Vulnerabilities (CVE)

The decode program in silk-v3-decoder Version:20160922 Build By kn007 does not strictly check data, resulting in a buffer overflow.

When uploading a file in Sysax Multi Server 6.90, an authenticated user can modify the filename="" parameter in the uploadfile_name1.htm form to a length of 368 or more bytes. This will create a buffer overflow condition, causing the application to crash.

IrfanView 4.54 allows a user-mode write access violation starting at FORMATS!ShowPlugInSaveOptions_W+0x0000000000002cba.

Mikrotik RouterOs prior to stable 6.47 suffers from a memory corruption vulnerability in the /nova/bin/bfd process. An authenticated remote attacker can cause a Denial of Service (NULL pointer dereference).

The unserialize() function supported a type code, "S", which was meant to be supported only for APC serialization. This type code allowed arbitrary memory addresses to be accessed as if they were static StringData objects. This issue affected HHVM prior to v4.32.3, between versions 4.33.0 and 4.56.0, 4.57.0, 4.58.0, 4.58.1, 4.59.0, 4.60.0, 4.61.0, 4.62.0.

Huawei NIP6800 versions V500R001C30, V500R001C60SPC500, and V500R005C00; Secospace USG6600 and USG9500 versions V500R001C30SPC200, V500R001C30SPC600, V500R001C60SPC500, and V500R005C00 have a Dangling pointer dereference vulnerability. An authenticated attacker may do some special operations in the affected products in some special scenarios to exploit the vulnerability. Due to improper race conditions of different operations, successful exploit will lead to Dangling pointer dereference, causing ... Huawei NIP6800 versions V500R001C30, V500R001C60SPC500, and V500R005C00; Secospace USG6600 and USG9500 versions V500R001C30SPC200, V500R001C30SPC600, V500R001C60SPC500, and V500R005C00 have a Dangling pointer dereference vulnerability. An authenticated attacker may do some special operations in the affected products in some special scenarios to exploit the vulnerability. Due to improper race conditions of different operations, successful exploit will lead to Dangling pointer dereference, causing some service abnormal.

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On Juniper Networks Junos OS platforms configured as DHCPv6 local server or DHCPv6 Relay Agent, Juniper Networks Dynamic Host Configuration Protocol Daemon (JDHCPD) process might crash with a core dump if a malformed DHCPv6 packet is received, resulting with the restart of the daemon. This issue only affects DHCPv6, it does not affect DHCPv4. This issue affects: Juniper Networks Junos OS 17.4 versions prior to 17.4R2-S12, 17.4R3-S3; 18.1 versions prior to 18.1R3-S11; 18.2 versions prior to 18.2R ... On Juniper Networks Junos OS platforms configured as DHCPv6 local server or DHCPv6 Relay Agent, Juniper Networks Dynamic Host Configuration Protocol Daemon (JDHCPD) process might crash with a core dump if a malformed DHCPv6 packet is received, resulting with the restart of the daemon. This issue only affects DHCPv6, it does not affect DHCPv4. This issue affects: Juniper Networks Junos OS 17.4 versions prior to 17.4R2-S12, 17.4R3-S3; 18.1 versions prior to 18.1R3-S11; 18.2 versions prior to 18.2R3-S6; 18.2X75 versions prior to 18.2X75-D65; 18.3 versions prior to 18.3R2-S4, 18.3R3-S3; 18.4 versions prior to 18.4R2-S5, 18.4R3-S4; 19.1 versions prior to 19.1R3-S2; 19.2 versions prior to 19.2R1-S5, 19.2R3; 19.2 version 19.2R2 and later versions; 19.3 versions prior to 19.3R2-S4, 19.3R3; 19.4 versions prior to 19.4R1-S3, 19.4R2-S2, 19.4R3; 20.1 versions prior to 20.1R1-S3, 20.1R2; This issue does not affect Juniper Networks Junos OS prior to 17.4R1.

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This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Studio Photo 3.6.6.922. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of CR2 files. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to execute ... This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Studio Photo 3.6.6.922. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of CR2 files. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-11230.

