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For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Quite 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 may use. The Protocol Safety Analysis staff on the Ethereum Basis had the chance to assessment 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 approach 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 have been already well-integrated with LLVM mission’s different choices.
Here is the fuzzer for verify_kzg_proof, one in every of c-kzg-4844’s capabilities:
#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 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, one thing is unsuitable. This system could be very fashionable in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification offers an additional degree of security, figuring out that if one implementation have been flawed the others might not have the identical challenge.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by its Golang bindings) and go-kzg-4844. To date, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from operating the checks. It is a nice strategy to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of how one 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 prime and the non-exported (static) capabilities are on the underside.
There’s a whole lot of inexperienced within the desk above, however there’s some yellow and purple too. To find out what’s and is not being executed, confer with the HTML file (protection.html) that was generated. This webpage reveals the whole supply file and highlights non-executed code in purple. On this mission’s case, a lot of the non-executed code offers with hard-to-test error circumstances comparable to reminiscence allocation failures. For instance, here is some non-executed code:
Originally of this perform, it checks that the trusted setup is sufficiently big to carry out a pairing verify. 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 proper trusted setup, the results of is_monomial_form is all the time the identical and would not return the error worth.
Profile
We do not suggest this for all initiatives, however since c-kzg-4844 is a efficiency crucial library we predict it is essential 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 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 from time to time. 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.
#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 predominant(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 may then use pprof to visualise this knowledge.
Right here is the graph generated from the command above:
Here is an even bigger instance from one in every of 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) device comparable to Ghidra or IDA. These instruments can assist you perceive how high-level constructs are translated into low-level machine code. We expect it helps to assessment your code this fashion; like how studying a paper in a distinct font will pressure your mind to interpret sentences in another 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 an eye fixed out for this, one thing like this truly occurred in c-kzg-4844, some of the tests were being optimized out.
While you view a decompiled perform, 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 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 positive. It could assist to construct your binary with DWARF debugging info; 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 slightly work, you’ll be able to 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 establish 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 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 utterly legitimate code.
#embrace <stdlib.h> int predominant(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, however it is smart if you consider it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not all the 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 sudden enter, it was doable 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 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 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.
Tackle
AddressSanitizer (ASan) is a quick reminiscence error detector which may 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. It is a easy instance of a heap-buffer-overflow:
#embrace <stdlib.h> int predominant(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it’ll output the next error message. This factors you in a great route (a 4-byte write in predominant). This binary might be seen in a disassembler to determine precisely which instruction (at predominant+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int predominant(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 predominant+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int predominant(void) { 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 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.
#embrace <limits.h> int predominant(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 circumstances 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 case introduces unpredictability and may result in undefined conduct. Here is an instance wherein 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.
#embrace <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int predominant(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 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 finest identified for figuring out reminiscence errors and leaks with its built-in Memcheck device.
The next picture reveals the output from operating c-kzg-4844’s checks with Valgrind. Within the purple field is a legitimate discovering for a “conditional leap or transfer [that] is dependent upon uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the unsuitable root of unity or width have been offered, it was doable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate verify would depend 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 Overview
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 would possibly not be a stamp of approval, however it reveals that your mission is no less than considerably safe. Take into accout there is no such thing as 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 comprises 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 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 beneficial properties, like it’s for Ethereum, contemplate organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability stories in trade for cash. Typically, 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 relatively than exploiting it or promoting it to a different social gathering. We suggest 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 strong C initiatives, particularly within the crucial area of blockchain and cryptocurrencies, requires a multi-faceted method. Given the inherent vulnerabilities related to the C language, a mix of finest practices and instruments is crucial for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present useful insights and finest practices for others embarking on comparable initiatives.
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