Under-constrained Manticore

MATE provides a web UI for exploring programs with the Manticore symbolic execution engine in an under-constrained mode. Unlike traditional symbolic execution which begins at the program entry point and executes until the program exits, under-constrained symbolic execution starts at an arbitrary function. This specificity means that under-constrained symbolic execution can analyze parts of programs that would be too large or complex for traditional symbolic execution.

Symbolic execution enables bit-precise local reasoning about memory and arithmetic, which complements MATE’s higher-level inter-procedural data- and control-flow analyses.

Under-constrained execution is implemented as a Manticore Plugin, which means it can be enabled/disabled easily, and should be able to coexist with other detectors such as the UAF or variable-bounds detectors.

In broad terms, under-constrained Manticore works as follows:

  • Program initialization: the program is run normally from its entry-point, until the main function is reached. This allows shared libraries to be properly initialized, as well as any globals in the program. When main is reached, Manticore jumps directly to the beginning of the target function and continues from there

  • Target function setup: when jumping directly to the target function, Manticore needs to provide proper function arguments as if it was normally called from within the program. To do so, it uses the CPG to infer the expected arguments and their types, and creates a symbolic expression for every argument. So the target function is called with fully symbolic inputs.

  • Symbolic pointers: when a function takes a pointer as argument, e.g foo(int *ptr), and that pointer is dereferenced in the function’s body, Manticore has to rely on a special memory model. In a normal Manticore run, ptr would have been initialized previously by the program, but in under-constrained mode it is purely symbolic, and doesn’t point to any real allocated data. So Manticore will artificially allocate a symbolic object pointed by ptr (and thus containing only symbolic data as well), and read inside that object rather than in the regular memory when ptr is dereferenced. Note that underlying usage of a special memory layout happens seamlessly.

  • Out-of-bounds memory access detection: when the program reads from a symbolic offset in an under-constrained object, for instance:

    foo(int *ptr, int idx){
        return ptr[idx];

    under-constrained Manticore is able to detect if the access can be out-of-bounds by using the solver to determine whether the symbolic offset can exceed the bounds of the object. If yes, then it will record a test case indicating a potential OOB error.

Starting an under-constrained Manticore task

Under-constrained Manticore tasks are started just like regular Manticore exploration tasks. The request format is available in the MATE REST API documentation by selecting ExploreFunctionOptions in the request.

The exploration options that are passed with the API call are similar to the regular exploration options with some additional settings:

  • target_function: the name of the target function to execute. In case of a C++ binary the name must be mangled.

  • input_constraints: additional symbolic state constraints. Those can be used to constrain Manticore further to eliminate possible errors that are false positive or to optimize the execution time by trimming some exploration paths. See the Specifying additional symbolic constraints section for more details.

  • primitive_ptr_policy: the policy for choosing the length of unbounded symbolic arrays that contain primitive types. The default policy lets Manticore choose reasonable lengths for arrays, but the user can specify explicit lengths to use by switching to the custom policy.

  • complex_ptr_policy: the policy for choosing the length of unbounded symbolic arrays that contain complex types such as structures or objects. The default policy lets Manticore choose reasonable lengths for arrays, but the user can specify explicit lengths to use by switching to the custom policy.

Specifying additional symbolic constraints

Sending additional symbolic constraints is central in the under-constrained Manticore workflow. When first starting a task it is very likely that Manticore will report many errors that are false positives. Incrementally adding constraints and re-launching the task allows to eliminate the false positives and keep only the interesting results.

Two examples of using constraints are:

  • relationship between function arguments: consider the following strcpy-like function:

    void my_strcpy(char *dst, char *src){
        while((*(dst++) = *(src++))){};

    If src is longer than dst, Manticore will return a potential out-of-bounds memory write error. However, in some cases, we might be sure (or want to assume) that src is smaller than dst. Using a symbolic constraint will allow use to enforce the size relationship between src and dst in Manticore and remove the out-of-bounds error.

  • data structure invariants: imagine a function that takes the following struct as argument:

    struct string {
        char *str;
        int len; // Length of 'str'

    under-constrained Manticore doesn’t know that len if referring to the size of str. While in some cases avoiding to correlate len and str could help find bugs withing the string implementation, we will often want to inform Manticore of the relationship between those two variables (one is the size of the other) so that the string struct behaves correctly and doesn’t cause many false positive errors that will hide other interesting findings. This becomes even more true when using classes of the C++ standard library like std::vector, std::string, etc, of whom Manticore must assume that their implementations and internals are bug-free.

Symbolic constraints can be written using the Domain-Specific-Language (DSL) described below.

Constraints on function parameters

Basic constraints on function parameters can be expressed using regular arithmetic and logic operations and by following the variable naming found in the source code. For example if we target the foo function:

struct A {
    int a;
    int b;

void foo(struct A x) {

We could add the following constraint on the x argument:

x.a <= x.b + 10

Most of the operations can be expressed using the corresponding standard C operator (+, -, *, >>, &, ^, %, etc). However, many operators exist in both signed and unsigned versions. In order to distinguish between them, some operators are written using a function-like syntax (<operator>(arg1, arg2, ...)):

  • Unsigned comparisons: ULE(), ULT(), UGE(), UGT() (>, <, etc, default to signed comparisons)

  • Signed division: SDIV() (/ defaults to unsigned division)

  • Arithmetic shift left: SAR()

  • Concatenation: CONCAT(<higher>, <lower>)

  • Bitfield extract: EXTRACT(<arg>, <offset>, <size>)


The symbolic constraint DSL offers a few special operators that refer to “properties” of variables rather than to the variable themselves. Since every property of every object is represented by a dedicated unique symbolic variable, we call those meta-variables.

