Apache Polaris can issue broad temporary ("vended") storage credentials during staged table creation before the effective table location has been validated or durably reserved. Those temporary credentials are meant to limit the scope of accessible table data and metadata, but this scope limitation becomes attacker- directed because the attacker can choose a reachable target location. In the confirmed variant, if the caller supplies a custom `location` during stage create and requests credential vending, Apache Polaris uses that location to construct delegated storage credentials immediately. The stage-create path itself neither runs the normal location validation nor the overlap checks before those credentials are issued. Closely related to that, the staged-create flow also accepts `write.data.path` / `write.metadata.path` in the request properties and feeds those location overrides into the same effective table location set used for credential vending. Those fields are secondary to the main custom-`location` exploit, but they are still attacker-influenced location inputs that should be validated before any credentials are issued.

OOM Denial of Service via Unbounded Array Allocation in Apache OpenNLP AbstractModelReader  Versions Affected:  before 2.5.9 before 3.0.0-M3  Description: The AbstractModelReader methods getOutcomes(), getOutcomePatterns(), and getPredicates() each read a 32-bit signed integer count field from a binary model stream and pass that value directly to an array allocation (new String[numOutcomes], new int[numOCTypes][], new String[NUM_PREDS]) without validating that the value is non-negative or within a reasonable bound. The count is therefore fully attacker-controlled when the model file originates from an untrusted source. A crafted .bin model file in which any of these count fields is set to Integer.MAX_VALUE (or any value large enough to exhaust the available heap) triggers an OutOfMemoryError at the array allocation itself, before the corresponding label or pattern data is consumed from the stream. The error occurs very early in deserialization: for a GIS model, getOutcomes() is reached after only the model-type string, the correction constant, and the correction parameter have been read; so the attacker pays no meaningful size cost to weaponize a payload, and a single small file can crash a JVM that loads it. Any code path that deserializes a .bin model is affected, including direct use of GenericModelReader and any higher-level component that delegates to it during model load. The practical impact is denial of service against processes that load model files from untrusted or semi-trusted origins.   Mitigation: * 2.x users should upgrade to 2.5.9. * 3.x users should upgrade to 3.0.0-M3. Note: The fix introduces an upper bound on each of the three count fields, checked before array allocation; counts that are negative or exceed the bound cause an IllegalArgumentException to be thrown and the read to fail fast with no large allocation. The default bound is 10,000,000, which is well above the entry counts of legitimate OpenNLP models but far below any value that would threaten heap exhaustion. Deployments that legitimately need to load models with more entries than the default 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. Users who cannot upgrade immediately should treat all .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.

D-Link DIR-456U Hardware Revision A1 (End-of-Life, EOL) contains a hardcoded telnet backdoor. The device starts a telnet daemon at boot via /etc/init0.d/S80telnetd.sh with the username "Alphanetworks" and the static password "whdrv01_dlob_dir456U" read from /etc/config/image_sign. The custom telnetd binary accepts a -u user:password flag, and the custom login binary uses strcmp() to validate credentials. Successful authentication grants an unauthenticated attacker on the local network a root shell with full administrative control. The device has reached End-of-Life (EOL) and will not receive patches.

D-Link DIR-600L Hardware Revision A1 (End-of-Life) contains a hardcoded telnet backdoor. The device starts a telnet daemon at boot via /bin/telnetd.sh with the username "Alphanetworks" and the static password "wrgn35_dlwbr_dir600l" read from /etc/alpha_config/image_sign. The custom telnetd binary accepts a -u user:password flag, and the custom login binary uses strcmp() to validate credentials. Successful authentication grants an unauthenticated attacker on the local network a root shell with full administrative control. The device has reached End-of-Life (EOL) and will not receive patches.

D-Link DIR-600L Hardware Revision B1 (End-of-Life) contains a hardcoded telnet backdoor. The device starts a telnet daemon at boot via /bin/telnetd.sh with the username "Alphanetworks" and the static password "wrgn61_dlwbr_dir600L" read from /etc/alpha_config/image_sign. The custom telnetd binary accepts a -u user:password flag, and the custom login binary uses strcmp() to validate credentials. Successful authentication grants an unauthenticated attacker on the local network a root shell with full administrative control.  The device has reached End-of-Life (EOL) and will not receive patches.

