rainbutterfly/cve_corpus huggingface dataset:
CVE-2021-37683 Division by zero in TensorFlow Lite division operations
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-369
description: CWE-369: Divide By Zero
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2021-08-12T22:30:23.000Z
CVE-2021-37684 Division by zero in TensorFlow Lite pooling operations
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-369
description: CWE-369: Divide By Zero
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2021-08-12T22:30:17.000Z
CVE-2021-37685 Heap OOB in TensorFlow Lite
TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-125
description: CWE-125: Out-of-bounds Read
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: NONE
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
version: 3.1
Published: 2021-08-12T22:15:10.000Z
CVE-2021-37686 Infinite loop in TensorFlow Lite
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for [ellipsis in axis definition](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). An attacker can craft a model such that `ellipsis_end_idx` is smaller than `i` (e.g., always negative). In this case, the inner loop does not increase `i` and the `continue` statement causes execution to skip over the preincrement at the end of the outer loop. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version.
Problem types: cwe_id: CWE-835
description: CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop')
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2021-08-12T21:55:11.000Z
CVE-2021-37687 Heap OOB in TensorFlow Lite's `Gather*` implementations
TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`GatherNd` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather_nd.cc#L124) does not support negative indices but there are no checks for this situation. Hence, an attacker can read arbitrary data from the heap by carefully crafting a model with negative values in `indices`. Similar issue exists in [`Gather` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather.cc). We have patched the issue in GitHub commits bb6a0383ed553c286f87ca88c207f6774d5c4a8f and eb921122119a6b6e470ee98b89e65d721663179d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-125
description: CWE-125: Out-of-bounds Read
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: NONE
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
version: 3.1
Published: 2021-08-12T22:15:17.000Z
CVE-2021-37688 Null pointer dereference in TensorFlow Lite
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 7.8
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
version: 3.1
Published: 2021-08-12T22:00:12.000Z
CVE-2021-37689 Null pointer dereference in TensorFlow Lite MLIR optimizations
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-476
description: CWE-476: NULL Pointer Dereference
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 7.8
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
version: 3.1
Published: 2021-08-12T22:00:19.000Z
CVE-2021-37690 Use after free and segfault in shape inference functions in TensorFlow
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-416
description: CWE-416: Use After Free
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 6.6
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
version: 3.1
Published: 2021-08-12T23:10:16.000Z
CVE-2021-37691 Division by zero in LSH in TensorFlow Lite
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Problem types: cwe_id: CWE-369
description: CWE-369: Divide By Zero
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2021-08-12T22:25:11.000Z
CVE-2021-37692 Segfault on strings tensors with mistmatched dimensions in TensorFlow
TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2021-08-12T23:00:14.000Z
CVE-2021-37693 Re-use of email tokens in Discourse
Discourse is an open-source platform for community discussion. In Discourse before versions 2.7.8 and 2.8.0.beta4, when adding additional email addresses to an existing account on a Discourse site an email token is generated as part of the email verification process. Deleting the additional email address does not invalidate an unused token which can then be used in other contexts, including reseting a password.
Problem types: cwe_id: CWE-640
description: CWE-640: Weak Password Recovery Mechanism for Forgotten Password
cwe_id: CWE-613
description: CWE-613: Insufficient Session Expiration
Affected products: vendor: discourse
product: discourse
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 5.3
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N
version: 3.1
Published: 2021-08-13T15:15:10.000Z
CVE-2021-37694 Code injection issue for java-spring-cloud-stream-template
@asyncapi/java-spring-cloud-stream-template generates a Spring Cloud Stream (SCSt) microservice. In versions prior to 0.7.0 arbitrary code injection was possible when an attacker controls the AsyncAPI document. An example is provided in GHSA-xj6r-2jpm-qvxp. There are no mitigations available and all users are advised to update.
Problem types: cwe_id: CWE-94
description: CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected products: vendor: asyncapi
product: java-spring-cloud-stream-template
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 8.7
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: HIGH
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:N
version: 3.1
Published: 2021-08-11T17:25:09.000Z
CVE-2021-37695 Execution of JavaScript code using malformed HTML in ckeditor
ckeditor is an open source WYSIWYG HTML editor with rich content support. A potential vulnerability has been discovered in CKEditor 4 [Fake Objects](https://ckeditor.com/cke4/addon/fakeobjects) package. The vulnerability allowed to inject malformed Fake Objects HTML, which could result in executing JavaScript code. It affects all users using the CKEditor 4 plugins listed above at version < 4.16.2. The problem has been recognized and patched. The fix will be available in version 4.16.2.