  • $LEN(<var>): can be used to refer to the length of an array pointed by a raw pointer. When under-constrained Manticore receives an unbounded pointer (e.g int*) it has to guess if the pointer points to a single integer in memory, or if it points to an array of integers. In addition to hard-coded heuristics, users can give hints or constrain array sizes using $LEN(). For instance, $LEN(buf) < 20 tells Manticore that the number of elements pointed by buf is less than 20.


    $LEN() refers to the number of contiguous elements of an array in memory, and not the total length in bytes of the array

  • $CAPACITY(<var>): this refers to the total capacity of a container class such as

    vector or string. When used alone, this meta-variable doesn’t have much sense, it is meant to be used in Generic class constraints to ensure that under-constrained container classes have enough space allocated to add elements without needing to re-allocate additional space.

    We want to avoid memory re-allocation within complex objects because memory allocation using symbolic pointers or sizes is likely to break under-constrained Manticore

    An example usage of $CAPACITY() can be found in our Generic class constraints vector reference example.

  • $SIZE(<var>): size is similar to $CAPACITY in so far as it refers to the current size of a container-class. It should be contained between 0 and $CAPACITY(<var>). Again, using $SIZE() standalone doesn’t make sense, but it comes in handy for writing generic class constraints.

Example constraints to make the following structure coherent:

struct buffer {
    int *buf;
    int len; // Current number of elements stored in 'buf'

void foo(struct buffer *b);
$LEN(b.buf) == $CAPACITY(b)   # total length of b.buf: as big as b's capacity
$SIZE(b) <= $CAPACITY(b) # current size of b less or equal to it's capacity
b.len == $SIZE(b)

$POINTS_WITHIN constraints

By default, under-constrained Manticore will create new symbolic objects for every symbolic pointer it deals with. For example, if running the foo(int *a, int *b) function, Manticore will create two symbolic arrays, one for a and one for b. Those are distinct and will never overlap.

In some cases, pointers actually point to the same memory area. For example that is the case in std::vector’s implementation where the internal storage beginning and end are both indicated by a raw pointer.

To tell Manticore that two pointers point to the same area, we can use the $POINTS_WITHIN operator. The following:


will lead to Manticore creating one symbolic array for a and make b point to somewhere within a.

Generic class constraints

Symbolic constraints that must apply to all symbolic instances of a given type or class can be written using the following syntax:

<class_name>: <constraint>

The <class_name>: specifier must match type names as they are stored in the CPG.

Since class constraints are generic, there is no declared variable name to use when writing the constraint. Instead, one can use the $OBJ. syntax to refer to the instance of the class. If we build up on our previous example, that would give:

struct buffer {
    int *buf;
    int len; // Current number of elements stored in 'buf'

void foo(struct buffer *b);
buffer: $LEN($OBJ.buf) == $CAPACITY($OBJ)   # total length of 'buf' field as big as the instance capacity
buffer: $SIZE($OBJ) <= $CAPACITY($OBJ) # current size of the instance less or equal to it's capacity
buffer: $OBJ.len == $SIZE($OBJ)

When under-constrained Manticore instantiates the function argument b, the generic constraints for buffer are applied to b ($OBJ gets replaced by b).

It is also possible to write generic constraints for templated types by replace template type arguments by #:

some_templated_class<#,#>: ...

In the constraint body, template arguments can be referred to with the #<num> syntax. #0 refers to the first template argument, #1 to the second, and so on. Template arguments references with # can be used in constraints by the following operators:

  • $TYPESIZE(#<num>): returns the size in bytes for template argument number <num>, starting at #0

Below is an example set of constraints that enforces correct behavior for a symbolic std::vector with maximal capacity of 100 elements:

# Internal correctness of the data structure
vector<#,#>: $OBJ._M_impl._M_finish - $OBJ._M_impl._M_start == $SIZE($OBJ)*$TYPESIZE(#0)
vector<#,#>: $OBJ._M_impl._M_end_of_storage == $OBJ._M_impl._M_start + ($CAPACITY($OBJ)*$TYPESIZE(#0))
vector<#,#>: $LEN($OBJ._M_impl._M_start) == $CAPACITY($OBJ)
vector<#,#>: $CAPACITY($OBJ) == 100
# Make all internal pointers point to the same symbolic buffer
vector<#,#>: $POINTS_WITHIN($OBJ._M_impl._M_finish, $OBJ._M_impl._M_start)
vector<#,#>: $POINTS_WITHIN($OBJ._M_impl._M_end_of_storage, $OBJ._M_impl._M_start)

State forking

Under-constrained Manticore will fork at the same locations as regular Manticore. However, for practical reasons, under-constrained Manticore also needs to perform additional forking on Meta-variables. It will thus fork on:

  • $LEN: the length of an array pointed by a symbolic pointer

  • $CAPACITY: the capacity of a symbolic container class instance

  • $SIZE: the size (number of current elements) of a symbolic container class instance

If desired it is possible to constrain some of the meta-variables further to avoid too much state forking by Specifying additional symbolic constraints.