D-Link DIR-605L Hardware Revision B2 (End-of-Life, EOL) contains a hardcoded telnet backdoor. The device starts a telnet daemon at boot via /bin/telnetd.sh with the username "Alphanetworks" and the static password "wrgn76_dlwbr_dir605L" read from /etc/alpha_config/image_sign. The custom telnetd binary accepts a -u user:password flag, and the custom login binary uses strcmp() to validate credentials. Successful authentication grants an unauthenticated attacker on the local network a root shell with full administrative control. The device has reached End-of-Life (EOL) and will not receive patches.

D-Link DIR-605L Hardware Revision A1 (End-of-Life, EOL) contains a hardcoded telnet backdoor. The device starts a telnet daemon at boot via /bin/telnetd.sh with the username "Alphanetworks" and the static password "wrgn35_dlwbr_dir605l" read from /etc/alpha_config/image_sign. The custom telnetd binary accepts a -u user:password flag, and the custom login binary uses strcmp() to validate credentials. Successful authentication grants an unauthenticated attacker on the local network a root shell with full administrative control. The device has reached End-of-Life (EOL) and will not receive patches.

Notesnook is a note-taking app focused on user privacy & ease of use. Prior to Notesnook Web/Desktop version 3.3.15 and prior to Notesnook iOS/Android version 3.3.20, a stored XSS vulnerability in the note export flow can be escalated to remote code execution in the desktop app. The root cause is that exported note fields such as title, headline, and content are inserted into the generated HTML template without HTML escaping. When the note is later exported to PDF, Notesnook renders that HTML into a same-origin, unsandboxed iframe using iframe.srcdoc = .... Injected script executes in the Notesnook origin. In the desktop app, this becomes RCE because Electron is configured with nodeIntegration: true and contextIsolation: false. This issue has been patched in Notesnook Web/Desktop version 3.3.15 and Notesnook iOS/Android version 3.3.20.

PPTAgent is an agentic framework for reflective PowerPoint generation. Prior to commit 418491a, there is an arbitrary file write vulnerability via `save_generated_slides`. This issue has been patched via commit 418491a.

PPTAgent is an agentic framework for reflective PowerPoint generation. Prior to commit 418491a, PPTAgent is vulnerable to arbitrary code execution via Python eval() of LLM-generated code with builtins in scope. This issue has been patched via commit 418491a.

PPTAgent is an agentic framework for reflective PowerPoint generation. Prior to commit 418491a, PPTAgent is vulnerable to arbitrary file write and directory creation via markdown_table_to_image. This issue has been patched via commit 418491a.

Evolver is a GEP-powered self-evolving engine for AI agents. Prior to version 1.69.3, a prototype pollution vulnerability in the mailbox store module allows attackers to modify the behavior of all JavaScript objects by injecting malicious properties into Object.prototype. The vulnerability exists in the _applyUpdate() and _updateRecord() functions which use Object.assign() to merge user-controlled data without filtering dangerous keys like __proto__, constructor, or prototype. This issue has been patched in version 1.69.3.

Evolver is a GEP-powered self-evolving engine for AI agents. Prior to version 1.69.3, a command injection vulnerability in the _extractLLM() function allows attackers to execute arbitrary shell commands on the server. The function constructs a curl command using string concatenation and passes it to execSync() without proper sanitization, enabling remote code execution when the corpus parameter contains shell metacharacters. This issue has been patched in version 1.69.3.

Evolver is a GEP-powered self-evolving engine for AI agents. Prior to version 1.69.3, a path traversal vulnerability in the skill download (fetch) command allows attackers to write files to arbitrary locations on the filesystem. The --out= flag accepts user-provided paths without validation, enabling directory traversal attacks that can overwrite critical system files or create files in sensitive location. This issue has been patched in version 1.69.3.

