For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Fairly than every consumer rolling their very own crypto, researchers and builders got here collectively to jot down c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The thought was to create a sturdy and environment friendly cryptographic library that each one shoppers may use. The Protocol Safety Analysis workforce on the Ethereum Basis had the chance to evaluate and enhance this library. This weblog submit will talk about some issues we do to make C initiatives safer.
Fuzz
Fuzzing is a dynamic code testing method that includes offering random inputs to find bugs in a program. LibFuzzer and afl++ are two fashionable fuzzing frameworks for C initiatives. They’re each in-process, coverage-guided, evolutionary fuzzing engines. For c-kzg-4844, we used LibFuzzer since we had been already well-integrated with LLVM undertaking’s different choices.
Here is the fuzzer for verify_kzg_proof, one in all c-kzg-4844’s capabilities:
static const size_t COMMITMENT_OFFSET = 0;
static const size_t Z_OFFSET = COMMITMENT_OFFSET + BYTES_PER_COMMITMENT;
static const size_t Y_OFFSET = Z_OFFSET + BYTES_PER_FIELD_ELEMENT;
static const size_t PROOF_OFFSET = Y_OFFSET + BYTES_PER_FIELD_ELEMENT;
static const size_t INPUT_SIZE = PROOF_OFFSET + BYTES_PER_PROOF;
int LLVMFuzzerTestOneInput(const uint8_t* information, size_t dimension) {
initialize();
if (dimension == INPUT_SIZE) {
bool okay;
verify_kzg_proof(
&okay,
(const Bytes48 *)(information + COMMITMENT_OFFSET),
(const Bytes32 *)(information + Z_OFFSET),
(const Bytes32 *)(information + Y_OFFSET),
(const Bytes48 *)(information + PROOF_OFFSET),
&s
);
}
return 0;
}
When executed, that is what the output appears like. If there have been an issue, it could write the enter to disk and cease executing. Ideally, you must be capable to reproduce the issue.
There’s additionally differential fuzzing, which is a way which fuzzes two or extra implementations of the identical interface and compares the outputs. For a given enter, if the output is totally different, and also you anticipated them to be the identical, you recognize one thing is incorrect. This method could be very fashionable in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification offers an additional stage of security, understanding that if one implementation had been flawed the others could not have the identical concern.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of its Golang bindings) and go-kzg-4844. To this point, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from working the checks. This can be a nice technique to confirm code is executed (“coated”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of generate this report.
When this goal is run (i.e., make protection) it produces a desk that serves as a high-level overview of how a lot of every perform is executed. The exported capabilities are on the high and the non-exported (static) capabilities are on the underside.
There’s a whole lot of inexperienced within the desk above, however there may be some yellow and purple too. To find out what’s and is not being executed, seek advice from the HTML file (protection.html) that was generated. This webpage reveals your entire supply file and highlights non-executed code in purple. On this undertaking’s case, many of the non-executed code offers with hard-to-test error instances similar to reminiscence allocation failures. For instance, here is some non-executed code:
Firstly of this perform, it checks that the trusted setup is sufficiently big to carry out a pairing test. There is not a check case which offers an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check with the right trusted setup, the results of is_monomial_form is all the time the identical and does not return the error worth.
Profile
We do not advocate this for all initiatives, however since c-kzg-4844 is a efficiency crucial library we predict it is vital to profile its exported capabilities and measure how lengthy they take to execute. This can assist establish inefficiencies which may probably DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as an alternative of llvm-xray as a result of we discovered it to be extra feature-rich and simpler to make use of.
The next is an easy instance which profiles my_function. Profiling works by checking which instruction is being executed now and again. If a perform is quick sufficient, it might not be observed by the profiler. To cut back the prospect of this, you might have to name your perform a number of instances. On this instance, we name my_function 1000 instances.
int task_a(int n) {
if (n <= 1) return 1;
return task_a(n – 1) * n;
}
int task_b(int n) {
if (n <= 1) return 1;
return task_b(n – 2) + n;
}
void my_function(void) {
for (int i = 0; i < 500; i++) {
if (i % 2 == 0) {
task_a(i);
} else {
task_b(i);
}
}
}
int primary(void) {
ProfilerStart(“instance.prof”);
for (int i = 0; i < 1000; i++) {
my_function();
}
ProfilerStop();
return 0;
}
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which components of your program to profile. When re-compiled and executed, it’s going to write a file to disk with profiling information. You possibly can then use pprof to visualise this information.
Right here is the graph generated from the command above:
Here is a much bigger instance from one in all c-kzg-4844’s capabilities. The next picture is the profiling graph for compute_blob_kzg_proof. As you possibly can see, 80% of this perform’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) device similar to Ghidra or IDA. These instruments can assist you perceive how high-level constructs are translated into low-level machine code. We predict it helps to evaluate your code this manner; like how studying a paper in a distinct font will power your mind to interpret sentences in a different way. It is also helpful to see what kind of optimizations your compiler makes. It is uncommon, however typically the compiler will optimize out one thing which it deemed pointless. Hold a watch out for this, one thing like this truly occurred in c-kzg-4844, among the checks had been being optimized out.
If you view a decompiled perform, it won’t have variable names, complicated sorts, or feedback. When compiled, this data is not included within the binary. It will likely be as much as you to reverse engineer this. You will usually see capabilities are inlined right into a single perform, a number of variables declared in code are optimized right into a single buffer, and the order of checks are totally different. These are simply compiler optimizations and are typically fantastic. It could assist to construct your binary with DWARF debugging data; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears like in Ghidra:
With a bit of work, you possibly can rename variables and add feedback to make it simpler to learn. Here is what it may seem like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a wonderful static evaluation device that may establish many issues that the compiler will miss. Because the identify “static” suggests, it examines code with out executing it. That is slower than the compiler, however loads quicker than “dynamic” evaluation instruments which execute code.
