| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A vulnerability was found in Quay, which allows successful authentication even when a truncated password version is provided. This flaw affects the authentication mechanism, reducing the overall security of password enforcement. While the risk is relatively low due to the typical length of the passwords used (73 characters), this vulnerability can still be exploited to reduce the complexity of brute-force or password-guessing attacks. The truncation of passwords weakens the overall authentication process, thereby reducing the effectiveness of password policies and potentially increasing the risk of unauthorized access in the future. |
| A flaw was found in Quay. Cross-site request forgery (CSRF) attacks force a user to perform unwanted actions in an application. During the pentest, it was detected that the config-editor page is vulnerable to CSRF. The config-editor page is used to configure the Quay instance. By coercing the victim’s browser into sending an attacker-controlled request from another domain, it is possible to reconfigure the Quay instance (including adding users with admin privileges). |
| A flaw was found in the Quay registry. While the image labels created through Quay undergo validation both in the UI and backend by applying a regex (validation.py), the same validation is
not performed when the label comes from an image. This flaw allows an attacker to publish a malicious image to a public registry containing a script that can be executed via Cross-site scripting (XSS). |
| cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. In affected versions `Cipher.update_into` would accept Python objects which implement the buffer protocol, but provide only immutable buffers. This would allow immutable objects (such as `bytes`) to be mutated, thus violating fundamental rules of Python and resulting in corrupted output. This now correctly raises an exception. This issue has been present since `update_into` was originally introduced in cryptography 1.8. |
| A flaw was found in python. In algorithms with quadratic time complexity using non-binary bases, when using int("text"), a system could take 50ms to parse an int string with 100,000 digits and 5s for 1,000,000 digits (float, decimal, int.from_bytes(), and int() for binary bases 2, 4, 8, 16, and 32 are not affected). The highest threat from this vulnerability is to system availability. |
| Pillow before 8.1.2 allows attackers to cause a denial of service (memory consumption) because the reported size of a contained image is not properly checked for an ICO container, and thus an attempted memory allocation can be very large. |
| Pillow before 8.1.2 allows attackers to cause a denial of service (memory consumption) because the reported size of a contained image is not properly checked for an ICNS container, and thus an attempted memory allocation can be very large. |
| Pillow before 8.1.2 allows attackers to cause a denial of service (memory consumption) because the reported size of a contained image is not properly checked for a BLP container, and thus an attempted memory allocation can be very large. |
| Werkzeug is a comprehensive WSGI web application library. Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses `request.data`, `request.form`, `request.files`, or `request.get_data(parse_form_data=False)`, it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers. Version 2.2.3 contains a patch for this issue. |
| Flask is a lightweight WSGI web application framework. When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches `Set-Cookie` headers, it may send one client's `session` cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met.
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets `session.permanent = True`
3. The application does not access or modify the session at any point during a request.
4. `SESSION_REFRESH_EACH_REQUEST` enabled (the default).
5. The application does not set a `Cache-Control` header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the `Vary: Cookie` header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified. This issue has been fixed in versions 2.3.2 and 2.2.5. |
| Some HTTP/2 implementations are vulnerable to window size manipulation and stream prioritization manipulation, potentially leading to a denial of service. The attacker requests a large amount of data from a specified resource over multiple streams. They manipulate window size and stream priority to force the server to queue the data in 1-byte chunks. Depending on how efficiently this data is queued, this can consume excess CPU, memory, or both. |
| Some HTTP/2 implementations are vulnerable to a settings flood, potentially leading to a denial of service. The attacker sends a stream of SETTINGS frames to the peer. Since the RFC requires that the peer reply with one acknowledgement per SETTINGS frame, an empty SETTINGS frame is almost equivalent in behavior to a ping. Depending on how efficiently this data is queued, this can consume excess CPU, memory, or both. |
| Some HTTP/2 implementations are vulnerable to a flood of empty frames, potentially leading to a denial of service. The attacker sends a stream of frames with an empty payload and without the end-of-stream flag. These frames can be DATA, HEADERS, CONTINUATION and/or PUSH_PROMISE. The peer spends time processing each frame disproportionate to attack bandwidth. This can consume excess CPU. |
| Some HTTP/2 implementations are vulnerable to unconstrained interal data buffering, potentially leading to a denial of service. The attacker opens the HTTP/2 window so the peer can send without constraint; however, they leave the TCP window closed so the peer cannot actually write (many of) the bytes on the wire. The attacker then sends a stream of requests for a large response object. Depending on how the servers queue the responses, this can consume excess memory, CPU, or both. |
| Some HTTP/2 implementations are vulnerable to a header leak, potentially leading to a denial of service. The attacker sends a stream of headers with a 0-length header name and 0-length header value, optionally Huffman encoded into 1-byte or greater headers. Some implementations allocate memory for these headers and keep the allocation alive until the session dies. This can consume excess memory. |
| Some HTTP/2 implementations are vulnerable to a reset flood, potentially leading to a denial of service. The attacker opens a number of streams and sends an invalid request over each stream that should solicit a stream of RST_STREAM frames from the peer. Depending on how the peer queues the RST_STREAM frames, this can consume excess memory, CPU, or both. |
| Some HTTP/2 implementations are vulnerable to resource loops, potentially leading to a denial of service. The attacker creates multiple request streams and continually shuffles the priority of the streams in a way that causes substantial churn to the priority tree. This can consume excess CPU. |
| A vulnerability was found in Quay. If an attacker can obtain the client ID for an application, they can use an OAuth token to authenticate despite not having access to the organization from which the application was created. This issue is limited to authentication and not authorization. However, in configurations where endpoints rely only on authentication, a user may authenticate to applications they otherwise have no access to. |
| A flaw was found in Keystone. There is a time lag (up to one hour in a default configuration) between when security policy says a token should be revoked from when it is actually revoked. This could allow a remote administrator to secretly maintain access for longer than expected. |
| A privilege escalation flaw was found in Podman. This flaw allows an attacker to publish a malicious image to a public registry. Once this image is downloaded by a potential victim, the vulnerability is triggered after a user runs the 'podman top' command. This action gives the attacker access to the host filesystem, leading to information disclosure or denial of service. |
