-- On the standard library side:
The `input: []const u8` parameter of functions passed to `testing.fuzz`
has changed to `smith: *testing.Smith`. `Smith` is used to generate
values from libfuzzer or input bytes generated by libfuzzer.
`Smith` contains the following base methods:
* `value` as a generic method for generating any type
* `eos` for generating end-of-stream markers. Provides the additional
guarantee `true` will eventually by provided.
* `bytes` for filling a byte array.
* `slice` for filling part of a buffer and providing the length.
`Smith.Weight` is used for giving value ranges a higher probability of
being selected. By default, every value has a weight of zero (i.e. they
will not be selected). Weights can only apply to values that fit within
a u64. The above functions have corresponding ones that accept weights.
Additionally, the following functions are provided:
* `baselineWeights` which provides a set of weights containing every
possible value of a type.
* `eosSimpleWeighted` for unique weights for `true` and `false`
* `valueRangeAtMost` and `valueRangeLessThan` for weighing only a range
of values.
-- On the libfuzzer and abi side:
--- Uids
These are u32s which are used to classify requested values. This solves
the problem of a mutation causing a new value to be requested and
shifting all future values; for example:
1. An initial input contains the values 1, 2, 3 which are interpreted
as a, b, and c respectively by the test.
2. The 1 is mutated to a 4 which causes the test to request an extra
value interpreted as d. The input is now 4, 2, 3, 5 (new value) which
the test corresponds to a, d, b, c; however, b and c no longer
correspond to their original values.
Uids contain a hash component and type component. The hash component
is currently determined in `Smith` by taking a hash of the calling
`@returnAddress()` or via an argument in the corresponding `WithHash`
functions. The type component is used extensively in libfuzzer with its
hashmaps.
--- Mutations
At the start of a cycle (a run), a random number of values to mutate is
selected with less being exponentially more likely. The indexes of the
values are selected from a selected uid with a logarithmic bias to uids
with more values.
Mutations may change a single values, several consecutive values in a
uid, or several consecutive values in the uid-independent order they
were requested. They may generate random values, mutate from previous
ones, or copy from other values in the same uid from the same input or
spliced from another.
For integers, mutations from previous ones currently only generates
random values. For bytes, mutations from previous mix new random data
and previous bytes with a set number of mutations.
--- Passive Minimization
A different approach has been taken for minimizing inputs: instead of
trying a fixed set of mutations when a fresh input is found, the input
is instead simply added to the corpus and removed when it is no longer
valuable.
The quality of an input is measured based off how many unique pcs it
hit and how many values it needed from the fuzzer. It is tracked which
inputs hold the best qualities for each pc for hitting the minimum and
maximum unique pcs while needing the least values.
Once all an input's qualities have been superseded for the pcs it hit,
it is removed from the corpus.
-- Comparison to byte-based smith
A byte-based smith would be much more inefficient and complex than this
solution. It would be unable to solve the shifting problem that Uids
do. It is unable to provide values from the fuzzer past end-of-stream.
Even with feedback, it would be unable to act on dynamic weights which
have proven essential with the updated tests (e.g. to constrain values
to a range).
-- Test updates
All the standard library tests have been updated to use the new smith
interface. For `Deque`, an ad hoc allocator was written to improve
performance and remove reliance on heap allocation. `TokenSmith` has
been added to aid in testing Ast and help inform decisions on the smith
interface.
This PR significantly improves the capabilities of the fuzzer.
The changes made to the fuzzer to accomplish this feat mostly include
tracking memory reads from .rodata to determine fresh inputs, new
mutations (especially the ones that insert const values from .rodata
reads and __sanitizer_conv_const_cmp), and minimizing found inputs.
Additionally, the runs per second has greatly been increased due to
generating smaller inputs and avoiding clearing the 8-bit pc counters.
An additional feature added is that the length of the input file is now
stored and the old input file is rerun upon start.
Other changes made to the fuzzer include more logical initialization,
using one shared file `in` for inputs, creating corpus files with
proper sizes, and using hexadecimal-numbered corpus files for
simplicity.
Furthermore, I added several new fuzz tests to gauge the fuzzer's
efficiency. I also tried to add a test for zstandard decompression,
which it crashed within 60,000 runs (less than a second.)
Bug fixes include:
* Fixed a race conditions when multiple fuzzer processes needed to use
the same coverage file.
* Web interface stats now update even when unique runs is not changing.
* Fixed tokenizer.testPropertiesUpheld to allow stray carriage returns
since they are valid whitespace.
