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| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-60731 | 1 Oracle | 1 Webcenter Portal | 2026-08-21 | 8.8 High |
| Vulnerability in the Oracle WebCenter Portal product of Oracle Fusion Middleware (component: Composer). Supported versions that are affected are 12.2.1.4.0 and 14.1.2.0.0. Easily exploitable vulnerability allows low privileged attacker with network access via RMI to compromise Oracle WebCenter Portal. Successful attacks of this vulnerability can result in takeover of Oracle WebCenter Portal. CVSS 3.1 Base Score 8.8 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). | ||||
| CVE-2026-60822 | 1 Oracle | 1 Enterprise Manager For Systems Infrastructure | 2026-08-21 | 7.8 High |
| Vulnerability in the Oracle Enterprise Manager for Systems Infrastructure product of Oracle Enterprise Manager (component: Agent). Supported versions that are affected are 13.5 and 24.1. Easily exploitable vulnerability allows low privileged attacker with logon to the infrastructure where Oracle Enterprise Manager for Systems Infrastructure executes to compromise Oracle Enterprise Manager for Systems Infrastructure. Successful attacks of this vulnerability can result in takeover of Oracle Enterprise Manager for Systems Infrastructure. CVSS 3.1 Base Score 7.8 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). | ||||
| CVE-2026-60895 | 1 Oracle | 1 Unified Directory | 2026-08-21 | 6.8 Medium |
| Vulnerability in the Oracle Unified Directory product of Oracle Fusion Middleware (component: OUD Core). Supported versions that are affected are 12.2.1.4.0 and 14.1.2.1.0. Difficult to exploit vulnerability allows low privileged attacker with network access via LDAP to compromise Oracle Unified Directory. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Unified Directory accessible data as well as unauthorized access to critical data or complete access to all Oracle Unified Directory accessible data. CVSS 3.1 Base Score 6.8 (Confidentiality and Integrity impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:N). | ||||
| CVE-2026-59323 | 1 Vmware | 1 Spring | 2026-08-21 | 5.3 Medium |
| An application using Micrometer Tracing with W3C baggage propagation in the Brave bridge is vulnerable to denial of service (DoS) due to unbounded object allocation when extracting incoming baggage headers. Specifically, an application is vulnerable when all the following are true: * The application uses a vulnerable version of io.micrometer:micrometer-tracing-bridge-brave. * W3C propagation is active (either configured manually or active by default, such as in Spring Boot 3.x+). * Baggage propagation is enabled (which is the default in Spring Boot 3.x+) and a baggage manager (such as BraveBaggageManager) is configured to handle baggage fields. * The application processes requests or messages from untrusted sources with baggage headers which it normally should not, see: https://www.w3.org/TR/trace-context/#security-considerations . * Network components including the (HTTP) server that receives the request do not limit the header size or the limit is high enough to cause issues. The last two points are very important: normally this should not affect applications because they should not receive untrusted and unlimited input for baggage. * The application processes requests or messages from untrusted sources with baggage headers. When extracting baggage from the W3C baggage header, incoming entries are parsed without enforcing limits on the number of entries or header size as mandated by the W3C Baggage specification. An attacker can send requests or messages with artificially inflated baggage headers containing many key-value pairs, causing unconditional BaggageField allocations per entry. This leads to garbage collection pressure, high CPU usage, and potential application crash via OutOfMemoryError. | ||||
| CVE-2026-41451 | 1 Tclahr | 1 Uac | 2026-08-21 | 7.8 High |
| UAC (Unix-like Artifacts Collector) versions prior to 3.3.0 contain a command injection vulnerability in the user substitution logic within parse_artifact.sh where usernames and home directories from /etc/passwd are substituted directly into command strings without escaping before execution via eval. Attackers can inject shell metacharacters such as command substitution syntax or semicolons through crafted usernames or home directory paths in /etc/passwd entries to execute arbitrary commands on the analyst's host system. | ||||
| CVE-2026-76397 | 1 Splunk | 2 Ai Toolkit, Splunk Ai Toolkit | 2026-08-21 | 8.1 High |
