For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Somewhat 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 strong and environment friendly cryptographic library that every one purchasers 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 focus on 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 common fuzzing frameworks for C initiatives. They’re each in-process, coverage-guided, evolutionary fuzzing engines. For c-kzg-4844, we used LibFuzzer since we have been already well-integrated with LLVM mission’s different choices.

This is the fuzzer for verify_kzg_proof, one among c-kzg-4844’s capabilities:

#embody "../base_fuzz.h"

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 measurement) {
    initialize();
    if (measurement == 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 seems to be like. If there have been an issue, it might 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 unsuitable. This method could be very common in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification supplies an additional stage of security, understanding that if one implementation have been flawed the others could not have the identical difficulty.

For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means 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 operating the checks. This can be a nice method to confirm code is executed (“coated”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of how you can 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 plenty of inexperienced within the desk above, however there’s some yellow and pink too. To find out what’s and is not being executed, check with the HTML file (protection.html) that was generated. This webpage exhibits the complete supply file and highlights non-executed code in pink. On this mission’s case, a lot of the non-executed code offers with hard-to-test error circumstances equivalent to reminiscence allocation failures. For instance, this is some non-executed code:

Originally 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 supplies an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check with the proper trusted setup, the results of is_monomial_form is at all times 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 essential library we predict it is vital to profile its exported capabilities and measure how lengthy they take to execute. This may 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 an easy instance which profiles my_function. Profiling works by checking which instruction is being executed once in a while. If a perform is quick sufficient, it might not be observed by the profiler. To scale back the possibility of this, chances are you’ll must name your perform a number of instances. On this instance, we name my_function 1000 instances.

#embody <gperftools/profiler.h>

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 would write a file to disk with profiling information. You’ll be able to then use pprof to visualise this information.

Right here is the graph generated from the command above:

This is a much bigger instance from one among c-kzg-4844’s capabilities. The next picture is the profiling graph for compute_blob_kzg_proof. As you’ll be able to 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) software equivalent to Ghidra or IDA. These instruments may 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 unique font will drive 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. Preserve an eye fixed out for this, one thing like this truly occurred in c-kzg-4844, a number of the checks have been being optimized out.

If you view a decompiled perform, it is not going to have variable names, advanced 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 may 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 usually tremendous. It could assist to construct your binary with DWARF debugging data; most SREs can analyze this part to offer higher outcomes.

For instance, that is what blob_to_kzg_commitment initially seems to be like in Ghidra:

With a bit of work, you’ll be able to rename variables and add feedback to make it simpler to learn. This is what it might seem like after a couple of minutes:

Static Evaluation

Clang comes built-in with the Clang Static Analyzer, which is a wonderful static evaluation software that may determine 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 lots sooner than “dynamic” evaluation instruments which execute code.

This is a easy instance which forgets to free arr (and has one other drawback however we are going to discuss extra about that later). The compiler is not going to determine this, even with all warnings enabled as a result of technically that is utterly legitimate code.

#embody <stdlib.h>

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, however it is sensible 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 straightforward although. This is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the mission:

Given an sudden enter, it was doable 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 unimaginable. Good job, Clang Static Analyzer!

Sanitize

Santizers are dynamic evaluation instruments which instrument (add directions) to applications 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 below are the 4 we discover most helpful and simple to make use of.

Handle

AddressSanitizer (ASan) is a quick reminiscence error detector which might determine 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 factor in a 5 factor array. This can be a easy instance of a heap-buffer-overflow:

#embody <stdlib.h>

int essential(void) {
    int* arr = malloc(5 * sizeof(int));
    arr[5] = 42;
    return 0;
}

When compiled with -fsanitize=handle and executed, it would output the next error message. This factors you in a great course (a 4-byte write in essential). This binary might be seen 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:

#embody <stdlib.h>

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. This is a easy instance which reads (and returns) an uninitialized worth:

int essential(void) {
    int information[2];
    return information[0];
}

When compiled with -fsanitize=reminiscence and executed, it would output the next error message:

Undefined Habits

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 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 habits.

#embody <limits.h>

int essential(void) {
    int a = INT_MAX;
    return a + 1;
}

When compiled with -fsanitize=undefined and executed, it would 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 applications when two or extra threads entry a shared reminiscence location on the similar time. This case introduces unpredictability and might result in undefined habits. This is an instance during which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is solely doable that these two threads will increment the variable on the similar time.

#embody <pthread.h>

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 would 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 robust instrumentation framework for constructing dynamic evaluation instruments, however its greatest recognized for figuring out reminiscence errors and leaks with its built-in Memcheck software.

The next picture exhibits the output from operating c-kzg-4844’s checks with Valgrind. Within the pink field is a sound discovering for a “conditional leap or transfer [that] relies on uninitialized worth(s).”

This recognized an edge case in expand_root_of_unity. If the unsuitable root of unity or width have been supplied, it was doable 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.

static C_KZG_RET expand_root_of_unity(
    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 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, however it exhibits that your mission is a minimum of considerably safe. Bear in mind there isn’t a such factor as excellent safety. There’ll at all times be the chance 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 comprises one essential 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 mission might be exploited for positive factors, like it’s for Ethereum, think about establishing a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability reviews 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 quite than exploiting it or promoting it to a different celebration. 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 strong C initiatives, particularly within the essential area of blockchain and cryptocurrencies, requires a multi-faceted method. Given the inherent vulnerabilities related to the C language, a mixture of greatest practices and instruments is important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present useful insights and greatest practices for others embarking on related initiatives.