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 thought was to create a strong and environment friendly cryptographic library that each one purchasers may use. The Protocol Safety Analysis staff 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 widespread 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 mission’s different choices.
Here is the fuzzer for verify_kzg_proof, certainly one of c-kzg-4844’s features:
#embrace "../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* knowledge, size_t dimension) { initialize(); if (dimension == 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 seems like. If there have been an issue, it could write the enter to disk and cease executing. Ideally, it’s best to be capable of 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 completely different, and also you anticipated them to be the identical, you realize one thing is improper. This method may be very widespread in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification supplies an additional stage of security, understanding that if one implementation had been flawed the others could not have the identical difficulty.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (via 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 assessments. This can be a nice approach to confirm code is executed (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of the way 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 features are on the high and the non-exported (static) features are on the underside.
There may be lots of inexperienced within the desk above, however there’s some yellow and pink too. To find out what’s and is not being executed, discuss with the HTML file (protection.html) that was generated. This webpage exhibits your 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 instances reminiscent of reminiscence allocation failures. For instance, this is some non-executed code:
At the start of this operate, 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 right 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 tasks, however since c-kzg-4844 is a efficiency crucial library we predict it is essential to profile its exported features and measure how lengthy they take to execute. This may help determine inefficiencies which may doubtlessly 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 occasionally. If a operate is quick sufficient, it might not be 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.
#embrace <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 fundamental(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 is going to 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 a much bigger instance from certainly one of c-kzg-4844’s features. 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) device reminiscent of Ghidra or IDA. These instruments may help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to assessment your code this manner; 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 generally the compiler will optimize out one thing which it deemed pointless. Maintain a watch out for this, one thing like this truly occurred in c-kzg-4844, some of the tests were being optimized out.
If you view a decompiled operate, it is not going to have variable names, complicated varieties, 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 typically see features 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 completely different. These are simply compiler optimizations and are typically nice. It might 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 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 appear to be after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation device 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 rather a lot quicker than “dynamic” evaluation instruments which execute code.
Here is a easy instance which forgets to free arr (and has one other drawback however we’ll speak extra about that later). The compiler is not going to determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embrace <stdlib.h> int fundamental(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 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 mission:
Given an surprising enter, it was potential 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 unimaginable. 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 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 simple to make use of.
Deal with
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 similar instance from earlier. It forgets to free arr and it’ll set the sixth ingredient in a 5 ingredient array. This can be a easy instance of a heap-buffer-overflow:
#embrace <stdlib.h> int fundamental(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=tackle and executed, it is going to output the next error message. This factors you in a great course (a 4-byte write in fundamental). This binary could possibly be seen in a disassembler to determine precisely which instruction (at fundamental+0x84) is inflicting the issue.
Equally, this is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int fundamental(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 fundamental+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int fundamental(void) { int knowledge[2]; return knowledge[0]; }
When compiled with -fsanitize=reminiscence and executed, it is going to output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the state of affairs the place a program’s conduct is unpredictable and never specified by the langauge commonplace. 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.
#embrace <limits.h> int fundamental(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it is 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 knowledge races, which may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the identical time. This example 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 completely potential that these two threads will increment the variable on the identical time.
#embrace <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int fundamental(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 is going to 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 identical 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 device.
The next picture exhibits the output from operating c-kzg-4844’s assessments with Valgrind. Within the pink field is a legitimate discovering for a “conditional bounce or transfer [that] is determined by uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the improper root of unity or width had been offered, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate test would rely upon 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 Evaluation
After improvement stabilizes, it has been totally examined, and your staff has manually reviewed the codebase themselves a number of instances, it is time to get a safety assessment by a good safety group. This may not be a stamp of approval, however it exhibits that your mission is a minimum of considerably safe. Take into account there is no such thing as a such factor as good 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 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 mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your mission could possibly be exploited for beneficial properties, like it’s for Ethereum, take into account establishing a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability reviews in trade for cash. Typically, that is particularly for findings which may show that an exploit is feasible. If the bug bounty payouts are affordable, bug finders will notify you of the bug slightly than exploiting it or promoting it to a different get together. We advocate beginning your bug bounty program after the findings from the primary safety assessment are resolved; ideally, the safety assessment would price 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 mix 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 helpful insights and greatest practices for others embarking on related tasks.