| In Splunk AI Toolkit versions below 6.0.0, a user who holds the "power" Splunk role could access and delete all relevant data in experiment history, including data associated with other users. The vulnerability is possible because Splunk AI Toolkit does not preserve the trusted experiment scope when it processes caller-controlled query values before accessing restricted history data. For more information see Experiment Assistants (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/use-ai-toolkit/5.6.4/experiment-assistants) in the Splunk documentation. | ||||
| CVE-2026-76396 | 1 Splunk | 2 Ai Toolkit, Splunk Ai Toolkit | 2026-08-21 | 7.5 High |
| In Splunk AI Toolkit versions below 6.0.0, a user that holds a role with the schedule_search capability could cause a scheduled search to load and deserialize a model file through the apply search command. The improper access control is possible because Splunk AI Toolkit does not mark the apply search command as risky. For more information see Troubleshoot the AI Toolkit (https://help.splunk.com/en/splunk-enterprise/apply-machine-learning/use-ai-toolkit/5.7.3/troubleshooting-the-ai-toolkit/troubleshoot-the-ai-toolkit) in the Splunk documentation. | ||||
| CVE-2026-54071 | 2026-08-21 | 7.8 High | ||
| BabelDOC is a document translation tool. Prior to 0.6.3, BabelDOC's vendored PDF parser in babeldoc/pdfminer/cmapdb.py deserializes untrusted pickle data when CMapDB._load_data() loads CMap files. PDF-controlled Encoding or CMapName values and embedded PostScript usecmap operators can reach this sink after path separators are decoded, while _normalize_cmap_name() removes only a leading slash. Absolute paths or traversal sequences can escape the trusted CMap directories through os.path.join(), select an attacker-writable .pickle.gz file, and cause pickle.loads() to execute arbitrary Python code with the privileges of the BabelDOC process. This issue is fixed in version 0.6.3. | ||||
| CVE-2026-76395 | 1 Splunk | 2 Ai Toolkit, Splunk Ai Toolkit | 2026-08-21 | 8.8 High |
| In Splunk AI Toolkit versions below 6.0.0, a user who holds the "power" Splunk role could execute arbitrary code on the Splunk server by loading a model file containing crafted sparse matrix data. The deserialization of untrusted data is possible because a model codec in Splunk AI Toolkit deserializes sparse matrix data without guarding against embedded pickle content. For more information see Troubleshoot the Splunk Machine Learning Toolkit (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/machine-learning-toolkit-user-guide/5.5.0/troubleshooting-mltk/troubleshoot-the-splunk-machine-learning-toolkit) in the Splunk documentation. | ||||
| CVE-2026-76394 | 1 Splunk | 2 Ai Toolkit, Splunk Ai Toolkit | 2026-08-21 | 8.3 High |
| In Splunk AI Toolkit versions below 6.0.0, a low-privileged user who does not hold the "admin" or "power" Splunk roles could start, stop, and configure containers, and read or modify connection and configuration data through the Representational State Transfer (REST) API. The missing authorization is possible because multiple REST API handlers in Splunk AI Toolkit do not enforce authorization checks. For more information see Troubleshoot the Splunk Machine Learning Toolkit (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/machine-learning-toolkit-user-guide/5.5.0/troubleshooting-mltk/troubleshoot-the-splunk-machine-learning-toolkit) in the Splunk documentation. | ||||
| CVE-2026-76393 | 1 Splunk | 2 Ai Toolkit, Splunk Ai Toolkit | 2026-08-21 | 5.9 Medium |
| In Splunk AI Toolkit versions below 6.0.0, a user who can upload models could overwrite a model being uploaded by another user by sending a concurrent upload request for the same model name, causing the resulting model lookup entry to reference attacker-controlled content. The race condition is possible because Splunk AI Toolkit does not verify that the uploaded content belongs to the request that creates the model lookup entry. For more information see Troubleshoot the Splunk Machine Learning Toolkit (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/machine-learning-toolkit-user-guide/5.5.0/troubleshooting-mltk/troubleshoot-the-splunk-machine-learning-toolkit) in the Splunk documentation. | ||||
| CVE-2026-76392 | 1 Splunk | 1 Ai Toolkit | 2026-08-21 | 5.4 Medium |
