Vulnerability Detection with Code Language Models: How Far Are We?
Paper • 2403.18624 • Published
idx int64 | project string | commit_id string | project_url string | commit_url string | commit_message string | target int64 | func string | func_hash string | file_name string | file_hash string | cwe string | cve string | cve_desc string | nvd_url string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
194,963 | ImageMagick6 | dc070da861a015d3c97488fdcca6063b44d47a7b | https://github.com/ImageMagick/ImageMagick6 | https://github.com/ImageMagick/ImageMagick6/commit/dc070da861a015d3c97488fdcca6063b44d47a7b | https://github.com/ImageMagick/ImageMagick/pull/5034 | 1 | static MagickBooleanType GetEXIFProperty(const Image *image,
const char *property)
{
#define MaxDirectoryStack 16
#define EXIF_DELIMITER "\n"
#define EXIF_NUM_FORMATS 12
#define EXIF_FMT_BYTE 1
#define EXIF_FMT_STRING 2
#define EXIF_FMT_USHORT 3
#define EXIF_FMT_ULONG 4
#define EXIF_FMT_URATIONAL 5
#define EX... | 292096308156704952246887123009503225331 | property.c | 122751008107964047346147343124174074065 | CWE-704 | CVE-2022-32547 | In ImageMagick, there is load of misaligned address for type 'double', which requires 8 byte alignment and for type 'float', which requires 4 byte alignment at MagickCore/property.c. Whenever crafted or untrusted input is processed by ImageMagick, this causes a negative impact to application availability or other probl... | https://nvd.nist.gov/vuln/detail/CVE-2022-32547 |
217,569 | ImageMagick6 | dc070da861a015d3c97488fdcca6063b44d47a7b | https://github.com/ImageMagick/ImageMagick6 | https://github.com/ImageMagick/ImageMagick6/commit/dc070da861a015d3c97488fdcca6063b44d47a7b | https://github.com/ImageMagick/ImageMagick/pull/5034 | 0 | static MagickBooleanType GetEXIFProperty(const Image *image,
const char *property)
{
#define MaxDirectoryStack 16
#define EXIF_DELIMITER "\n"
#define EXIF_NUM_FORMATS 12
#define EXIF_FMT_BYTE 1
#define EXIF_FMT_STRING 2
#define EXIF_FMT_USHORT 3
#define EXIF_FMT_ULONG 4
#define EXIF_FMT_URATIONAL 5
#define EX... | 75422468811560646183620950160304672170 | property.c | 320426917520707901134127411021604962567 | CWE-704 | CVE-2022-32547 | In ImageMagick, there is load of misaligned address for type 'double', which requires 8 byte alignment and for type 'float', which requires 4 byte alignment at MagickCore/property.c. Whenever crafted or untrusted input is processed by ImageMagick, this causes a negative impact to application availability or other probl... | https://nvd.nist.gov/vuln/detail/CVE-2022-32547 |
194,989 | ImageMagick6 | 450949ed017f009b399c937cf362f0058eacc5fa | https://github.com/ImageMagick/ImageMagick6 | https://github.com/ImageMagick/ImageMagick6/commit/450949ed017f009b399c937cf362f0058eacc5fa | Pull request: https://github.com/ImageMagick/ImageMagick/pull/4963 | 1 | static MagickBooleanType ReadPSDChannelPixels(Image *image,
const size_t channels,const ssize_t row,const ssize_t type,
const unsigned char *pixels,ExceptionInfo *exception)
{
Quantum
pixel;
const unsigned char
*p;
IndexPacket
*indexes;
PixelPacket
*q;
ssize_t
x;
size_t
pack... | 50584299779312396054491404176852470969 | psd.c | 159316916509494023086155162326374999236 | CWE-190 | CVE-2022-32545 | A vulnerability was found in ImageMagick, causing an outside the range of representable values of type 'unsigned char' at coders/psd.c, when crafted or untrusted input is processed. This leads to a negative impact to application availability or other problems related to undefined behavior. | https://nvd.nist.gov/vuln/detail/CVE-2022-32545 |
218,785 | ImageMagick6 | 450949ed017f009b399c937cf362f0058eacc5fa | https://github.com/ImageMagick/ImageMagick6 | https://github.com/ImageMagick/ImageMagick6/commit/450949ed017f009b399c937cf362f0058eacc5fa | Pull request: https://github.com/ImageMagick/ImageMagick/pull/4963 | 0 | static MagickBooleanType ReadPSDChannelPixels(Image *image,
const size_t channels,const ssize_t row,const ssize_t type,
const unsigned char *pixels,ExceptionInfo *exception)
{
Quantum
pixel;
const unsigned char
*p;
IndexPacket
*indexes;
PixelPacket
*q;
ssize_t
x;
size_t
pack... | 177518249272594340059836567736761123364 | psd.c | 226732625250511916284298083592366716300 | CWE-190 | CVE-2022-32545 | A vulnerability was found in ImageMagick, causing an outside the range of representable values of type 'unsigned char' at coders/psd.c, when crafted or untrusted input is processed. This leads to a negative impact to application availability or other problems related to undefined behavior. | https://nvd.nist.gov/vuln/detail/CVE-2022-32545 |
194,994 | tensorflow | c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd | Fix memory leak when a graph node is invalid.