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This vulnerability allows local attackers to escalate privileges on affected installations of Parallels Desktop 15.1.4. An attacker must first obtain the ability to execute high-privileged code on the target guest system in order to exploit this vulnerability. The specific flaw exists within the handling of network packets. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to ... This vulnerability allows local attackers to escalate privileges on affected installations of Parallels Desktop 15.1.4. An attacker must first obtain the ability to execute high-privileged code on the target guest system in order to exploit this vulnerability. The specific flaw exists within the handling of network packets. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to escalate privileges and execute code in the context of the hypervisor. Was ZDI-CAN-11253.

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A vulnerability has been identified in SIMATIC Drive Controller family (All versions < V2.9.2), SIMATIC ET 200SP Open Controller CPU 1515SP PC (incl. SIPLUS variants) (All versions), SIMATIC ET 200SP Open Controller CPU 1515SP PC2 (incl. SIPLUS variants) (All versions < V21.9), SIMATIC S7-1200 CPU family (incl. SIPLUS variants) (All versions < V4.5.0), SIMATIC S7-1500 CPU family (incl. related ET200 CPUs and SIPLUS variants) (All versions < V2.9.2), SIMATIC S7-1500 Software Controller (All versi ... A vulnerability has been identified in SIMATIC Drive Controller family (All versions < V2.9.2), SIMATIC ET 200SP Open Controller CPU 1515SP PC (incl. SIPLUS variants) (All versions), SIMATIC ET 200SP Open Controller CPU 1515SP PC2 (incl. SIPLUS variants) (All versions < V21.9), SIMATIC S7-1200 CPU family (incl. SIPLUS variants) (All versions < V4.5.0), SIMATIC S7-1500 CPU family (incl. related ET200 CPUs and SIPLUS variants) (All versions < V2.9.2), SIMATIC S7-1500 Software Controller (All versions < V21.9), SIMATIC S7-PLCSIM Advanced (All versions < V4.0), SINAMICS PERFECT HARMONY GH180 Drives (Drives manufactured before 2021-08-13), SINUMERIK MC (All versions < V6.15), SINUMERIK ONE (All versions < V6.15). Affected devices are vulnerable to a memory protection bypass through a specific operation. A remote unauthenticated attacker with network access to port 102/tcp could potentially write arbitrary data and code to protected memory areas or read sensitive data to launch further attacks.

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An issue was discovered on Samsung mobile devices with Q(10.0) software. Attackers can trigger an out-of-bounds access and device reset via a 4K wallpaper image because ImageProcessHelper mishandles boundary checks. The Samsung ID is SVE-2020-18056 (July 2020).

An issue was discovered on Samsung mobile devices with P(9.0) and Q(10.0) (Exynos 7885 chipsets) software. The Bluetooth Low Energy (BLE) component has a buffer overflow with a resultant deadlock or crash. The Samsung ID is SVE-2020-16870 (July 2020).

An issue was discovered in Xen through 4.13.x, allowing Arm guest OS users to cause a hypervisor crash because of a missing alignment check in VCPUOP_register_vcpu_info. The hypercall VCPUOP_register_vcpu_info is used by a guest to register a shared region with the hypervisor. The region will be mapped into Xen address space so it can be directly accessed. On Arm, the region is accessed with instructions that require a specific alignment. Unfortunately, there is no check that the address provide ... An issue was discovered in Xen through 4.13.x, allowing Arm guest OS users to cause a hypervisor crash because of a missing alignment check in VCPUOP_register_vcpu_info. The hypercall VCPUOP_register_vcpu_info is used by a guest to register a shared region with the hypervisor. The region will be mapped into Xen address space so it can be directly accessed. On Arm, the region is accessed with instructions that require a specific alignment. Unfortunately, there is no check that the address provided by the guest will be correctly aligned. As a result, a malicious guest could cause a hypervisor crash by passing a misaligned address. A malicious guest administrator may cause a hypervisor crash, resulting in a Denial of Service (DoS). All Xen versions are vulnerable. Only Arm systems are vulnerable. x86 systems are not affected.