Problem types: cwe_id: CWE-79
description: CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Affected products: vendor: ckeditor
product: ckeditor4
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.3
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:N
version: 3.1
Published: 2021-08-12T23:10:10.000Z
CVE-2021-37696 Sensitive information leak in MassDM of tmerc-cogs
tmerc-cogs are a collection of open source plugins for the Red Discord bot. A vulnerability has been found in the code that allows any user to access sensitive information by crafting a specific MassDM message. Issue is patched in commit 92325be650a6c17940cc52611797533ed95dbbe1. All users are advised to update to the current commit. As a workaround users may unload the MassDM cog or globally disable the `[p]massdm` command.
Problem types: cwe_id: CWE-306
description: CWE-306: Missing Authentication for Critical Function
Affected products: vendor: tmercswims
product: tmerc-cogs
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.1
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N
version: 3.1
Published: 2021-08-11T22:55:09.000Z
CVE-2021-37697 Sensitive information leak in Welcome of tmerc-cogs
tmerc-cogs are a collection of open source plugins for the Red Discord bot. A vulnerability has been found in the code that allows any user to access sensitive information by crafting a specific membership event message. Issue is patched in commit d63c49b4cfc30c795336e4fff08cba3795e0fcc0. As a workaround users may unload the Welcome cog.
Problem types: cwe_id: CWE-306
description: CWE-306: Missing Authentication for Critical Function
Affected products: vendor: tmercswims
product: tmerc-cogs
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.1
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: LOW
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N
version: 3.1
Published: 2021-08-11T23:00:11.000Z
CVE-2021-37698 Missing TLS service certificate validation in GelfWriter, ElasticsearchWriter, InfluxdbWriter and Influxdb2Writer
Icinga is a monitoring system which checks the availability of network resources, notifies users of outages, and generates performance data for reporting. In versions 2.5.0 through 2.13.0, ElasticsearchWriter, GelfWriter, InfluxdbWriter and Influxdb2Writer do not verify the server's certificate despite a certificate authority being specified. Icinga 2 instances which connect to any of the mentioned time series databases (TSDBs) using TLS over a spoofable infrastructure should immediately upgrade to version 2.13.1, 2.12.6, or 2.11.11 to patch the issue. Such instances should also change the credentials (if any) used by the TSDB writer feature to authenticate against the TSDB. There are no workarounds aside from upgrading.
Problem types: cwe_id: CWE-295
description: CWE-295: Improper Certificate Validation
Affected products: vendor: Icinga
product: icinga2
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.5
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
version: 3.1
Published: 2021-08-19T13:55:10.000Z
CVE-2021-37699 Open Redirect in Next.js versions below 11.1.0
Next.js is an open source website development framework to be used with the React library. In affected versions specially encoded paths could be used when pages/_error.js was statically generated allowing an open redirect to occur to an external site. In general, this redirect does not directly harm users although can allow for phishing attacks by redirecting to an attacker's domain from a trusted domain. We recommend everyone to upgrade regardless of whether you can reproduce the issue or not. The issue has been patched in release 11.1.0.
Problem types: cwe_id: CWE-601
description: CWE-601: URL Redirection to Untrusted Site ('Open Redirect')
Affected products: vendor: vercel
product: next.js
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 6.9
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: LOW
privilegesRequired: NONE
scope: CHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:L/A:N
version: 3.1
Published: 2021-08-11T23:15:10.000Z
CVE-2021-37700 Clipboard-based DOM-XSS
@github/paste-markdown is an npm package for pasting markdown objects. A self Cross-Site Scripting vulnerability exists in the @github/paste-markdown before version 0.3.4. If the clipboard data contains the string `<table>`, a **div** is dynamically created, and the clipboard content is copied into its **innerHTML** property without any sanitization, resulting in improper execution of JavaScript in the browser of the victim (the user who pasted the code). Users directed to copy text from a malicious website and paste it into pages that utilize this library are affected. This is fixed in version 0.3.4. Refer the to the referenced GitHub Advisory for more details including an example exploit.
Problem types: cwe_id: CWE-79
description: CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Affected products: vendor: github
product: paste-markdown
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N
version: 3.1
Published: 2021-08-12T20:45:13.000Z