If a graph node is invalid but a kernel is created then we set the kernel back to `nullptr` but we forget to delete it. Hence, we get a memory leak.
PiperOrigin-RevId: 408968108
Change-Id: I1d8a9d0d8988ed5e08be8b9f2004ce1b4cd11b7c | 1 | Status ImmutableExecutorState::Initialize(const Graph& graph) {
TF_RETURN_IF_ERROR(gview_.Initialize(&graph));
// Build the information about frames in this subgraph.
ControlFlowInfo cf_info;
TF_RETURN_IF_ERROR(BuildControlFlowInfo(&graph, &cf_info));
for (auto& it : cf_info.unique_frame_names) {
Ensure... | 105248557138287586060572648585871722551 | immutable_executor_state.cc | 234046012522402227954780787024760975669 | CWE-401 | CVE-2022-23578 | Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. The... | https://nvd.nist.gov/vuln/detail/CVE-2022-23578 |
218,852 | tensorflow | c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd | Fix memory leak when a graph node is invalid.
If a graph node is invalid but a kernel is created then we set the kernel back to `nullptr` but we forget to delete it. Hence, we get a memory leak.
PiperOrigin-RevId: 408968108
Change-Id: I1d8a9d0d8988ed5e08be8b9f2004ce1b4cd11b7c | 0 | Status ImmutableExecutorState::Initialize(const Graph& graph) {
TF_RETURN_IF_ERROR(gview_.Initialize(&graph));
// Build the information about frames in this subgraph.
ControlFlowInfo cf_info;
TF_RETURN_IF_ERROR(BuildControlFlowInfo(&graph, &cf_info));
for (auto& it : cf_info.unique_frame_names) {
Ensure... | 156764801773187472412077288460661715117 | immutable_executor_state.cc | 208458315060777566057381971058447382110 | CWE-401 | CVE-2022-23578 | Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. The... | https://nvd.nist.gov/vuln/detail/CVE-2022-23578 |
194,996 | tensorflow | 4f38b1ac8e42727e18a2f0bde06d3bee8e77b250 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/4f38b1ac8e42727e18a2f0bde06d3bee8e77b250 | Prevent null dereference read in `GetInitOp`.
We have a map of maps. We test that the key exists in the first map but then we don't have any validation that this also means the second map has the needed key. In the scenarios where this is not the case, we'll dereference a nullptr, if we don't have this check
PiperOri... | 1 | Status GetInitOp(const string& export_dir, const MetaGraphDef& meta_graph_def,
string* init_op_name) {
const auto& sig_def_map = meta_graph_def.signature_def();
const auto& init_op_sig_it =
meta_graph_def.signature_def().find(kSavedModelInitOpSignatureKey);
if (init_op_sig_it != sig_def_map... | 90320046309155279319769139363770698236 | loader_util.cc | 223638670651747648145854147173893848422 | CWE-476 | CVE-2022-23577 | Tensorflow is an Open Source Machine Learning Framework. The implementation of `GetInitOp` is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also aff... | https://nvd.nist.gov/vuln/detail/CVE-2022-23577 |
218,933 | tensorflow | 4f38b1ac8e42727e18a2f0bde06d3bee8e77b250 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/4f38b1ac8e42727e18a2f0bde06d3bee8e77b250 | Prevent null dereference read in `GetInitOp`.