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An issue was discovered in Xen through 4.13.x, allowing x86 HVM guest OS users to cause a hypervisor crash. An inverted conditional in x86 HVM guests' dirty video RAM tracking code allows such guests to make Xen de-reference a pointer guaranteed to point at unmapped space. A malicious or buggy HVM guest may cause the hypervisor to crash, resulting in Denial of Service (DoS) affecting the entire host. Xen versions from 4.8 onwards are affected. Xen versions 4.7 and earlier are not affected. Only ... An issue was discovered in Xen through 4.13.x, allowing x86 HVM guest OS users to cause a hypervisor crash. An inverted conditional in x86 HVM guests' dirty video RAM tracking code allows such guests to make Xen de-reference a pointer guaranteed to point at unmapped space. A malicious or buggy HVM guest may cause the hypervisor to crash, resulting in Denial of Service (DoS) affecting the entire host. Xen versions from 4.8 onwards are affected. Xen versions 4.7 and earlier are not affected. Only x86 systems are affected. Arm systems are not affected. Only x86 HVM guests using shadow paging can leverage the vulnerability. In addition, there needs to be an entity actively monitoring a guest's video frame buffer (typically for display purposes) in order for such a guest to be able to leverage the vulnerability. x86 PV guests, as well as x86 HVM guests using hardware assisted paging (HAP), cannot leverage the vulnerability.

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Multiple buffer overflow vulnerabilities in REST API in Brocade Fabric OS versions v8.2.1 through v8.2.1d, and 8.2.2 versions before v8.2.2c could allow remote unauthenticated attackers to perform various attacks.

RIOT 2020.04 has a buffer overflow in the base64 decoder. The decoding function base64_decode() uses an output buffer estimation function to compute the required buffer capacity and validate against the provided buffer size. The base64_estimate_decode_size() function calculates the expected decoded size with an arithmetic round-off error and does not take into account possible padding bytes. Due to this underestimation, it may be possible to craft base64 input that causes a buffer overflow.

In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Crossbeam is a set of tools for concurrent programming. In crossbeam-channel before version 0.4.4, the bounded channel incorrectly assumes that `Vec::from_iter` has allocated capacity that same as the number of iterator elements. `Vec::from_iter` does not actually guarantee that and may allocate extra memory. The destructor of the `bounded` channel reconstructs `Vec` from the raw pointer based on the incorrect assumes described above. This is unsound and causing deallocation with the incorrect c ... Crossbeam is a set of tools for concurrent programming. In crossbeam-channel before version 0.4.4, the bounded channel incorrectly assumes that `Vec::from_iter` has allocated capacity that same as the number of iterator elements. `Vec::from_iter` does not actually guarantee that and may allocate extra memory. The destructor of the `bounded` channel reconstructs `Vec` from the raw pointer based on the incorrect assumes described above. This is unsound and causing deallocation with the incorrect capacity when `Vec::from_iter` has allocated different sizes with the number of iterator elements. This has been fixed in crossbeam-channel 0.4.4.

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In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potent ... In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

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In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is ... In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856 ... In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in ... In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the hea ... In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

In ACCEL-PPP (an implementation of PPTP/PPPoE/L2TP/SSTP), there is a buffer overflow when receiving an l2tp control packet ith an AVP which type is a string and no hidden flags, length set to less than 6. If your application is used in open networks or there are untrusted nodes in the network it is highly recommended to apply the patch. The problem was patched with commit 2324bcd5ba12cf28f47357a8f03cd41b7c04c52b As a workaround changes of commit 2324bcd5ba12cf28f47357a8f03cd41b7c04c52b can be ap ... In ACCEL-PPP (an implementation of PPTP/PPPoE/L2TP/SSTP), there is a buffer overflow when receiving an l2tp control packet ith an AVP which type is a string and no hidden flags, length set to less than 6. If your application is used in open networks or there are untrusted nodes in the network it is highly recommended to apply the patch. The problem was patched with commit 2324bcd5ba12cf28f47357a8f03cd41b7c04c52b As a workaround changes of commit 2324bcd5ba12cf28f47357a8f03cd41b7c04c52b can be applied to older versions.

