gguf : harden loader against malformed tensor dims and metadata types (llama/25596)
* gguf : harden loader against malformed tensor dims and metadata types * gguf: address review on malformed-metadata hardening - report the expected vs. actual type when general.alignment is not u32 - use ggml_nelements() > 0 for the zero-element guard and keep the representability checks visually aligned - add test-gguf cases for a wrong-typed alignment key and a zero-dim tensor (both used to crash: assert-abort and SIGFPE respectively) Ran tests/test-gguf: 164/164 pass. Used an AI assistant to help draft these edits; reviewed and verified by me. * cont : less comments Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -611,6 +611,13 @@ static struct gguf_context * gguf_init_from_reader(const struct gguf_reader & gr
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GGML_ASSERT(int64_t(ctx->kv.size()) == n_kv);
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const int alignment_idx = gguf_find_key(ctx, GGUF_KEY_GENERAL_ALIGNMENT);
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if (alignment_idx != -1 && gguf_get_kv_type(ctx, alignment_idx) != GGUF_TYPE_UINT32) {
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GGML_LOG_ERROR("%s: key '%s' must be of type %s but is %s\n",
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__func__, GGUF_KEY_GENERAL_ALIGNMENT, gguf_type_name(GGUF_TYPE_UINT32),
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gguf_type_name(gguf_get_kv_type(ctx, alignment_idx)));
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gguf_free(ctx);
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return nullptr;
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}
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ctx->alignment = alignment_idx == -1 ? GGUF_DEFAULT_ALIGNMENT : gguf_get_val_u32(ctx, alignment_idx);
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if (ctx->alignment == 0 || (ctx->alignment & (ctx->alignment - 1)) != 0) {
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@ -682,9 +689,11 @@ static struct gguf_context * gguf_init_from_reader(const struct gguf_reader & gr
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}
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// check that the total number of elements is representable
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if (ok && ((INT64_MAX/info.t.ne[1] <= info.t.ne[0]) ||
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(INT64_MAX/info.t.ne[2] <= info.t.ne[0]*info.t.ne[1]) ||
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(INT64_MAX/info.t.ne[3] <= info.t.ne[0]*info.t.ne[1]*info.t.ne[2]))) {
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// (a zero-element tensor is trivially representable; the guard also avoids a division by zero below)
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if (ok && ggml_nelements(&info.t) > 0 &&
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((INT64_MAX/info.t.ne[1] <= info.t.ne[0]) ||
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(INT64_MAX/info.t.ne[2] <= info.t.ne[0]*info.t.ne[1]) ||
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(INT64_MAX/info.t.ne[3] <= info.t.ne[0]*info.t.ne[1]*info.t.ne[2]))) {
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GGML_LOG_ERROR("%s: total number of elements in tensor '%s' with shape "
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"(%" PRIi64 ", %" PRIi64 ", %" PRIi64 ", %" PRIi64 ") is >= %" PRIi64 "\n",
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