We have a map of maps. We test that the key exists in the first map but then we don't have any validation that this also means the second map has the needed key. In the scenarios where this is not the case, we'll dereference a nullptr, if we don't have this check
PiperOri... | 0 | Status GetInitOp(const string& export_dir, const MetaGraphDef& meta_graph_def,
string* init_op_name) {
const auto& sig_def_map = meta_graph_def.signature_def();
const auto& init_op_sig_it =
meta_graph_def.signature_def().find(kSavedModelInitOpSignatureKey);
if (init_op_sig_it != sig_def_map... | 120370294428908534368713689048437773064 | loader_util.cc | 225205642200693417259460288987767726126 | CWE-476 | CVE-2022-23577 | Tensorflow is an Open Source Machine Learning Framework. The implementation of `GetInitOp` is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also aff... | https://nvd.nist.gov/vuln/detail/CVE-2022-23577 |
194,998 | tensorflow | 240655511cd3e701155f944a972db71b6c0b1bb6 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/240655511cd3e701155f944a972db71b6c0b1bb6 | Eliminate `CHECK`-fails from `IsSimplifiableReshape` via `MakeShape(<invalid shape>)`
PiperOrigin-RevId: 409166738
Change-Id: I7f0a3590b8acae3f3e3e2fe636e1f5ef285693cf | 1 | Status ConstantFolding::IsSimplifiableReshape(
const NodeDef& node, const GraphProperties& properties) const {
if (!IsReshape(node)) {
return errors::Internal("Node ", node.name(), " is not a Reshape node");
}
if (2 > node.input_size()) {
return errors::Internal("Node ", node.name(),
... | 122664089420988233915419567191040959656 | constant_folding.cc | 35061507297230918846503076104140700863 | CWE-617 | CVE-2022-23581 | Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that `IsSimplifiableReshape` would trigger `CHECK` failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorF... | https://nvd.nist.gov/vuln/detail/CVE-2022-23581 |
219,032 | tensorflow | 240655511cd3e701155f944a972db71b6c0b1bb6 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/240655511cd3e701155f944a972db71b6c0b1bb6 | Eliminate `CHECK`-fails from `IsSimplifiableReshape` via `MakeShape(<invalid shape>)`
PiperOrigin-RevId: 409166738
Change-Id: I7f0a3590b8acae3f3e3e2fe636e1f5ef285693cf | 0 | Status ConstantFolding::IsSimplifiableReshape(
const NodeDef& node, const GraphProperties& properties) const {
if (!IsReshape(node)) {
return errors::Internal("Node ", node.name(), " is not a Reshape node");
}
if (2 > node.input_size()) {
return errors::Internal("Node ", node.name(),
... | 262760907526734396914090099303096262406 | constant_folding.cc | 271606694375277711450004865336349725435 | CWE-617 | CVE-2022-23581 | Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that `IsSimplifiableReshape` would trigger `CHECK` failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorF... | https://nvd.nist.gov/vuln/detail/CVE-2022-23581 |
195,017 | gpac | ad18ece95fa064efc0995c4ab2c985f77fb166ec | https://github.com/gpac/gpac | https://github.com/gpac/gpac/commit/ad18ece95fa064efc0995c4ab2c985f77fb166ec | fixed #1904 | 1 | u32 GetHintFormat(GF_TrackBox *trak)
{
GF_HintMediaHeaderBox *hmhd = (GF_HintMediaHeaderBox *)trak->Media->information->InfoHeader;
if (hmhd->type != GF_ISOM_BOX_TYPE_HMHD)
return 0;
if (!hmhd || !hmhd->subType) {
GF_Box *a = (GF_Box *)gf_list_get(trak->Media->information->sampleTable->SampleDescription->chil... | 91218268849686441388880855658517990203 | hint_track.c | 60176895274654779679144452624639678766 | CWE-476 | CVE-2021-40576 | The binary MP4Box in Gpac 1.0.1 has a null pointer dereference vulnerability in the gf_isom_get_payt_count function in hint_track.c, which allows attackers to cause a denial of service. | https://nvd.nist.gov/vuln/detail/CVE-2021-40576 |
219,912 | gpac | ad18ece95fa064efc0995c4ab2c985f77fb166ec | https://github.com/gpac/gpac | https://github.com/gpac/gpac/commit/ad18ece95fa064efc0995c4ab2c985f77fb166ec | fixed #1904 | 0 | u32 GetHintFormat(GF_TrackBox *trak)
{
GF_HintMediaHeaderBox *hmhd = (GF_HintMediaHeaderBox *)trak->Media->information->InfoHeader;
if (!hmhd || (hmhd->type != GF_ISOM_BOX_TYPE_HMHD))
return 0;
if (!hmhd || !hmhd->subType) {
GF_Box *a = (GF_Box *)gf_list_get(trak->Media->information->sampleTable->SampleDescri... | 240641657114030682383886931707833033482 | hint_track.c | 28976036322661795345788739460485147148 | CWE-476 | CVE-2021-40576 | The binary MP4Box in Gpac 1.0.1 has a null pointer dereference vulnerability in the gf_isom_get_payt_count function in hint_track.c, which allows attackers to cause a denial of service. | https://nvd.nist.gov/vuln/detail/CVE-2021-40576 |
195,019 | tensorflow | 6b5adc0877de832b2a7c189532dbbbc64622eeb6 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/6b5adc0877de832b2a7c189532dbbbc64622eeb6 | Prevent `CHECK`-fail when building reference tensor.