| In Splunk AI Toolkit versions below 6.0.0, a user who does not hold the "admin" or "power" Splunk roles could obtain predictable or default credentials for connected container services. The use of hard-coded credentials is possible because Splunk AI Toolkit generates or stores credentials for connected container services using predictable or hard-coded default values. For more information see Connections tab in the AI Toolkit (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/use-ai-toolkit/5.7.2/ai-toolkit-commands-macros-and-visualizations/connections-tab-in-the-ai-toolkit) in the Splunk documentation. | ||||
| CVE-2026-54073 | 2026-08-21 | N/A | ||
| VeraCrypt provides disk encryption with strong security based on TrueCrypt. From 1.26.6 until 1.26.29, file-hosted hidden volume creation forces quick format and the FormatNoFs function in src/Common/Format.c and FormatFat function in src/Common/Fat.c use WriteFile to place raw zeroed sectors at predictable 128 MiB intervals. These writes bypass the normal EncryptDataUnits formatting path, leaving deterministic plaintext markers in an area expected to resemble random ciphertext. The markers can weaken plausible deniability during forensic inspection, although they do not disclose hidden-volume content or reduce the strength of VeraCrypt encryption. This issue is fixed in version 1.26.29. | ||||
| CVE-2026-76391 | 1 Splunk | 1 Ai Toolkit | 2026-08-21 | 8.3 High |
| In Splunk AI Toolkit versions below 6.0.0, a user who does not hold the "admin" or "power" Splunk roles could run searches with system-level privileges, access all relevant data, affect system integrity, and read or delete search jobs belonging to other users through Agent Run History. The improper privilege management is possible because the Agent Run History handler replaces the calling user session key with a system authentication token before it performs search operations. For more information see AI Toolkit Agent Launchpad (https://help.splunk.com/en/splunk-enterprise/apply-machine-learning/use-ai-toolkit/6.0.0/ai-toolkit-connections-containers-and-agents/ai-toolkit-agent-launchpad) in the Splunk documentation. | ||||
| CVE-2026-53762 | 2026-08-21 | 6.2 Medium | ||
| VeraCrypt provides disk encryption with strong security based on TrueCrypt. Prior to 1.26.29, non-default builds created with WOLFCRYPT=1 and WOLFCRYPT_BACKEND route SHA-256 and SHA-512 volume-header key derivation through derive_key_sha256 and derive_key_sha512 in src/Crypto/wolfCrypt.c, where the configured iterations value is discarded and wc_HKDF is used instead of PBKDF2-HMAC. Changing the PIM or iteration count therefore does not increase derivation cost, allowing an attacker with an affected container, disk image, or volume header to perform substantially cheaper offline password guesses. Official precompiled VeraCrypt binaries and normal distribution packages use the standard PBKDF2 backend and are not affected. Volumes created by an affected WOLFCRYPT=1 build require backup and recreation because corrected builds derive different keys. This issue is fixed in version 1.26.29. | ||||
| CVE-2026-52606 | 2026-08-21 | 6.1 Medium | ||
| A reflected cross-site scripting (XSS) vulnerability in reportico-web <= 8.1.0 allows remote attackers to execute arbitrary JavaScript in the web browser of a user by including a malicious payload in the loadTemplate parameter in conjunction with the execute_mode=PREPARE parameter of run.php. | ||||
| CVE-2026-52609 | 2026-08-21 | 6.1 Medium | ||
| A reflected cross-site scripting (XSS) vulnerability in reportico-web <= 8.1.0 allows remote attackers to execute arbitrary JavaScript in the web browser of a user by including a malicious payload in the reportico_criteria parameter in conjunction with the execute_mode=CRITERIA parameter of run.php. | ||||
| CVE-2026-67921 | 2026-08-21 | 9.3 Critical | ||
| Cross-Site Request Forgery (CSRF) vulnerability exists in Halo CMS versions up to 2.25.4 via the CorsConfigurer.java and the CsrfConfigurer.java components. This allows a remote attacker to execute arbitrary code. | ||||
| CVE-2026-71676 | 2026-08-21 | 7.5 High | ||
| Buffer Overflow vulnerability in Open5GS v.2.7.0 allows a remote attacker to cause a denial of service via the NAS 5GS decoder chain, triggered when the message type byte of a NAS PDU is mutated | ||||
| CVE-2026-3985 | 2 Constantcontact, Wordpress | 2 Creative Mail – Easier Wordpress & Woocommerce Email Marketing, Wordpress | 2026-08-21 | 7.5 High |
| The Creative Mail – Easier WordPress & WooCommerce Email Marketing plugin for WordPress is vulnerable to SQL Injection via the 'checkout_uuid' parameter in all versions up to, and including, 1.6.9. This is due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query in the `has_checkout_consent()` method. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database. | ||||