Here is a easy instance which forgets to free arr (and has one other downside however we’ll discuss extra about that later). The compiler won’t establish this, even with all warnings enabled as a result of technically that is fully legitimate code.
int primary(void) {
int* arr = malloc(5 * sizeof(int));
arr[5] = 42;
return 0;
}
The unix.Malloc checker will establish that arr wasn’t freed. The road within the warning message is a bit deceptive, nevertheless it is smart if you consider it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not the entire findings are that straightforward although. Here is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the undertaking:
Given an sudden enter, it was attainable to shift this worth by 32 bits which is undefined conduct. The answer was to limit the enter with CHECK(log2_pow2(n) != 0) in order that this was not possible. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to packages which might level out points throughout execution. These are notably helpful at discovering frequent errors related to reminiscence dealing with. Clang comes built-in with a number of sanitizers; listed here are the 4 we discover most helpful and straightforward to make use of.
Handle
AddressSanitizer (ASan) is a quick reminiscence error detector which might establish out-of-bounds accesses, use-after-free, use-after-return, use-after-scope, double-free, and reminiscence leaks.
Right here is similar instance from earlier. It forgets to free arr and it’ll set the sixth component in a 5 component array. This can be a easy instance of a heap-buffer-overflow:
int primary(void) {
int* arr = malloc(5 * sizeof(int));
arr[5] = 42;
return 0;
}
When compiled with -fsanitize=deal with and executed, it’s going to output the next error message. This factors you in a superb route (a 4-byte write in primary). This binary may very well be considered in a disassembler to determine precisely which instruction (at primary+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
int primary(void) {
int *arr = malloc(5 * sizeof(int));
free(arr);
return arr[2];
}
It tells you that there is a 4-byte learn of freed reminiscence at primary+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int information[2];
return information[0];
}
When compiled with -fsanitize=reminiscence and executed, it’s going to output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the scenario the place a program’s conduct is unpredictable and never specified by the langauge customary. Some frequent examples of this are accessing out-of-bounds reminiscence, dereferencing an invalid pointer, studying uninitialized variables, and overflow of a signed integer. For instance, right here we increment INT_MAX which is undefined conduct.
int primary(void) {
int a = INT_MAX;
return a + 1;
}
When compiled with -fsanitize=undefined and executed, it’s going to output the next error message which tells us precisely the place the issue is and what the situations are:
Thread
ThreadSanitizer (TSan) detects information races, which might happen in multi-threaded packages when two or extra threads entry a shared reminiscence location on the similar time. This case introduces unpredictability and may result in undefined conduct. Here is an instance through which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is totally attainable that these two threads will increment the variable on the similar time.
int counter = 0;
void *increment(void *arg) {
(void)arg;
for (int i = 0; i < 1000000; i++)
counter++;
return NULL;
}
int primary(void) {
pthread_t thread1, thread2;
pthread_create(&thread1, NULL, increment, NULL);
pthread_create(&thread2, NULL, increment, NULL);
pthread_join(thread1, NULL);
pthread_join(thread2, NULL);
return 0;
}
When compiled with -fsanitize=thread and executed, it’s going to output the next error message:
This error message tells us that there is a information race. In two threads, the increment perform is writing to the identical 4 bytes on the similar time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a strong instrumentation framework for constructing dynamic evaluation instruments, however its finest identified for figuring out reminiscence errors and leaks with its built-in Memcheck device.
The next picture reveals the output from working c-kzg-4844’s checks with Valgrind. Within the purple field is a sound discovering for a “conditional leap or transfer [that] is dependent upon uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the incorrect root of unity or width had been supplied, it was attainable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate test would depend upon an uninitialized worth.
fr_t *out, const fr_t *root, uint64_t width
) {
out[0] = FR_ONE;
out[1] = *root;
for (uint64_t i = 2; !fr_is_one(&out[i – 1]); i++) {
CHECK(i <= width);
blst_fr_mul(&out[i], &out[i – 1], root);
}
CHECK(fr_is_one(&out[width]));
return C_KZG_OK;
}
Safety Overview
After growth stabilizes, it has been completely examined, and your workforce has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluate by a good safety group. This would possibly not be a stamp of approval, nevertheless it reveals that your undertaking is no less than considerably safe. Take into account there isn’t a such factor as good safety. There’ll all the time be the danger of vulnerabilities.
For c-kzg-4844 and go-kzg-4844, the Ethereum Basis contracted Sigma Prime to conduct a safety evaluate. They produced this report with 8 findings. It incorporates one crucial vulnerability in go-kzg-4844 that was a very good discover. The BLS12-381 library that go-kzg-4844 makes use of, gnark-crypto, had a bug which allowed invalid G1 and G2 factors to be sucessfully decoded. Had this not been mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your undertaking may very well be exploited for good points, like it’s for Ethereum, contemplate establishing a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability studies in change for cash. Usually, that is particularly for findings which might show that an exploit is feasible. If the bug bounty payouts are affordable, bug finders will notify you of the bug somewhat than exploiting it or promoting it to a different social gathering. We advocate beginning your bug bounty program after the findings from the primary safety evaluate are resolved; ideally, the safety evaluate would price lower than the bug bounty payouts.
Conclusion
The event of sturdy C initiatives, particularly within the crucial area of blockchain and cryptocurrencies, requires a multi-faceted strategy. Given the inherent vulnerabilities related to the C language, a mixture of finest practices and instruments is important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present invaluable insights and finest practices for others embarking on related initiatives.