The tensor constructor does not allow reference dtypes, as these should not show up explicitly. However, when passed these invalid types instead of building an invalid object the constructor crashes via a `CHECK`-fail. We have a static builder that properly handles ... | 1 | Status ConstantFolding::EvaluateOneFoldable(const NodeDef& node,
std::vector<NodeDef>* outputs,
bool* result_too_large) {
TensorVector inputs;
TensorVector output_tensors;
auto inputs_cleanup = gtl::MakeCleanup([&inputs, &outp... | 33937240667530924395323323412961833143 | constant_folding.cc | 221573695858123615640237954647315751120 | CWE-617 | CVE-2022-23588 | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that Grappler optimizer would attempt to build a tensor using a reference `dtype`. This would result in a crash due to a `CHECK`-fail in the `Tensor` constructor as reference types are... | https://nvd.nist.gov/vuln/detail/CVE-2022-23588 |
219,931 | tensorflow | 6b5adc0877de832b2a7c189532dbbbc64622eeb6 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/6b5adc0877de832b2a7c189532dbbbc64622eeb6 | Prevent `CHECK`-fail when building reference tensor.
The tensor constructor does not allow reference dtypes, as these should not show up explicitly. However, when passed these invalid types instead of building an invalid object the constructor crashes via a `CHECK`-fail. We have a static builder that properly handles ... | 0 | Status ConstantFolding::EvaluateOneFoldable(const NodeDef& node,
std::vector<NodeDef>* outputs,
bool* result_too_large) {
TensorVector inputs;
TensorVector output_tensors;
auto inputs_cleanup = gtl::MakeCleanup([&inputs, &outp... | 111779981092160670584101984885423453823 | constant_folding.cc | 271606694375277711450004865336349725435 | CWE-617 | CVE-2022-23588 | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that Grappler optimizer would attempt to build a tensor using a reference `dtype`. This would result in a crash due to a `CHECK`-fail in the `Tensor` constructor as reference types are... | https://nvd.nist.gov/vuln/detail/CVE-2022-23588 |
195,022 | glewlwyd | 125281f1c0d4b6a8b49f7e55a757205a2ef01fbe | https://github.com/babelouest/glewlwyd | https://github.com/babelouest/glewlwyd/commit/125281f1c0d4b6a8b49f7e55a757205a2ef01fbe | Fix update session when auth fail | 1 | int callback_glewlwyd_user_auth (const struct _u_request * request, struct _u_response * response, void * user_data) {
struct config_elements * config = (struct config_elements *)user_data;
json_t * j_param = ulfius_get_json_body_request(request, NULL), * j_result = NULL;
const char * ip_source = get_ip_source(re... | 236114269060053642565806917047085397848 | webservice.c | 249878395356016662912854745569339968395 | CWE-287 | CVE-2021-45379 | Glewlwyd 2.0.0, fixed in 2.6.1 is affected by an incorrect access control vulnerability. One user can attempt to log in as another user without its password. | https://nvd.nist.gov/vuln/detail/CVE-2021-45379 |
219,947 | glewlwyd | 125281f1c0d4b6a8b49f7e55a757205a2ef01fbe | https://github.com/babelouest/glewlwyd | https://github.com/babelouest/glewlwyd/commit/125281f1c0d4b6a8b49f7e55a757205a2ef01fbe | Fix update session when auth fail | 0 | int callback_glewlwyd_user_auth (const struct _u_request * request, struct _u_response * response, void * user_data) {
struct config_elements * config = (struct config_elements *)user_data;
json_t * j_param = ulfius_get_json_body_request(request, NULL), * j_result = NULL;
const char * ip_source = get_ip_source(re... | 155113792370707223407331204609439430532 | webservice.c | 287798817606377336444620654835011177393 | CWE-287 | CVE-2021-45379 | Glewlwyd 2.0.0, fixed in 2.6.1 is affected by an incorrect access control vulnerability. One user can attempt to log in as another user without its password. | https://nvd.nist.gov/vuln/detail/CVE-2021-45379 |
195,023 | tensorflow | a68f68061e263a88321c104a6c911fe5598050a8 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/a68f68061e263a88321c104a6c911fe5598050a8 | Replace faulty overflow check with a builder for `TensorShape`.
