Full accounting of memory used by the library.
Change `ndpi_realloc()` prototype to be compatible with standard
`realloc()`.
Be compatible with croaring allocation logic.
Note that aligned allocations are used only by croaring code.
Note that flow allocations are used only by the application, not by the
library.
API changes:
* remove `set_ndpi_malloc()` and `set_ndpi_free()`; use
`ndpi_set_memory_alloction_functions()` instead
The main goal is not to have the bitmask depending on the total number
of protocols anymore: `NDPI_INTERNAL_PROTOCOL_BITMASK` depends only on
internal protocols, i.e. on `NDPI_MAX_INTERNAL_PROTOCOLS`, i.e.
custom-defined protocols are not counted.
See #2136
Keep the old data structure `NDPI_PROTOCOL_BITMASK` with the old
semantic.
Since we need to change the API (and all the application code...)
anyway, simplify the API: by default all the protocols are enabled.
If you need otherwise, please use `ndpi_init_detection_module_ext()`
instead of `ndpi_init_detection_module()` (you can find an example in
the `ndpiReader` code).
To update the application code you likely only need to remove these 3
lines from your code:
```
- NDPI_PROTOCOL_BITMASK all;
- NDPI_BITMASK_SET_ALL(all);
- ndpi_set_protocol_detection_bitmask2(ndpi_str, &all);
```
Removed an unused field and struct definition.
It might be usefull to be able to match traffic against a list of
suspicious JA4C fingerprints
Use the same code/logic/infrastructure used for JA3C (note that we are
going to remove JA3C...)
See: #2551
Add the concept of "global context".
Right now every instance of `struct ndpi_detection_module_struct` (we
will call it "local context" in this description) is completely
independent from each other. This provide optimal performances in
multithreaded environment, where we pin each local context to a thread,
and each thread to a specific CPU core: we don't have any data shared
across the cores.
Each local context has, internally, also some information correlating
**different** flows; something like:
```
if flow1 (PeerA <-> Peer B) is PROTOCOL_X; then
flow2 (PeerC <-> PeerD) will be PROTOCOL_Y
```
To get optimal classification results, both flow1 and flow2 must be
processed by the same local context. This is not an issue at all in the far
most common scenario where there is only one local context, but it might
be impractical in some more complex scenarios.
Create the concept of "global context": multiple local contexts can use
the same global context and share some data (structures) using it.
This way the data correlating multiple flows can be read/write from
different local contexts.
This is an optional feature, disabled by default.
Obviously data structures shared in a global context must be thread safe.
This PR updates the code of the LRU implementation to be, optionally,
thread safe.
Right now, only the LRU caches can be shared; the other main structures
(trees and automas) are basically read-only: there is little sense in
sharing them. Furthermore, these structures don't have any information
correlating multiple flows.
Every LRU cache can be shared, independently from the others, via
`ndpi_set_config(ndpi_struct, NULL, "lru.$CACHE_NAME.scope", "1")`.
It's up to the user to find the right trade-off between performances
(i.e. without shared data) and classification results (i.e. with some
shared data among the local contexts), depending on the specific traffic
patterns and on the algorithms used to balance the flows across the
threads/cores/local contexts.
Add some basic examples of library initialization in
`doc/library_initialization.md`.
This code needs libpthread as external dependency. It shouldn't be a big
issue; however a configure flag has been added to disable global context
support. A new CI job has been added to test it.
TODO: we should need to find a proper way to add some tests on
multithreaded enviroment... not an easy task...
*** API changes ***
If you are not interested in this feature, simply add a NULL parameter to
any `ndpi_init_detection_module()` calls.
Some changes in the parameters names.
Add a fuzzer to fuzz the configuration file format.
Add the infrastructure to configuratin callbacks.
Add an helper to map LRU cache indexes to names.
This is the first step into providing (more) configuration options in nDPI.
The idea is to have a simple way to configure (most of) nDPI: only one
function (`ndpi_set_config()`) to set any configuration parameters
(in the present or on in the future) and we try to keep this function
prototype as agnostic as possible.
You can configure the library:
* via API, using `ndpi_set_config()`
* via a configuration file, in a text format
This way, anytime we need to add a new configuration parameter:
* we don't need to add two public functions (a getter and a setter)
* we don't break API/ABI compatibility of the library; even changing
the parameter type (from integer to a list of integer, for example)
doesn't break the compatibility.
The complete list of configuration options is provided in
`doc/configuration_parameters.md`.
As a first example, two configuration knobs are provided:
* the ability to enable/disable the extraction of the sha1 fingerprint of
the TLS certificates.
* the upper limit on the number of packets per flow that will be subject
to inspection
Start using a dictionary for fuzzing (see:
https://llvm.org/docs/LibFuzzer.html#dictionaries).
Remove some dead code.
Fuzzing with debug enabled is not usually a great idea (from performance
POV). Keep the code since it might be useful while debugging.
The goal of this fuzzer is to test init and deinit of the library, with
different configurations. In details:
* random memory allocation failures, even during init phase
* random `ndpi_init_prefs` parameter of `ndpi_init_detection_module()`
* random LRU caches sizes
* random bitmask of enabled protocols
* random parameters of `ndpi_set_detection_preferences()`
* random initialization of opportunistic TLS
* random load/don't load of configuration files
This new fuzzer is a C++ file, because it uses `FuzzedDataProvider`
class (see
https://github.com/google/fuzzing/blob/master/docs/split-inputs.md).
Note that the (existing) fuzzers need to be linked with C++ compiler
anyway, so this new fuzzer doesn't add any new requirements.
Load some custom configuration (like in the unit tests) and factorize some
(fuzzing) common code.
There is no way to pass file paths to the fuzzers as parameters. The safe
solution seems to be to load them from the process working dir. Anyway,
missing file is not a blocking error.
Remove some dead code (found looking at the coverage report)