Arbitrary Class Instantiation via Model Manifest in Apache OpenNLP ExtensionLoader Versions Affected: before 2.5.9, before 3.0.0-M3 Description:  The ExtensionLoader.instantiateExtension(Class, String) method loads a class by its fully-qualified name via Class.forName() and invokes its no-arg constructor, with the class name sourced from the manifest.properties entry of a model archive. The existing isAssignableFrom check correctly rejects classes that are not subtypes of the expected extension interface (BaseToolFactory for factory=, ArtifactSerializer for serializer-class-*), but the check runs after Class.forName() has already loaded and initialized the named class. Class.forName() with default initialization semantics executes the target class's static initializer before returning, so an attacker who can supply a crafted model archive can cause the static initializer of any class on the classpath to run during model loading, regardless of whether that class passes the subsequent type check. Exploitation requires a class with attacker-useful side effects in its static initializer (for example, JNDI lookup, outbound network I/O, or filesystem access) to be present on the classpath, so this is not a drop-in remote code execution; however, the attack surface grows as third-party model distribution becomes more common (community model repositories, Hugging Face-style sharing), where users routinely load model files from origins they do not control. A secondary, narrower vector affects deployments that ship legitimate BaseToolFactory or ArtifactSerializer subclasses with side-effecting no-arg constructors: a malicious manifest can name such a class and force its constructor to run during model load. Mitigation:  * 2.x users should upgrade to 2.5.9. * 3.x users should upgrade to 3.0.0-M3. Note: The fix introduces a package-prefix allowlist that is consulted before Class.forName() is invoked, so the static initializer of a disallowed class is never executed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing factories or serializers outside opennlp.* must opt those packages in, either programmatically via ExtensionLoader.registerAllowedPackage(String) before the first model load, or by setting the OPENNLP_EXT_ALLOWED_PACKAGES system property to a comma-separated list of allowed package prefixes. Users who cannot upgrade immediately should ensure that all model files are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors, particularly any that perform JNDI lookups, network requests, or filesystem operations during class initialization.

XML External Entity (XXE) via Unsanitized Dictionary Parsing in Apache OpenNLP DictionaryEntryPersistor Versions Affected: before 2.5.9, before 3.0.0-M3 Description: The DictionaryEntryPersistor class initializes a static SAXParserFactory at class-load time without enabling FEATURE_SECURE_PROCESSING or disabling DTD processing. When create(InputStream, EntryInserter) is invoked, the only feature set on the XMLReader is namespace support — external entity resolution and DOCTYPE declarations remain fully enabled. An attacker who can supply a crafted dictionary file (e.g., a stop-word list or domain dictionary) containing a malicious DOCTYPE declaration can trigger local file disclosure via file:// entity references or server-side request forgery via http:// entity references during SAX parsing, before the application processes a single dictionary entry. This is inconsistent with the project's own XmlUtil.createSaxParser() helper, which correctly sets FEATURE_SECURE_PROCESSING and disallow-doctype-decl and is used by all other XML parsing paths in the codebase. The public Dictionary(InputStream) constructor delegates directly to this method and is the documented API for loading user-supplied dictionaries, making untrusted input a realistic scenario. Mitigation: 2.x users should upgrade to 2.5.9. 3.x users should upgrade to 3.0.0-M3. Users who cannot upgrade immediately should ensure that all dictionary files are sourced from trusted origins and should consider wrapping the Dictionary(InputStream) constructor with input validation that rejects any XML containing a DOCTYPE declaration before it reaches the parser.

wCMS v.1.4 is vulnerable to Cross Site Scripting (XSS) when creating a new blog.

An out-of-bounds read in the ParseIP6Extended function (/bgp/bgp.go) of gobgp v4.3.0 allows attackers to cause a Denial of Service (DoS) via supplying a crafted BGP UPDATE message.

NetBox versions 4.3.5 through 4.5.4 contain a remote code execution vulnerability in the RenderTemplateMixin.get_environment_params() method that allows authenticated users with exporttemplate or configtemplate permissions to execute arbitrary code by specifying malicious Python callables in the environment_params field. Attackers can bypass Jinja2 SandboxedEnvironment protections by setting the finalize parameter to any importable Python callable such as subprocess.getoutput, which is invoked on every rendered expression outside the sandbox's call interception mechanism, achieving remote code execution as the NetBox service user.

vm2 is an open source vm/sandbox for Node.js. In version 3.10.4, vm2 is vulnerable to full sandbox escape with arbitrary code execution. Attacker code inside VM.run() obtains host process object and runs host commands with zero host cooperation. This issue has been patched in version 3.10.5.

vm2 is an open source vm/sandbox for Node.js. Prior to version 3.11.0, SuppressedError allows attackers to escape the sandbox and run arbitrary code. This issue has been patched in version 3.11.0.

Buffer overflow due to incorrect authorization in PLC FW

Memory corruption while processing IOCTL command when device is in power-save state.

vm2 is an open source vm/sandbox for Node.js. Prior to version 3.11.0, VM2 suffers from a sandbox breakout vulnerability through the inspect function. This allows attackers to write code which can escape from the VM2 sandbox and execute arbitrary commands on the host system. This issue has been patched in version 3.11.0.

vm2 is an open source vm/sandbox for Node.js. Prior to version 3.10.5, the fix for CVE-2023-37466 is insufficient and can be circumvented allowing attackers to write code which can escape from the VM2 sandbox and execute arbitrary commands on the host system. This issue has been patched in version 3.10.5.