Prevents an integer overflow that was not caught before.
PiperOrigin-RevId: 415381595
Change-Id: I76585ddedc912bd9f4a390aeafa8e2ced1a28863 | 1 | void Compute(OpKernelContext* context) override {
const Tensor* input_indices;
const Tensor* input_values;
const Tensor* input_shape;
SparseTensorsMap* map;
OP_REQUIRES_OK(context, context->input("sparse_indices", &input_indices));
OP_REQUIRES_OK(context, context->input("sparse_values", &inpu... | 160387063214720131730960354923232758630 | sparse_tensors_map_ops.cc | 224775123349374780251651202891389866533 | CWE-190 | CVE-2022-23568 | Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the inp... | https://nvd.nist.gov/vuln/detail/CVE-2022-23568 |
220,021 | tensorflow | a68f68061e263a88321c104a6c911fe5598050a8 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/a68f68061e263a88321c104a6c911fe5598050a8 | Replace faulty overflow check with a builder for `TensorShape`.
Prevents an integer overflow that was not caught before.
PiperOrigin-RevId: 415381595
Change-Id: I76585ddedc912bd9f4a390aeafa8e2ced1a28863 | 0 | void Compute(OpKernelContext* context) override {
const Tensor* input_indices;
const Tensor* input_values;
const Tensor* input_shape;
SparseTensorsMap* map;
OP_REQUIRES_OK(context, context->input("sparse_indices", &input_indices));
OP_REQUIRES_OK(context, context->input("sparse_values", &inpu... | 294930600730557371611113946400120075396 | sparse_tensors_map_ops.cc | 5591389034837291700501932002893322459 | CWE-190 | CVE-2022-23568 | Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the inp... | https://nvd.nist.gov/vuln/detail/CVE-2022-23568 |
195,026 | linux | ab0fc21bc7105b54bafd85bd8b82742f9e68898a | https://github.com/torvalds/linux | https://github.com/torvalds/linux/commit/ab0fc21bc7105b54bafd85bd8b82742f9e68898a | Revert "NFSv4: Handle the special Linux file open access mode"
This reverts commit 44942b4e457beda00981f616402a1a791e8c616e.
After secondly opening a file with O_ACCMODE|O_DIRECT flags,
nfs4_valid_open_stateid() will dereference NULL nfs4_state when lseek().
Reproducer:
1. mount -t nfs -o vers=4.2 $server_ip:/ /mn... | 1 | nfs4_file_open(struct inode *inode, struct file *filp)
{
struct nfs_open_context *ctx;
struct dentry *dentry = file_dentry(filp);
struct dentry *parent = NULL;
struct inode *dir;
unsigned openflags = filp->f_flags;
struct iattr attr;
int err;
/*
* If no cached dentry exists or if it's negative, NFSv4 handled... | 67846125552854891508125900978071958871 | nfs4file.c | 109456154040292488452120321326967957719 | CWE-909 | CVE-2022-24448 | An issue was discovered in fs/nfs/dir.c in the Linux kernel before 5.16.5. If an application sets the O_DIRECTORY flag, and tries to open a regular file, nfs_atomic_open() performs a regular lookup. If a regular file is found, ENOTDIR should occur, but the server instead returns uninitialized data in the file descripto... | https://nvd.nist.gov/vuln/detail/CVE-2022-24448 |
220,100 | linux | ab0fc21bc7105b54bafd85bd8b82742f9e68898a | https://github.com/torvalds/linux | https://github.com/torvalds/linux/commit/ab0fc21bc7105b54bafd85bd8b82742f9e68898a | Revert "NFSv4: Handle the special Linux file open access mode"
This reverts commit 44942b4e457beda00981f616402a1a791e8c616e.
After secondly opening a file with O_ACCMODE|O_DIRECT flags,
nfs4_valid_open_stateid() will dereference NULL nfs4_state when lseek().
