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For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Moderately 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 concept was to create a strong and environment friendly cryptographic library that every one purchasers may use. The Protocol Safety Analysis group on the Ethereum Basis had the chance to overview and enhance this library. This weblog publish 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 venture’s different choices.
Here is the fuzzer for verify_kzg_proof, considered 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* 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 seems to be like. If there have been an issue, it will write the enter to disk and cease executing. Ideally, you need 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, one thing is incorrect. 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, figuring out that if one implementation had been flawed the others could not have the identical situation.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means of its Golang bindings) and go-kzg-4844. Thus far, 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 solution to confirm code is executed (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of find out 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 perform 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 purple 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 purple. On this venture’s case, many of the non-executed code offers with hard-to-test error circumstances comparable to reminiscence allocation failures. For instance, this is some non-executed code:
At first of this perform, it checks that the trusted setup is sufficiently big to carry out a pairing examine. 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 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 vital library we predict it is vital to profile its exported features and measure how lengthy they take to execute. This might help establish 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 a straightforward instance which profiles my_function. Profiling works by checking which instruction is being executed on occasion. If a perform is quick sufficient, it is probably not seen by the profiler. To scale back the prospect of this, you might 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 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 is going to write a file to disk with profiling information. You possibly can then use pprof to visualise this information.
Right here is the graph generated from the command above:
Here is an even bigger instance from considered one of c-kzg-4844’s features. 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) instrument comparable to Ghidra or IDA. These instruments might help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to overview your code this manner; like how studying a paper in a special font will pressure your mind to interpret sentences in a different way. 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 an eye fixed out for this, one thing like this really occurred in c-kzg-4844, some of the tests were being optimized out.
Once you view a decompiled perform, it won’t have variable names, advanced varieties, or feedback. When compiled, this data is not included within the binary. It is going to be as much as you to reverse engineer this. You will typically see features 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 completely different. These are simply compiler optimizations and are usually superb. It might assist to construct your binary with DWARF debugging data; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially seems to be like in Ghidra:
With just a little work, you’ll be able to rename variables and add feedback to make it simpler to learn. Here 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 superb static evaluation instrument 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 quite a bit 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 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 sensible if you concentrate on it; the analyzer reached the return assertion and seen 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 venture:
Given an surprising 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 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 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 straightforward 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 identical 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:
#embrace <stdlib.h> int foremost(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it is going to output the next error message. This factors you in a great path (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, this 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. Here 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 is 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 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.
#embrace <limits.h> int foremost(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 circumstances are:
Thread
ThreadSanitizer (TSan) detects information races, which may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the identical time. This case introduces unpredictability and might result in undefined habits. Here is an instance through which two threads increment a world counter variable. There are not any locks or semaphores, so it is totally 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 is going to 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 identical time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a strong instrumentation framework for constructing dynamic evaluation instruments, however its greatest identified for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture exhibits the output from operating c-kzg-4844’s assessments 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 incorrect root of unity or width had been supplied, it was doable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate examine 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 growth stabilizes, it has been completely examined, and your group has manually reviewed the codebase themselves a number of instances, it is time to get a safety overview by a good safety group. This may not be a stamp of approval, but it surely exhibits that your venture is at the least considerably safe. Remember there is no such thing as a such factor as good 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 overview. They produced this report with 8 findings. It accommodates one vital 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 venture might be exploited for positive factors, like it’s for Ethereum, contemplate organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability experiences 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 reasonably 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 overview are resolved; ideally, the safety overview would price lower than the bug bounty payouts.
Conclusion
The event of sturdy C tasks, particularly within the vital 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 invaluable insights and greatest practices for others embarking on related tasks.
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