🚨 CVE-2026-43038
In the Linux kernel, the following vulnerability has been resolved:

ipv6: icmp: clear skb2->cb[] in ip6_err_gen_icmpv6_unreach()

Sashiko AI-review observed:

In ip6_err_gen_icmpv6_unreach(), the skb is an outer IPv4 ICMP error packet
where its cb contains an IPv4 inet_skb_parm. When skb is cloned into skb2
and passed to icmp6_send(), it uses IP6CB(skb2).

IP6CB interprets the IPv4 inet_skb_parm as an inet6_skb_parm. The cipso
offset in inet_skb_parm.opt directly overlaps with dsthao in inet6_skb_parm
at offset 18.

If an attacker sends a forged ICMPv4 error with a CIPSO IP option, dsthao
would be a non-zero offset. Inside icmp6_send(), mip6_addr_swap() is called
and uses ipv6_find_tlv(skb, opt->dsthao, IPV6_TLV_HAO).

This would scan the inner, attacker-controlled IPv6 packet starting at that
offset, potentially returning a fake TLV without checking if the remaining
packet length can hold the full 18-byte struct ipv6_destopt_hao.

Could mip6_addr_swap() then perform a 16-byte swap that extends past the end
of the packet data into skb_shared_info?

Should the cb array also be cleared in ip6_err_gen_icmpv6_unreach() and
ip6ip6_err() to prevent this?

This patch implements the first suggestion.

I am not sure if ip6ip6_err() needs to be changed.
A separate patch would be better anyway.

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🚨 CVE-2026-37457
An off-by-one out-of-bounds write vulnerability in the bgp_flowspec_op_decode() function (bgpd/bgp_flowspec_util.c) of FRRouting (FRR) stable/10.0 allows attackers to cause a Denial of Service (DoS) via supplying a crafted FlowSpec component.

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🚨 CVE-2026-7598
A security vulnerability has been detected in libssh2 up to 1.11.1. The impacted element is the function userauth_password of the file src/userauth.c. Such manipulation of the argument username_len/password_len leads to integer overflow. The attack may be launched remotely. The name of the patch is 256d04b60d80bf1190e96b0ad1e91b2174d744b1. A patch should be applied to remediate this issue.

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🚨 CVE-2026-43824
In Argo CD 3.2.0 before 3.2.11 and 3.3.0 before 3.3.9, ServerSideDiff allows reading cleartext Kubernetes Secret data.

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🚨 CVE-2026-33846
A heap buffer overflow vulnerability exists in the DTLS handshake fragment reassembly logic of GnuTLS. The issue arises in merge_handshake_packet() where incoming handshake fragments are matched and merged based solely on handshake type, without validating that the message_length field remains consistent across all fragments of the same logical message. An attacker can exploit this by sending crafted DTLS fragments with conflicting message_length values, causing the implementation to allocate a buffer based on a smaller initial fragment and subsequently write beyond its bounds using larger, inconsistent fragments. Because the merge operation does not enforce proper bounds checking against the allocated buffer size, this results in an out-of-bounds write on the heap. The vulnerability is remotely exploitable without authentication via the DTLS handshake path and can lead to application crashes or potential memory corruption.

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🚨 CVE-2025-70069
An issue in Assimp v.6.0.2 allows a remote attacker to cause a denial of service via the FBXConverter.cpp and ConvertMeshMultiMaterial() method

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🚨 CVE-2026-23918
Double Free and possible RCE vulnerability in Apache HTTP Server with the HTTP/2 protocol.

This issue affects Apache HTTP Server: 2.4.66.

Users are recommended to upgrade to version 2.4.67, which fixes the issue.

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🚨 CVE-2025-70071
An issue in Assimp v.6.0.2 allows a remote attacker to cause a denial of service via the FBXParser.cpp, ParseVectorDataArray()

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🚨 CVE-2026-24118
vm2 is an open source vm/sandbox for Node.js. Prior to version 3.11.0, VM2 suffers from a sandbox breakout vulnerability. 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.

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🚨 CVE-2026-24120
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.

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🚨 CVE-2026-24781
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.

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🚨 CVE-2026-26332
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.

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🚨 CVE-2026-26956
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.

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🚨 CVE-2026-40682
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.

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🚨 CVE-2026-42027
Arbitrary Class Instantiation via Model Manifest in Apache OpenNLP ExtensionLoader





Versions Affected: before 1.9.5, 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.

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🚨 CVE-2026-42440
OOM Denial of Service via Unbounded Array Allocation in Apache OpenNLP AbstractModelReader 

Versions Affected: 

before 1.9.5
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.

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🚨 CVE-2026-29004
BusyBox before commit 42202bf contains a heap buffer overflow vulnerability in the DHCPv6 client (udhcpc6) DNS_SERVERS option handler in networking/udhcp/d6_dhcpc.c that allows network-adjacent attackers to trigger memory corruption by sending a crafted DHCPv6 response with a malformed D6_OPT_DNS_SERVERS option. Attackers can exploit incorrect heap buffer allocation calculations in the option_to_env() function to cause denial of service or achieve arbitrary code execution on embedded systems without heap hardening.

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🚨 CVE-2026-37459
An integer underflow in FRRouting (FRR) stable/10.0 to stable/10.6 allows attackers to cause a Denial of Service (DoS) via supplying a crafted BGP UPDATE message.

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🚨 CVE-2026-42151
Prometheus is an open-source monitoring system and time series database. Prior to versions 3.5.3 and 3.11.3, the client_secret field in the Azure AD remote write OAuth configuration (storage/remote/azuread) was typed as string instead of Secret. Prometheus redacts fields of type Secret when serving the configuration via the /-/config HTTP API endpoint. Because the field was a plain string, the Azure OAuth client secret was exposed in plaintext to any user or process with access to that endpoint. This issue has been patched in versions 3.5.3 and 3.11.3.

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🚨 CVE-2026-42154
Prometheus is an open-source monitoring system and time series database. Prior to versions 3.5.3 and 3.11.3, the remote read endpoint (/api/v1/read) does not validate the declared decoded length in a snappy-compressed request body before allocating memory. An unauthenticated attacker can send a small payload that causes a huge heap allocation per request. Under concurrent load this can exhaust available memory and crash the Prometheus process. This issue has been patched in versions 3.5.3 and 3.11.3.

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🚨 CVE-2026-43964
Postfix before 3.8.16, 3.9 before 3.9.10, and 3.10 before 3.10.9 sometimes allows a buffer over-read and process crash via an enhanced status code that lacks text after the third number.

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