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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 concept was to create a sturdy and environment friendly cryptographic library that every one shoppers might use. The Protocol Safety Analysis group on the Ethereum Basis had the chance to assessment and enhance this library. This weblog put up will talk about some issues we do to make C tasks 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 in style fuzzing frameworks for C tasks. 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, certainly one of 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* knowledge, size_t measurement) {
initialize();
if (measurement == INPUT_SIZE) {
bool okay;
verify_kzg_proof(
&okay,
(const Bytes48 *)(knowledge + COMMITMENT_OFFSET),
(const Bytes32 *)(knowledge + Z_OFFSET),
(const Bytes32 *)(knowledge + Y_OFFSET),
(const Bytes48 *)(knowledge + PROOF_OFFSET),
&s
);
}
return 0;
}
When executed, that is what the output appears to be like like. If there have been an issue, it will write the enter to disk and cease executing. Ideally, it’s best to be capable to reproduce the issue.
There’s additionally differential fuzzing, which is a method 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 already know one thing is improper. This system may be very in style in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification offers an additional stage of security, figuring out that if one implementation had been flawed the others could not have the identical problem.
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 strategy to confirm code is executed (“coated”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of easy methods to 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 operate is executed. The exported capabilities are on the high and the non-exported (static) capabilities are on the underside.
There may be quite a 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, consult with the HTML file (protection.html) that was generated. This webpage reveals the complete supply file and highlights non-executed code in purple. On this undertaking’s case, a lot of the non-executed code offers with hard-to-test error circumstances comparable to reminiscence allocation failures. For instance, this is some non-executed code:
In the beginning of this operate, it checks that the trusted setup is large enough to carry out a pairing test. There is not a take a look at case which offers an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely take a look at with the proper 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 tasks, however since c-kzg-4844 is a efficiency crucial library we expect it is essential to profile its exported capabilities and measure how lengthy they take to execute. This may also help determine inefficiencies which might probably DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as a substitute of llvm-xray as a result of we discovered it to be extra feature-rich and simpler to make use of.
The next is a straightforward instance which profiles my_function. Profiling works by checking which instruction is being executed every now and then. If a operate is quick sufficient, it is probably not observed by the profiler. To scale back the prospect of this, you could have to name your operate 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 essential(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’ll write a file to disk with profiling knowledge. You possibly can then use pprof to visualise this knowledge.
Right here is the graph generated from the command above:
Here is an even bigger instance from certainly one of 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 operate’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) instrument comparable to Ghidra or IDA. These instruments may also help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to assessment your code this fashion; like how studying a paper in a special font will power your mind to interpret sentences in another way. It is also helpful to see what sort of optimizations your compiler makes. It is uncommon, however generally the compiler will optimize out one thing which it deemed pointless. Maintain a watch out for this, one thing like this really occurred in c-kzg-4844, among the checks had been being optimized out.
While you view a decompiled operate, it won’t have variable names, complicated sorts, or feedback. When compiled, this info 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 operate, 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 usually advantageous. It could assist to construct your binary with DWARF debugging info; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears to be like like in Ghidra:
With just a little work, you possibly can rename variables and add feedback to make it simpler to learn. Here is what it might appear like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation instrument that may determine many issues that the compiler will miss. Because the title “static” suggests, it examines code with out executing it. That is slower than the compiler, however so much sooner than “dynamic” evaluation instruments which execute code.
Here is a easy instance which forgets to free arr (and has one other downside however we are going to speak extra about that later). The compiler won’t determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
int essential(void) {
int* arr = malloc(5 * sizeof(int));
arr[5] = 42;
return 0;
}
The unix.Malloc checker will determine that arr wasn’t freed. The road within the warning message is a bit deceptive, but it surely is smart if you concentrate on it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not the entire findings are that easy 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 habits. The answer was to limit the enter with CHECK(log2_pow2(n) != 0) in order that this was unattainable. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to applications which may level out points throughout execution. These are notably helpful at discovering widespread 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 simple to make use of.
Tackle
AddressSanitizer (ASan) is a quick reminiscence error detector which may determine out-of-bounds accesses, use-after-free, use-after-return, use-after-scope, double-free, and reminiscence leaks.
Right here is identical 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 essential(void) {
int* arr = malloc(5 * sizeof(int));
arr[5] = 42;
return 0;
}
When compiled with -fsanitize=deal with and executed, it’ll output the next error message. This factors you in an excellent route (a 4-byte write in essential). This binary may very well be considered in a disassembler to determine precisely which instruction (at essential+0x84) is inflicting the issue.
Equally, this is an instance the place it finds a heap-use-after-free:
int essential(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 essential+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int knowledge[2];
return knowledge[0];
}
When compiled with -fsanitize=reminiscence and executed, it’ll output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined habits, which refers back to the state of affairs the place a program’s habits is unpredictable and never specified by the langauge customary. Some widespread 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 habits.
int essential(void) {
int a = INT_MAX;
return a + 1;
}
When compiled with -fsanitize=undefined and executed, it’ll output the next error message which tells us precisely the place the issue is and what the situations are:
Thread
ThreadSanitizer (TSan) detects knowledge races, which may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the similar time. This example introduces unpredictability and may result in undefined habits. Here is an instance through which two threads increment a world counter variable. There are not any locks or semaphores, so it is completely 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 essential(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’ll output the next error message:
This error message tells us that there is a knowledge race. In two threads, the increment operate is writing to the identical 4 bytes on the similar time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a robust instrumentation framework for constructing dynamic evaluation instruments, however its greatest recognized for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture reveals the output from working c-kzg-4844’s checks with Valgrind. Within the purple field is a legitimate discovering for a “conditional bounce or transfer [that] relies on uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the improper root of unity or width had been offered, it was attainable that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate test would rely on 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 Evaluation
After improvement stabilizes, it has been totally examined, and your group has manually reviewed the codebase themselves a number of instances, it is time to get a safety assessment by a good safety group. This would possibly not be a stamp of approval, but it surely reveals that your undertaking is no less than considerably safe. Take into accout there isn’t a such factor as excellent 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 assessment. They produced this report with 8 findings. It incorporates one crucial vulnerability in go-kzg-4844 that was a extremely 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 fastened, 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 beneficial properties, like it’s for Ethereum, take into account organising 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 may show that an exploit is feasible. If the bug bounty payouts are cheap, bug finders will notify you of the bug somewhat than exploiting it or promoting it to a different occasion. We advocate beginning your bug bounty program after the findings from the primary safety assessment are resolved; ideally, the safety assessment would value lower than the bug bounty payouts.
Conclusion
The event of sturdy C tasks, 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 greatest practices and instruments is crucial for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present beneficial insights and greatest practices for others embarking on comparable tasks.
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