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For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Reasonably 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 shoppers may use. The Protocol Safety Analysis workforce on the Ethereum Basis had the chance to evaluate 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 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 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* information, size_t dimension) { initialize(); if (dimension == 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 appears like. If there have been an issue, it will 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 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, one thing is incorrect. 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 gives an additional degree of security, understanding that if one implementation have been flawed the others could not have the identical subject.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by 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 operating the exams. It is a nice solution to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of tips on how 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’s lots 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 exhibits the whole 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 circumstances resembling reminiscence allocation failures. For instance, here is some non-executed code:
Initially of this operate, it checks that the trusted setup is sufficiently big to carry out a pairing verify. There is not a check case which gives 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 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 essential library we expect it is essential to profile its exported features 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 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 cut back the possibility of this, you could have to name your operate a number of occasions. On this instance, we name my_function 1000 occasions.
#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 foremost(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’s going to write a file to disk with profiling information. You may 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 in every of c-kzg-4844’s features. 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) software resembling 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 evaluate your code this manner; like how studying a paper in a special font will power your mind to interpret sentences otherwise. 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, some of the tests were being optimized out.
If you view a decompiled operate, it won’t have variable names, advanced 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 will usually 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 totally different. These are simply compiler optimizations and are usually effective. 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 appears like in Ghidra:
With somewhat work, you may rename variables and add feedback to make it simpler to learn. This is what it may appear 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 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 so much quicker than “dynamic” evaluation instruments which execute code.
This 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 establish this, even with all warnings enabled as a result of technically that is utterly legitimate code.
#embrace <stdlib.h> int foremost(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, 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 all the 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 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 establish 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 ingredient in a 5 ingredient array. It is a easy instance of a heap-buffer-overflow:
#embrace <stdlib.h> int foremost(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=tackle and executed, it’s going to output the next error message. This factors you in a great route (a 4-byte write in foremost). This binary might be considered in a disassembler to determine precisely which instruction (at foremost+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int foremost(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 foremost+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int foremost(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it’s going to 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 normal. 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.
#embrace <limits.h> int foremost(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it’s going to output the next error message which tells us precisely the place the issue is and what the circumstances are:
Thread
ThreadSanitizer (TSan) detects information races, which might happen in multi-threaded packages when two or extra threads entry a shared reminiscence location on the identical time. This example introduces unpredictability and might result in undefined habits. This is an instance wherein two threads increment a worldwide counter variable. There are no locks or semaphores, so it is fully doable 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 foremost(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’s going to output the next error message:
This error message tells us that there is a information 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 software.
The next picture exhibits the output from operating c-kzg-4844’s exams with Valgrind. Within the crimson field is a legitimate discovering for a “conditional bounce or transfer [that] is dependent upon uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the incorrect 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 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 Evaluate
After growth stabilizes, it has been completely examined, and your workforce has manually reviewed the codebase themselves a number of occasions, it is time to get a safety evaluate by a good safety group. This would possibly not be a stamp of approval, but it surely exhibits that your challenge is no less than considerably safe. Take into account there is no such thing as a such factor as excellent 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 evaluate. They produced this report with 8 findings. It incorporates 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 mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your challenge might be exploited for good points, like it’s for Ethereum, contemplate organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability stories in alternate for cash. Usually, that is particularly for findings which might 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 get together. We suggest beginning your bug bounty program after the findings from the primary safety evaluate are resolved; ideally, the safety evaluate would price lower than the bug bounty payouts.
Conclusion
The event of strong C tasks, particularly within the essential 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 useful insights and greatest practices for others embarking on comparable tasks.
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