For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Slightly than every shopper 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 shoppers might use. The Protocol Safety Analysis crew 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 approach that includes offering random inputs to find bugs in a program. LibFuzzer and afl++ are two common fuzzing frameworks for C tasks. 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 challenge’s different choices.
This is the fuzzer for verify_kzg_proof, one in every of 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* 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 like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, it is 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 totally different, and also you anticipated them to be the identical, one thing is flawed. This method may be very common 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 have been flawed the others might not have the identical situation.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of its Golang bindings) and go-kzg-4844. Up to now, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from working the assessments. It is a nice strategy to confirm code is executed (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of the best 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 capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There may be loads of inexperienced within the desk above, however there’s some yellow and crimson 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 crimson. On this challenge’s case, many of the non-executed code offers with hard-to-test error instances equivalent to reminiscence allocation failures. For instance, here is some non-executed code:
At the start of this operate, it checks that the trusted setup is large enough 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 tasks, however since c-kzg-4844 is a efficiency important 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 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 once in a while. If a operate is quick sufficient, it will not be observed by the profiler. To cut back the possibility of this, you might must name your operate a number of occasions. On this instance, we name my_function 1000 occasions.
#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 elements of your program to profile. When re-compiled and executed, it should 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:
This is a much 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 may 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 equivalent 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 assessment your code this manner; like how studying a paper in a distinct font will drive your mind to interpret sentences otherwise. 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. Preserve an eye fixed out for this, one thing like this truly occurred in c-kzg-4844, some of the tests were being optimized out.
Whenever you view a decompiled operate, it is not going to have variable names, advanced varieties, or feedback. When compiled, this info is not included within the binary. Will probably be as much as you to reverse engineer this. You may 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 typically fantastic. It might 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 appears like in Ghidra:
With just a little work, you may rename variables and add feedback to make it simpler to learn. This is what it might 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 lots sooner than “dynamic” evaluation instruments which execute code.
This is a easy instance which forgets to free arr (and has one other downside however we’ll speak extra about that later). The compiler is not going to establish this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embody <stdlib.h> int essential(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 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 challenge:
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 packages which may level out points throughout execution. These are significantly helpful at discovering widespread 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.
Deal with
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 ingredient in a 5 ingredient array. It is 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 should output the next error message. This factors you in a great course (a 4-byte write in essential). This binary could possibly be seen in a disassembler to determine precisely which instruction (at essential+0x84) is inflicting the issue.
Equally, here 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 knowledge[2]; return knowledge[0]; }
When compiled with -fsanitize=reminiscence and executed, it should output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined habits, which refers back to the scenario the place a program’s habits is unpredictable and never specified by the langauge commonplace. 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.
#embody <limits.h> int essential(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it should 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 packages when two or extra threads entry a shared reminiscence location on the similar time. This case introduces unpredictability and may result in undefined habits. This is an instance through which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is fully 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 should 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 device.
The next picture reveals the output from working c-kzg-4844’s assessments with Valgrind. Within the crimson field is a sound discovering for a “conditional leap or transfer [that] is determined by uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the flawed root of unity or width have been supplied, it was doable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate verify 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 Overview
After improvement stabilizes, it has been completely examined, and your crew has manually reviewed the codebase themselves a number of occasions, 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 challenge is at the least considerably safe. Be mindful there isn’t any such factor as good safety. There’ll all the time 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 important 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 challenge could possibly be exploited for features, like it’s for Ethereum, think about organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability experiences 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 moderately than exploiting it or promoting it to a different occasion. We suggest 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 tasks, particularly within the important 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 important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present priceless insights and greatest practices for others embarking on comparable tasks.
