🚨 CVE-2026-92002
Affected versions of MISP use Redis to throttle repeated authentication-failure log entries. The intent is to avoid excessive duplicate logs while still recording failed authentication activity.


However, User->setupRedis() returns false when Redis cannot be reached. The vulnerable _shouldLog() logic only returned true when a Redis instance existed and no throttle key was present. Therefore, when Redis was unavailable, the function did not allow the log write at all, effectively silencing authentication-failure logging for the duration of the outage.

Version affected: ≤2.5.45

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🚨 CVE-2026-92003
Affected versions of MISP do not consistently apply the existing authentication-failure logging throttle.


Two API authentication failure branches wrote directly to the Log model:

 - API requests with no authentication key;
 - requests supplying an API key with an incorrect length




Unlike other authentication failures, these paths bypassed _shouldLog(), so every request could create another durable auth_fail entry.

Version affected: ≤2.5.45

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🚨 CVE-2026-48737
pyLoad is a free and open-source download manager written in Python. Prior to 0.5.0b3.dev101, is_global_address in src/pyload/core/utils/web/check.py relies on Python's global-address classification without examining IPv4 destinations embedded in 6to4 or NAT64 IPv6 addresses. A low-privileged user can submit an IPv6 literal through parse_urls to the pre-resolution is_global_host guard. Because host_to_ip is pinned to AF_INET, that guard does not evaluate a hostname's AAAA result. Separately, curl resolves hostnames before the pycurl PREREQFUNC in src/pyload/core/network/http/http_request.py applies the same vulnerable is_global_address check to the actual connection address, so a transition-form AAAA result can be permitted even when it terminates at an embedded loopback, private, CGNAT, or link-local IPv4 address. Exploitation requires the pyLoad host to route the applicable transition mechanism, including 6to4 on affected Python 3.9 through 3.11 deployments or NAT64 on a network with a NAT64 gateway. Successful exploitation can enable internal-network reconnaissance, timing-based confirmation, limited service disruption, or cloud metadata disclosure where the wrapped address is routable. This issue is fixed in version 0.5.0b3.dev101.

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🚨 CVE-2026-48987
pyLoad is a free and open-source download manager written in Python. Prior to 0.5.0b3.dev101, EventManager in src/pyload/core/managers/event_manager.py appends a Client object to the clients list for each unique uuid submitted to the authenticated getEvents API endpoint, but get_events does not invoke the available clean method to remove inactive clients. An authenticated user can repeatedly submit unique UUID values, causing retained client objects and process memory to grow without bound even after requests stop. The resulting memory exhaustion can trigger an operating-system out-of-memory termination of pyLoad or host-wide instability and denial of service. This issue is fixed in version 0.5.0b3.dev101.

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🚨 CVE-2023-54397
Tornado before 6.3.3 contains an HTTP request smuggling vulnerability due to improper parsing of Content-Length headers accepting non-standard characters. Attackers can send crafted HTTP requests with these characters to bypass proxy validation and smuggle requests when deployed behind certain proxies.

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🚨 CVE-2024-14029
Tornado before 6.4.1 ignores duplicate Transfer-Encoding: chunked headers, treating requests as having no message body and parsing the chunked body as a subsequent request. Attackers can exploit this inconsistency when Tornado is deployed behind proxies to perform HTTP request smuggling, enabling access control bypass, cache poisoning, or connection desynchronization.

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🚨 CVE-2024-58384
Tornado before 6.4.1 contains a CRLF injection vulnerability in CurlAsyncHTTPClient that fails to reject carriage return and line feed characters in request headers. Attackers can inject CRLF sequences into header values to inject arbitrary headers or construct entirely new HTTP requests.

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🚨 CVE-2026-91991
Tornado before 6.5.8 contains an incomplete fix for cookie attribute injection that allows attackers to inject arbitrary cookie attributes by passing capitalized or legacy keyword arguments to set_cookie. Attackers can embed semicolon-delimited data in capitalized parameters like Domain, Path, or SameSite to bypass validation and modify cookie security attributes.

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🚨 CVE-2026-91992
Tornado before 6.5.7 contains a credential leak vulnerability in CurlAsyncHTTPClient where pycurl handles are reused across requests without proper state clearing. Attackers can obtain sensitive credentials by issuing requests through the same client instance, allowing TLS certificates or proxy authentication to persist across unintended requests.

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🚨 CVE-2026-91855
A security flaw has been discovered in Open5GS up to 2.7.7. Affected by this vulnerability is an unknown functionality of the file lib/pfcp/handler.c of the component PFCP Message Handler. Performing a manipulation results in denial of service. Remote exploitation of the attack is possible. The exploit has been released to the public and may be used for attacks. The patch is named 028e1dbb5e3271035ccee906ef417a97fc523f71. Applying a patch is the recommended action to fix this issue. CVE-2025-29339 describes a different assertion failure vulnerability in Open5GS UPF.

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🚨 CVE-2026-77584
Tor before 0.4.9.10 did not reject a CONFLUX_LINK cell that arrives on a circuit which already has attached streams. A malicious client could send a RELAY_COMMAND_BEGIN before the CONFLUX_LINK on the same circuit, attaching an exit stream that would later end up orphan leaving a dangling circuit back-pointer and a use-after-free (UAF) when the circuit is freed. This is TROVE-2026-025.

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🚨 CVE-2026-77587
Tor before 0.4.9.11 is prone to a use-after-free (and potential double free) of a conflux object when a recovery leg revives a conflux set whose last linked leg has already been closed. A malicious exit node could use this to crash a client. This is TROVE-2026-026.

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🚨 CVE-2026-77638
Tor before 0.4.9.11 is prone to a race condition where in just the right circumstances a rendezvous point could man-in-the-middle (impersonate) the onion service that the client was trying to reach.

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🚨 CVE-2026-59279
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

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🚨 CVE-2026-59308
In Spring AI's Semantic Cache support, the context hash used to isolate cached responses between different system prompts could allow cached responses to be shared across unrelated contexts.
Affected versions:
Spring AI: 2.0.0

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🚨 CVE-2026-59318
In Spring AI's tool calling support, the per-request tool list is advertised to the model as a boundary but is not fully enforced when a tool call is dispatched. Under certain conditions, a tool that was not made available to the current request could be invoked, potentially leading to privilege escalation.
Affected versions:
Spring AI: 2.0.0
Spring AI: 1.1.0 through 1.1.8
Spring AI: 1.0.0 through 1.0.9

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🚨 CVE-2026-49114
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.

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🚨 CVE-2026-81665
A heap-based buffer overflow was found in Corosync's Totem Process Group (totempg) message reassembly. When processing fragmented multicast messages, the buffer used to reassemble fragments lacks a runtime bounds check in release builds. A network-adjacent attacker able to send crafted multicast protocol messages to the cluster could cause a heap buffer overflow with attacker-controlled data. This can crash the Corosync daemon, causing a denial of service to the entire cluster, and may potentially allow further exploitation given sufficient heap-corruption control.

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🚨 CVE-2026-84003
Authentication bypass by capture-replay in Microsoft Authentication Library (MSAL) for Node.js allows an unauthorized attacker to perform spoofing over a network.

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🚨 CVE-2026-18061
Improper restriction of XML external entity references in the RemoteQueryCachePlugin in AWS Advanced JDBC Wrapper 3.3.0 through 4.2.0 might allow an actor with write access to the shared cache infrastructure to disclose sensitive files from application hosts that read cached query results, including stored database and IAM role credentials, via crafted XML data in a cached column value.



To remediate this issue, users should upgrade to version 4.3.0 or later.

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🚨 CVE-2026-67211
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.

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