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In libIEC61850 before version 1.4.3, when a message with COTP message length field with value < 4 is received an integer underflow will happen leading to heap buffer overflow. This can cause an application crash or on some platforms even the execution of remote code. If your application is used in open networks or there are untrusted nodes in the network it is highly recommend to apply the patch. This was patched with commit 033ab5b. Users of version 1.4.x should upgrade to version 1.4.3 when av ... In libIEC61850 before version 1.4.3, when a message with COTP message length field with value < 4 is received an integer underflow will happen leading to heap buffer overflow. This can cause an application crash or on some platforms even the execution of remote code. If your application is used in open networks or there are untrusted nodes in the network it is highly recommend to apply the patch. This was patched with commit 033ab5b. Users of version 1.4.x should upgrade to version 1.4.3 when available. As a workaround changes of commit 033ab5b can be applied to older versions.

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DIGITUS DA-70254 4-Port Gigabit Network Hub 2.073.000.E0008 devices allow an attacker on the same network to denial-of-service the device via long input values.

Lindy 42633 4-Port USB 2.0 Gigabit Network Server 2.078.000 devices allow an attacker on the same network to denial-of-service the device via long input values.

TP-Link USB Network Server TL-PS310U devices before 2.079.000.t0210 allow an attacker on the same network to denial-of-service the device via long input values.

An issue was discovered in the jsrsasign package before 8.0.17 for Node.js. Its RSASSA-PSS (RSA-PSS) implementation does not detect signature manipulation/modification by prepending '\0' bytes to a signature (it accepts these modified signatures as valid). An attacker can abuse this behavior in an application by creating multiple valid signatures where only one signature should exist. Also, an attacker might prepend these bytes with the goal of triggering memory corruption issues.

An issue was discovered in the jsrsasign package before 8.0.18 for Node.js. Its RSA PKCS1 v1.5 decryption implementation does not detect ciphertext modification by prepending '\0' bytes to ciphertexts (it decrypts modified ciphertexts without error). An attacker might prepend these bytes with the goal of triggering memory corruption issues.

An untrusted pointer dereference flaw was found in Perl-DBI < 1.643. A local attacker who is able to manipulate calls to dbd_db_login6_sv() could cause memory corruption, affecting the service's availability.

A flaw was found in the X.Org Server before version 1.20.10. An out-of-bounds access in the XkbSetMap function may lead to a privilege escalation vulnerability. The highest threat from this vulnerability is to data confidentiality and integrity as well as system availability.

A flaw was found in X.Org Server before xorg-x11-server 1.20.9. An Out-Of-Bounds access in XkbSetNames function may lead to a privilege escalation vulnerability. The highest threat from this vulnerability is to data confidentiality and integrity as well as system availability.

Memory overflow in Xiaomi AI speaker Rom version <1.59.6 can happen when the speaker verifying a malicious firmware during OTA process.

An issue was discovered on Samsung mobile devices with Q(10.0) (with TEEGRIS on Exynos chipsets) software. The Widevine Trustlet allows arbitrary code execution because of memory disclosure, The Samsung IDs are SVE-2020-17117, SVE-2020-17118, SVE-2020-17119, and SVE-2020-17161 (June 2020).

An issue was discovered on Samsung mobile devices with O(8.x) and P(9.0) (Exynos 7570 chipsets) software. The Trustonic Kinibi component allows arbitrary memory mapping. The Samsung ID is SVE-2019-16665 (June 2020).

hw/pci/msix.c in QEMU 4.2.0 allows guest OS users to trigger an out-of-bounds access via a crafted address in an msi-x mmio operation.

A denial-of-service vulnerability exists in the Ethernet/IP server functionality of Rockwell Automation RSLinx Classic 2.57.00.14 CPR 9 SR 3. A specially crafted network request can lead to a denial of service. An attacker can send a sequence of malicious packets to trigger this vulnerability.

An out-of-bounds write vulnerability exists in the SGI RLE decompression functionality of Accusoft ImageGear 19.8. A specially crafted malformed file can lead to code execution. An attacker can provide a malicious file to trigger this vulnerability.