| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| An out-of-bounds read was addressed with improved bounds checking. This issue is fixed in macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7. Connecting to a malicious NFS server may cause unexpected system termination or corrupt kernel memory. |
| Privilege escalation due to incorrect boundary conditions in the Graphics: WebRender component. This vulnerability was fixed in Firefox 156, Firefox ESR 115.41, Firefox ESR 140.16, Firefox ESR 153.3, Thunderbird 156, Thunderbird 140.16, and Thunderbird 153.3. |
| Privilege escalation due to incorrect boundary conditions in the Graphics: CanvasWebGL component. This vulnerability was fixed in Firefox 156, Firefox ESR 115.41, Firefox ESR 140.16, Firefox ESR 153.3, Thunderbird 156, Thunderbird 140.16, and Thunderbird 153.3. |
| Privilege escalation due to incorrect boundary conditions in the Graphics: CanvasWebGL component. This vulnerability was fixed in Firefox 156, Firefox ESR 115.41, Firefox ESR 140.16, Firefox ESR 153.3, Thunderbird 156, Thunderbird 140.16, and Thunderbird 153.3. |
| zlt2000 microservices-platform through 6.0.0 contains a missing authorization vulnerability where the zlt.security.auth.urlPermission.enable flag defaults to false, disabling all permission checks after authentication. Authenticated users with no roles can access administrative APIs including user management, role assignment, and Elasticsearch index operations by bypassing the disabled authorization enforcement. |
| Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, Ember’s HTTP/1.1 parser accepts differing duplicate Content-Length headers and uses the last value instead of rejecting the message. When an Ember server is behind a keep-alive intermediary that selects a different occurrence, an unauthenticated attacker can create CL.CL request smuggling that bypasses front-end controls, captures a later user’s headers, or poisons a cache. The shared client parser can also misframe responses from a malicious or compromised upstream when the client acts as a proxy for multiple downstream consumers. This issue is fixed in versions 0.23.35 and 1.0.0-M47. |
| Vulnerability in the Oracle Hyperion Financial Management product of Oracle Hyperion (component: Security). The supported version that is affected is 11.2.26.0.000. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Hyperion Financial Management. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Hyperion Financial Management accessible data and unauthorized ability to cause a partial denial of service (partial DOS) of Oracle Hyperion Financial Management. CVSS 3.1 Base Score 7.1 (Confidentiality and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L). |
| Vulnerability in the Oracle Hyperion Financial Management product of Oracle Hyperion (component: Security). The supported version that is affected is 11.2.26.0.000. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Hyperion Financial Management. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Hyperion Financial Management accessible data and unauthorized ability to cause a partial denial of service (partial DOS) of Oracle Hyperion Financial Management. CVSS 3.1 Base Score 7.1 (Confidentiality and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L). |
| An integer overflow was addressed with improved input validation. This issue is fixed in Safari 26.6.1, iOS 26.6.1 and iPadOS 26.6.1, macOS Tahoe 26.6.2, tvOS 27, visionOS 27, watchOS 27. Processing maliciously crafted web content may lead to memory corruption. |
| An out-of-bounds write issue was addressed with improved bounds checking. This issue is fixed in Safari 26.6.1, iOS 26.6.1 and iPadOS 26.6.1, macOS Tahoe 26.6.2, tvOS 27, visionOS 27, watchOS 27. Processing maliciously crafted web content may lead to memory corruption. |
| On affected platforms running Arista EOS with OpenConfig-related services (i.e., gNMI, gNSI, RESTCONF and NETCONF), sensitive requests and responses may be unintentionally logged. These may be stored on the local EOS device or recorded on remote accounting servers. Note that gRPC-based streaming via Streaming Telemetry Agent to CloudVision is not affected by this vulnerability.
Examples of sensitive information include:
- Sensitive CLI commands (e.g., "username bob secret myPass")
- Sensitive OpenConfig YANG leafs (e.g., "system/aaa/global/tacacs/config/secret-key")
This issue was discovered internally by Arista, and the company is not aware of any malicious exploitation of this vulnerability in customer networks. |
| The MCP Streamable HTTP server transport (WebFlux and WebMvc variants) does not place any limit on the number of sessions it retains, and by default does not require clients to be authenticated. As a result, a remote attacker can cause the server to accumulate an unbounded number of sessions over time, gradually exhausting available memory and ultimately causing a Denial of Service that affects all legitimate clients.
Affected versions:
Spring AI: 2.0.0 |
| Authentication bypass by capture-replay in Microsoft Authentication Library (MSAL) for Node.js allows an unauthorized attacker to perform spoofing over a network. |
| Nodemailer versions 9.1.0 through 10.0.4 contain a quadratic time complexity vulnerability in the addressparser component when parsing email addresses with RFC 5322 comments. Attackers can craft malicious email headers with comment-separated atoms to consume excessive CPU and block the Node.js event loop for several seconds, causing denial of service. |
| OOM Denial of Service via Unbounded Map Pre-Sizing in Apache OpenNLP SymSpellModelSerializer
Versions Affected:
- 3.0.0-M4
- 3.0.0-M5
(The opennlp-spellcheck extension was introduced in 3.0.0-M4. Releases 1.x and 2.x do not contain the affected code.)