Reproducer:
1. mount -t nfs -o vers=4.2 $server_ip:/ /mn... | 0 | nfs4_file_open(struct inode *inode, struct file *filp)
{
struct nfs_open_context *ctx;
struct dentry *dentry = file_dentry(filp);
struct dentry *parent = NULL;
struct inode *dir;
unsigned openflags = filp->f_flags;
struct iattr attr;
int err;
/*
* If no cached dentry exists or if it's negative, NFSv4 handled... | 272987829557105540879962051296017178836 | nfs4file.c | 19160442996144037090827134285929888626 | CWE-909 | CVE-2022-24448 | An issue was discovered in fs/nfs/dir.c in the Linux kernel before 5.16.5. If an application sets the O_DIRECTORY flag, and tries to open a regular file, nfs_atomic_open() performs a regular lookup. If a regular file is found, ENOTDIR should occur, but the server instead returns uninitialized data in the file descripto... | https://nvd.nist.gov/vuln/detail/CVE-2022-24448 |
195,028 | tensorflow | ab51e5b813573dc9f51efa335aebcf2994125ee9 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9 | Prevent memory leak in decoding PNG images.
PiperOrigin-RevId: 409300653
Change-Id: I6182124c545989cef80cefd439b659095920763b | 1 | void DecodePngV2(OpKernelContext* context, StringPiece input) {
int channel_bits = (data_type_ == DataType::DT_UINT8) ? 8 : 16;
png::DecodeContext decode;
OP_REQUIRES(
context, png::CommonInitDecode(input, channels_, channel_bits, &decode),
errors::InvalidArgument("Invalid PNG. Failed to i... | 67814436772398534036630434647873886403 | decode_image_op.cc | 283519422605879710361255065504339887165 | CWE-401 | CVE-2022-23585 | Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However,... | https://nvd.nist.gov/vuln/detail/CVE-2022-23585 |
220,168 | tensorflow | ab51e5b813573dc9f51efa335aebcf2994125ee9 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9 | Prevent memory leak in decoding PNG images.
PiperOrigin-RevId: 409300653
Change-Id: I6182124c545989cef80cefd439b659095920763b | 0 | void DecodePngV2(OpKernelContext* context, StringPiece input) {
int channel_bits = (data_type_ == DataType::DT_UINT8) ? 8 : 16;
png::DecodeContext decode;
OP_REQUIRES(
context, png::CommonInitDecode(input, channels_, channel_bits, &decode),
errors::InvalidArgument("Invalid PNG. Failed to i... | 183944225263640230240348550837981668390 | decode_image_op.cc | 140340118421060830961361158847913918052 | CWE-401 | CVE-2022-23585 | Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However,... | https://nvd.nist.gov/vuln/detail/CVE-2022-23585 |
195,029 | tensorflow | c99d98cd189839dcf51aee94e7437b54b31f8abd | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/c99d98cd189839dcf51aee94e7437b54b31f8abd | Handle invalid inputs instead of crashing.
PiperOrigin-RevId: 409549744
Change-Id: I7f5935b34b53f7e426a5462fcc027bdbf5dcda24 | 1 | void Node::RunForwardTypeInference() {
VLOG(4) << "Forward type inference: " << props_->node_def.DebugString();
if (props_->fwd_type_fn == nullptr) {
return;
}
std::vector<Node*> input_nodes(props_->input_types.size(), nullptr);
std::vector<int> input_idx(props_->input_types.size(), 0);
for (const aut... | 285691869172413131662679092330979772991 | graph.cc | 172099243927919341591512227523808328051 | CWE-125 | CVE-2022-23592 | Tensorflow is an Open Source Machine Learning Framework. TensorFlow's type inference can cause a heap out of bounds read as the bounds checking is done in a `DCHECK` (which is a no-op during production). An attacker can control the `input_idx` variable such that `ix` would be larger than the number of values in `node_t... | https://nvd.nist.gov/vuln/detail/CVE-2022-23592 |
220,201 | tensorflow | c99d98cd189839dcf51aee94e7437b54b31f8abd | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/c99d98cd189839dcf51aee94e7437b54b31f8abd | Handle invalid inputs instead of crashing.
PiperOrigin-RevId: 409549744
Change-Id: I7f5935b34b53f7e426a5462fcc027bdbf5dcda24 | 0 | void Node::RunForwardTypeInference() {
VLOG(4) << "Forward type inference: " << props_->node_def.DebugString();
if (props_->fwd_type_fn == nullptr) {
return;
}
std::vector<Node*> input_nodes(props_->input_types.size(), nullptr);
std::vector<int> input_idx(props_->input_types.size(), 0);
for (const aut... | 208747443072046126472677622190312892089 | graph.cc | 252683577168046425270820661985512954953 | CWE-125 | CVE-2022-23592 | Tensorflow is an Open Source Machine Learning Framework. TensorFlow's type inference can cause a heap out of bounds read as the bounds checking is done in a `DCHECK` (which is a no-op during production). An attacker can control the `input_idx` variable such that `ix` would be larger than the number of values in `node_t... | https://nvd.nist.gov/vuln/detail/CVE-2022-23592 |
195,038 | mruby | 27d1e0132a0804581dca28df042e7047fd27eaa8 | https://github.com/mruby/mruby | https://github.com/mruby/mruby/commit/27d1e0132a0804581dca28df042e7047fd27eaa8 | array.c: fix `mrb_ary_shift_m` initialization bug.
