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For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Fairly than every shopper rolling their very own crypto, researchers and builders got here collectively to put in writing c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The thought was to create a sturdy and environment friendly cryptographic library that each one purchasers might 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 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 had been already well-integrated with LLVM undertaking’s different choices.
Here is the fuzzer for verify_kzg_proof, considered one 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* 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 like. If there have been an issue, it will write the enter to disk and cease executing. Ideally, it is best to 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, you recognize one thing is mistaken. This method may be very common in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification gives an additional degree of security, figuring out that if one implementation had been flawed the others might not have the identical subject.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means 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 exams. This can be 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 the right 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 high and the non-exported (static) capabilities are on the underside.
There may be lots of inexperienced within the desk above, however there may be some yellow and purple too. To find out what’s and is not being executed, check with the HTML file (protection.html) that was generated. This webpage exhibits the whole supply file and highlights non-executed code in purple. On this undertaking’s case, many of the non-executed code offers with hard-to-test error circumstances reminiscent of reminiscence allocation failures. For instance, this is some non-executed code:
Initially of this operate, it checks that the trusted setup is sufficiently big to carry out a pairing examine. There is not a take a look at case which gives an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely take a look at 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 advocate this for all tasks, however since c-kzg-4844 is a efficiency vital library we predict it is necessary to profile its exported capabilities and measure how lengthy they take to execute. This might help determine inefficiencies which might 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 every now and then. If a operate is quick sufficient, it will not be seen 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.
#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 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 would 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:
Here is an even bigger instance from considered one of c-kzg-4844’s capabilities. 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) instrument reminiscent of 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 fashion; like how studying a paper in a distinct font will drive 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 typically the compiler will optimize out one thing which it deemed pointless. Hold 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, complicated varieties, 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 will typically 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 usually 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 seems like in Ghidra:
With somewhat work, you possibly can rename variables and add feedback to make it simpler to learn. Here 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 instrument 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 loads sooner 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 determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embody <stdlib.h> int foremost(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, nevertheless it is sensible if you consider 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 undertaking:
Given an surprising enter, it was attainable 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 not possible. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to applications which might 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 might 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 component in a 5 component array. This can be a easy instance of a heap-buffer-overflow:
#embody <stdlib.h> int foremost(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it would 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, this is an instance the place it finds a heap-use-after-free:
#embody <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 would output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined habits, which refers back to the state of affairs 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.
#embody <limits.h> int foremost(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it would 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 applications when two or extra threads entry a shared reminiscence location on the identical time. This example introduces unpredictability and may result in undefined habits. Here is an instance wherein two threads increment a world counter variable. There are no locks or semaphores, so it is totally attainable that these two threads will increment the variable on the identical time.
#embody <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 would 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 strong instrumentation framework for constructing dynamic evaluation instruments, however its finest identified for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture exhibits the output from working c-kzg-4844’s exams with Valgrind. Within the purple field is a legitimate discovering for a “conditional soar or transfer [that] is dependent upon uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the mistaken root of unity or width had been offered, it was attainable that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate examine 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 improvement stabilizes, it has been completely examined, and your group has manually reviewed the codebase themselves a number of occasions, it is time to get a safety overview by a good safety group. This may not be a stamp of approval, nevertheless it exhibits that your undertaking is not less than considerably safe. Consider there isn’t 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 overview. They produced this report with 8 findings. It comprises 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 fastened, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your undertaking might be exploited for good points, like it’s for Ethereum, take into account organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability experiences in change for cash. Typically, 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 slightly than exploiting it or promoting it to a different occasion. We advocate beginning your bug bounty program after the findings from the primary safety overview are resolved; ideally, the safety overview would value lower than the bug bounty payouts.
Conclusion
The event of strong 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 mixture of finest practices and instruments is important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present beneficial insights and finest practices for others embarking on related tasks.
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