognize that the apparatus and method of invention can be
embodied in many different ways in addition to those described
without departing from the principles of the invention. Therefore,
the scope of the invention should be judged in view of the appended
claims and their legal equivalents.
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