Description:
The SymSpellModelSerializer.create() method reads two 32-bit signed integer count fields (unigramCount and bigramCount) from a binary SymSpell model stream and passes each value directly to LinkedHashMap.newLinkedHashMap() after validating only that it is non-negative. No upper bound is applied, so the count is fully attacker-controlled when the model file originates from an untrusted source.
A crafted .bin model file in which either count field is set to Integer.MAX_VALUE (or any value large enough to exhaust the available heap) causes the map to be pre-sized to a capacity of 2^30 entries. The oversized backing array is allocated on the first put() into that map, requesting 4–8 GB depending on whether compressed oops are in effect, and the load fails with an OutOfMemoryError. Because the count fields sit immediately after a fixed-size header (magic, format version, three UTF strings, the configuration fields, and the edit-distance identifier) the attacker pays no meaningful size cost to weaponize a payload: a file of well under 100 bytes plus a single real entry is sufficient to crash a JVM that loads it.
Any code path that deserializes a SymSpell model is affected, including SymSpellModels.deserialize(InputStream), SymSpellModels.fromBytes(byte[]), classpath model loading via SymSpellModelResolver.resolveByLanguage(String), the CorrectTextTool command-line tool, and model-archive loading through the registered ArtifactSerializer. The opennlp-spellcheck extension ships in the official OpenNLP binary distribution.
The practical impact is denial of service against processes that load SymSpell model files from untrusted or semi-trusted origins.
Mitigation:
- 3.x users should upgrade to 3.0.0-M6.
Note: The fix applies an upper bound to both count fields, checked before the map is pre-sized; counts that are negative or exceed the bound cause an IOException to be thrown and the read to fail fast with no large allocation. The bound is the existing AbstractModelReader.MAX_ENTRIES limit introduced earlie, which the current change promotes to public visibility so that serializers implementing their own binary format can share it. The default bound is 10,000,000, which is well above the entry counts of legitimate SymSpell dictionaries but far below any value that would threaten heap exhaustion. Deployments that legitimately need to load larger dictionaries can raise the limit at JVM startup by setting the OPENNLP_MAX_ENTRIES system property to the desired positive integer (e.g. -DOPENNLP_MAX_ENTRIES=50000000); invalid or non-positive values fall back to the default. Note that this property is shared with the model-reader limit and raising it relaxes both.
Users who cannot upgrade immediately should treat all SymSpell .bin model files as untrusted input unless their provenance is verified, and should avoid loading models supplied by end users or fetched from third-party repositories without integrity checks. |
| LangBot before 4.10.11 generates password recovery keys with only 24 bits of entropy and applies no rate limiting to the unauthenticated reset-password endpoint. Remote attackers knowing the administrator email can exhaust the keyspace through concurrent requests to reset the admin password and gain account access. |
| In ONNX before 1.21.0, the 'save_external_data' function builds the external-data file path from the model's external_data location field and opens it for writing without 'O_NOFOLLOW/O_EXCL', after a non-atomic 'os.path.isfile()' check. A local attacker with write access to the directory where a victim serializes external data can deterministically pre-plant a symlink that is being followed, causing the victim's write to append to any file the victim can write, e.g. ~/.ssh/authorized_keys, cron files, or application configs. Fixed in 1.21.0. |
| Vulnerability in the Oracle Purchasing product of Oracle E-Business Suite (component: G-Invoicing). Supported versions that are affected are 12.2.10-12.2.15. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Purchasing. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Purchasing accessible data as well as unauthorized access to critical data or complete access to all Oracle Purchasing accessible data. CVSS 3.1 Base Score 8.1 (Confidentiality and Integrity impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N). |
| Out-of-bounds read in Microsoft Windows Media Foundation allows an unauthorized attacker to execute code over a network. |
| Strimzi provides a way to run an Apache Kafka cluster on Kubernetes or OpenShift in various deployment configurations. In Strimzi 1.0.0 and earlier, an attacker who can create a Kafka custom resource can set Kafka.spec.entityOperator watchedNamespace to a target namespace, causing the Cluster Operator to create a Role with full Secret CRUD permissions there and bind it to the Entity Operator ServiceAccount in the attacker's namespace. The attacker can mint a token for that ServiceAccount and read or write Secrets in any target namespace where the Cluster Operator has been granted permissions, regardless of STRIMZI_NAMESPACE. This issue is fixed in versions 1.0.1 and 1.1.0. |