The `ARY_PTR` and `ARY_LEN` may be modified in `mrb_get_args`. | 1 | mrb_ary_shift_m(mrb_state *mrb, mrb_value self)
{
struct RArray *a = mrb_ary_ptr(self);
mrb_int len = ARY_LEN(a);
mrb_int n;
mrb_value val;
if (mrb_get_args(mrb, "|i", &n) == 0) {
return mrb_ary_shift(mrb, self);
};
ary_modify_check(mrb, a);
if (len == 0 || n == 0) return mrb_ary_new(mrb);
if (n ... | 88987793594626442814152795226896894437 | array.c | 131985777969528154957566525214352537878 | CWE-476 | CVE-2021-4188 | mruby is vulnerable to NULL Pointer Dereference | https://nvd.nist.gov/vuln/detail/CVE-2021-4188 |
220,442 | mruby | 27d1e0132a0804581dca28df042e7047fd27eaa8 | https://github.com/mruby/mruby | https://github.com/mruby/mruby/commit/27d1e0132a0804581dca28df042e7047fd27eaa8 | array.c: fix `mrb_ary_shift_m` initialization bug.
The `ARY_PTR` and `ARY_LEN` may be modified in `mrb_get_args`. | 0 | mrb_ary_shift_m(mrb_state *mrb, mrb_value self)
{
mrb_int n;
if (mrb_get_args(mrb, "|i", &n) == 0) {
return mrb_ary_shift(mrb, self);
}
struct RArray *a = mrb_ary_ptr(self);
mrb_int len = ARY_LEN(a);
mrb_value val;
ary_modify_check(mrb, a);
if (len == 0 || n == 0) return mrb_ary_new(mrb);
if (n... | 336824346603495353101799104649854425750 | array.c | 295526445825727607536544634773604768998 | CWE-476 | CVE-2021-4188 | mruby is vulnerable to NULL Pointer Dereference | https://nvd.nist.gov/vuln/detail/CVE-2021-4188 |
195,039 | tensorflow | e7f497570abb6b4ae5af4970620cd880e4c0c904 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904 | Fix segfault on OOM in Conv2D.
PiperOrigin-RevId: 404655317
Change-Id: I33588dbd3f5d0fef980e3c908bf5515a9ee09ce7 | 1 | void operator()(OpKernelContext* ctx, const Tensor& input,
const Tensor& filter, int row_stride, int col_stride,
int row_dilation, int col_dilation, const Padding& padding,
const std::vector<int64_t>& explicit_paddings, Tensor* output,
TensorForm... | 257618220779157714024325768166416151732 | conv_ops.cc | 252300068611383622428481854806618645318 | CWE-354 | CVE-2021-41206 | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenario... | https://nvd.nist.gov/vuln/detail/CVE-2021-41206 |
220,449 | tensorflow | e7f497570abb6b4ae5af4970620cd880e4c0c904 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904 | Fix segfault on OOM in Conv2D.
PiperOrigin-RevId: 404655317
Change-Id: I33588dbd3f5d0fef980e3c908bf5515a9ee09ce7 | 0 | void operator()(OpKernelContext* ctx, const Tensor& input,
const Tensor& filter, int row_stride, int col_stride,
int row_dilation, int col_dilation, const Padding& padding,
const std::vector<int64_t>& explicit_paddings, Tensor* output,
TensorForm... | 52476148530312265483336987277784785500 | conv_ops.cc | 162425470101834995272420301327894414264 | CWE-354 | CVE-2021-41206 | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenario... | https://nvd.nist.gov/vuln/detail/CVE-2021-41206 |
195,040 | tensorflow | e21af685e1828f7ca65038307df5cc06de4479e8 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/e21af685e1828f7ca65038307df5cc06de4479e8 | Fix Null-pointer dereference in BuildXlaCompilationCache
If ConfigProto is not used, then use the default settings which is to allow all devices.
PiperOrigin-RevId: 420391800
Change-Id: I88161ad7042990aef678e77b597a2fb2c8f815be | 1 | Status BuildXlaCompilationCache(DeviceBase* device, FunctionLibraryRuntime* flr,
const XlaPlatformInfo& platform_info,
XlaCompilationCache** cache) {
if (platform_info.xla_device_metadata()) {
*cache = new XlaCompilationCache(
platform_info.x... | 179065639871904945359341382009364285020 | xla_platform_info.cc | 171804916137745205288117058026592469555 | CWE-476 | CVE-2022-23595 | Tensorflow is an Open Source Machine Learning Framework. When building an XLA compilation cache, if default settings are used, TensorFlow triggers a null pointer dereference. In the default scenario, all devices are allowed, so `flr->config_proto` is `nullptr`. The fix will be included in TensorFlow 2.8.0. We will also... | https://nvd.nist.gov/vuln/detail/CVE-2022-23595 |
220,463 | tensorflow | e21af685e1828f7ca65038307df5cc06de4479e8 | https://github.com/tensorflow/tensorflow | https://github.com/tensorflow/tensorflow/commit/e21af685e1828f7ca65038307df5cc06de4479e8 | Fix Null-pointer dereference in BuildXlaCompilationCache
If ConfigProto is not used, then use the default settings which is to allow all devices.
PiperOrigin-RevId: 420391800
Change-Id: I88161ad7042990aef678e77b597a2fb2c8f815be | 0 | Status BuildXlaCompilationCache(DeviceBase* device, FunctionLibraryRuntime* flr,
const XlaPlatformInfo& platform_info,
XlaCompilationCache** cache) {
if (platform_info.xla_device_metadata()) {
*cache = new XlaCompilationCache(
platform_info.x... | 150487232572114145456611052017035566512 | xla_platform_info.cc | 318276067980065095571736754899104138947 | CWE-476 | CVE-2022-23595 | Tensorflow is an Open Source Machine Learning Framework. When building an XLA compilation cache, if default settings are used, TensorFlow triggers a null pointer dereference. In the default scenario, all devices are allowed, so `flr->config_proto` is `nullptr`. The fix will be included in TensorFlow 2.8.0. We will also... | https://nvd.nist.gov/vuln/detail/CVE-2022-23595 |
End of preview. Expand in Data Studio
PrimeVul-Paired Original Test Dataset
Overview
This dataset contains the original paired test split from the PrimeVul dataset, provided for reproducibility purposes. The data is sourced from the paper "PrimeVul: Vulnerability Detection with Code Language Models: How Far Are We?" and includes both the default (single functions) and paired (vulnerable/non-vulnerable pairs) configurations.
Citation
If you use this dataset, please cite the original PrimeVul paper:
@article{primevul2024,
title={PrimeVul: Vulnerability Detection with Code Language Models: How Far Are We?},
author={[Authors from the original paper]},
journal={arXiv preprint arXiv:2403.18624},
year={2024},
url={https://arxiv.org/abs/2403.18624}
}
Dataset Configurations
- Description: Paired vulnerability detection dataset with before/after patch pairs
- Size: 870 test samples
- Format: Each sample represents either the vulnerable or patched version of a function
- Fields:
idx: Unique sample identifierproject: Source project namecommit_id: Git commit hashtarget: Binary label (0=non-vulnerable, 1=vulnerable)func: Source code functionfunc_hash: Function hashcwe: Common Weakness Enumeration categoriescve: CVE identifier (if applicable)project_url: Source project repository URLcommit_url: Direct link to the commit- Additional metadata fields
Data Source
The original JSONL files are available from the PrimeVul authors at:
- Google Drive: https://drive.google.com/drive/folders/19iLaNDS0z99N8kB_jBRTmDLehwZBolMY
- GitHub Repository: https://github.com/DLVulDet/PrimeVul
Data Format
This dataset provides the test splits in Parquet format for easy loading with HuggingFace datasets. The original data was in JSONL format and has been converted while preserving all original fields and values.
Usage
from datasets import load_dataset
# Login using e.g. `huggingface-cli login` to access this dataset
ds = load_dataset("Code-TREAT/PrimeVul-Paired_original")
Purpose
This dataset is provided by the Code-TREAT project to ensure reproducibility and consistency in vulnerability detection research. By providing the exact test splits used in evaluations, researchers can:
- Reproduce results from papers using this dataset
- Compare methods fairly using identical test data
- Validate new approaches against established benchmarks
License
Please refer to the original PrimeVul repository for licensing information: https://github.com/DLVulDet/PrimeVul
Acknowledgments
We thank the authors of PrimeVul for making their dataset publicly available and for their contributions to vulnerability detection research.
Contact
For questions about this dataset distribution, please refer to the original PrimeVul repository or the Code-TREAT project.
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